ORMS Today October 2016

CYBERSECURITY: O.R. and the search for ‘cyber subs’

October 2016

Volume 43 • Number 5 ormstoday.informs.org

Also Inside: • AlphaGo: man vs. ‘intelligent’ machines

• Analytics education: leaders weigh in on present & future

Decisions, decisions So many questions, so many answers: • 2016 survey of decision analysis software • Decision definition: irrevocably allocating resources • Election analytics: predicting the next president

Contents October 2016 | Volume 43, No. 5 | ormstoday.informs.org

20 On the Cover The road not taken From corporate decision-making to citizens voting, the world is full of decision analysis problems.

Image © alphaspirit | 123rf.com

F e at ure s 20 24 30

Using big data in cybersecurity

By Douglas A. Samuelson Operations research analysts search for “cyber subs”: defending U.S. cyber assets is mission critical for U.S. military.

Google DeepMind’s AlphaGo

By Hyeong Soo Chang, Michael C. Fu, Jiaqiao Hu and Steven I. Marcus O.R.’s unheralded role in path-breaking achievement signals major advancement of truly “intelligent” machines.

Election Analytics

By Wenda Zhang, Jason J. Sauppe and Sheldon H. Jacobson Student-driven STEM learning lab’s election forecasting website predicts presidency and Senate races.

32

de partm e nt s

6 Inside Story

8 President’s Desk

10 INFORMS in the News

12 Issues in Education

14 PuzzlOR

16 INFORMS Initiatives

18 Viewpoint

54 Industry News

55 Literature Files

56 Classifieds

64 ORacle

14

Present and future of analytics education

By Kaibo Liu, Diego Klabjan, David Shmoys and Joel Sokol Panel discussion: Directors from four of the nation’s top university analytics programs share their insights and expertise.

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October 2016

ormstoday.informs.org

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October 2016 | Volume 43, No. 5 | ormstoday.informs.org

36

INFORMS Board of Directors

President Edward H. Kaplan, Yale University President-Elect Brian Denton, University of Michigan

Past President L. Robin Keller, University of California, Irvine

Secretary Pinar Keskinocak, Georgia Tech

Treasurer Sheldon N. Jacobson, University of Illinois

Vice President-Meetings Ronald G. Askin, Arizona State University Vice President-Publications Jonathan F. Bard, University of Texas-Austin

Vice President- Esma Gel, Arizona State University Sections and Societies

Vice President- Marco Lüebbecke, Information Technology RWTH Aachen University

Vice President- Jonathan Owen, CAP, General Motors Practice Activities Vice President- Grace Lin, International Activities Institute for Information Industry

Vice President-Membership Susan E. Martonosi,

Professional Recognition Harvey Mudd College

Vice President-Education Jill Hardin Wilson, Northwestern University Vice President-Marketing, Laura Albert McLay, Communications and Outreach University of Wisconsin-Madison Vice President-Chapters/Fora Michael Johnson, University of Massachusetts-Boston

Co m puting 36

Editors of Other INFORMS Publications

Decision Analysis Rakesh K. Sarin, University of California, Los Angeles

Decision analysis software survey

By Samantha Oleson Past, present and future of dynamic software emphasizes continuous improvement of vital O.R. tool.

Editor’s Cut Anne G. Robinson, Verizon Wireless

Information Systems Research Ritu Agarwal, University of Maryland I NFORMS Journal on Computing David Woodruff, University of California, Davis

INFORMS Online Kevin Geraghty, 360i INFORMS Transactions Jeroen Belien, KU Leuven on Education

Interfaces Srinivas Bollapragada, General Electric Global Research Center

Management Science Teck-Hua Ho, National University of Singapore Office of the Deputy President (Research and Technology)

n ews

Manufacturing & Service Christopher S. Tang, Operations Management University of California, Los Angeles

Marketing Science K. Sudhir, Yale University

Mathematics of Operations J. G. “Jim” Dai, Cornell University Research

Operations Research Stefanos Zenios, Stanford University

Organization Science Zur Shapira, New York University

Service Science Paul P. Maglio, University of California, Merced

Strategy Science Daniel A. Levinthal, Wharton School, University of Pennsylvania

47 Winter Simulation Conference

49 In Memoriam: Leo G. Kroon

47 In Memoriam: Jack Borsting

50 Annual Meeting Vendors

Transportation Science Martin Savelsbergh, Georgia Institute of Technology

48 In Memoriam: Charles D. Flagle

53 People

49 In Memoriam: András Prékopa

54 Meetings

Tutorials in Operations J. Cole Smith, University of Florida Research

INFORMS Office • Phone: 1-800-4INFORMS

Executive Director Melissa Moore

Headquarters

4 | ORMS Today

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October 2016

INFORMS (Maryland) 5521 Research Park Dr., Suite 200 Catonsville, MD 21228 USA Tel.: 443.757.3500 Fax: 443.757.3515 E-mail: informs@informs.org

ormstoday.informs.org

Welcome to Analytic Solver ® Cloud-based Simulation Modeling that Integrates with Excel

Everything in Predictive and Prescriptive Analytics Everywhere You Want, from Concept to Deployment.

The Analytic Solver® suite makes the fastest Monte Carlo simulation and risk analysis software available in your web browser (cloud-based software as a service), and in Microsoft Excel. And you can easily create models in our RASON® language for server, web and mobile apps.

Comprehensive Risk and Decision Analysis Tools.

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nonlinear optimization, simulation optimization, stochastic programming and robust optimization. And it’s a full-power tool for forecasting, data mining and text mining, from time series methods to classification and regression trees, neural networks and more, with access to SQL databases and Spark Big Data clusters.

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Inside Story

Peter Horner, editor

peter.horner@mail.informs.org

Decisions, decisions “When you come to a fork in the road, take it.”

So said baseball player/philosopher Yogi Berra, apparently explaining his personal decision-making process. Clearly, clarity was not Yogi’s strong suit.

Out here in the real world, making smart decisions can mean the difference between happiness or sadness, success or failure, even life or death. In the corporate world, smart decision-making is perhaps the most prized commodity, which explains why so many decision-makers are turning to high-end analytics to inform their toughest decisions.

Since data-driven, informed decisionmaking goes to the heart, soul and mind of operations research, it should come as no surprise that every issue of OR/MS Today features one if not many articles on the science (and occasional art) of decisionmaking. This issue doubles down on decision-making, including our biennial survey of data analysis software.

In introducing the 2016 survey (page 36), Samantha Oleson, an analyst with the analytics consulting firm Innovative Decisions, Inc., gives readers a brief history lesson of decision analysis and its founders, Howard Raiffa and Ron Howard, before exploring the latest trends and market demands that are shaping today’s and tomorrow’s decision analysis landscape.The survey includes a side-by-side comparison of software packages and a vendor directory.

So what, exactly, is a decision in this context? INFORMS President Ed Kaplan, in his “Member-in-Chief Memo (page 8), recalls a “classic” O.R. definition first used by Ron Howard that includes the phrase, “irrevocably allocating resources.” Kaplan lays out the critical role decision analysis plays not only in countless areas and industries, but also in very personal decisions, such as voting for the president of the United States.

Speaking of the race to the White House, University of Illinois Professor Sheldon Jacobson and a team of grad students maintain an analytics-driven website, Election Analytics, that provides daily forecasts for the presidential and Senate races. For more on the story, see page 30.

Finally, if you’re a college student contemplating pursuing an advanced degree in analytics, is there any more important decision you have to make than deciding which department or program to attend? If you’re an organization looking to hire top analytics talent, which university program or department should you turn to?

Not so long ago, there was basically one choice: the groundbreaking, interdisciplinary Master of Science program founded by Michael Rappa at North Carolina State. It set a high standard for all of those that followed, and boy did they; today, more than 100 universities offer analytics programs to meet the growing market demand.

Last year, Kaibo Liu of the University of Wisconsin organized a panel discussion on the topic of analytics education. The panelists included the leaders of some of the top analytics programs in the country, including Rappa, Joel Sokol of Georgia Tech, Diego Klabjan of Northwestern University and David Shmoys of Cornell University. During the discussion, the panelists shared their experiences of building an analytics programs, in many cases from the ground up, along with their thoughts on effective ways of teaching analytics, course design and the unique strengths of their respective programs.

Liu and the panelists summarized their panel discussion in the article, “Present and future of analytics education” (page 32).Whether you’re a student eyeing grad school or an organization searching for analytics talent, make the right decision and read it. ORMS — Peter Horner, editor peter.horner@mail.informs.org

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October 2016

OR/MS Today Advertising and Editorial Office Send all advertising submissions for OR/MS Today to: Lionheart Publishing Inc. 506 Roswell Street, Suite 220, Marietta, GA 30060 USA Tel.: 888.303.5639 • Fax: 770.432.6969

President John Llewellyn, ext. 209 john.llewellyn@mail.informs.org

Editor Peter R. Horner peter.horner@mail.informs.org Tel.: 770.587.3172

Assistant Editor Donna Brooks

Contributing writers/editors Douglas Samuelson, Matt Drake, John Toczek

Art Director Alan Brubaker, ext. 218 alan.brubaker@mail.informs.org

Online Projects Manager Patton McGinley, ext. 214 patton.mcginley@mail.informs.org

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Advertising Sales Managers Sharon Baker sharon.baker@mail.informs.org Tel.: 813-852-9942 Aileen Kronke, ext. 212 aileen@lionhrtpub.com

Reprints Kelly Millwood, ext. 215 kelly.millwood@mail.informs.org

OR/MS Today Committee James Cochran, chairman

INFORMS Online http://www.informs.org

Lionheart Publishing Online http://www.orms-today.org OR/MS Today (ISSN 1085-1038) is published bimonthly by the Institute for Operations Research and the Management Sciences (INFORMS). Canada Post International Publications Mail (Canadian Distribution) Sales Agreement No. 1220047.

Deadlines for contributions: Manuscripts and news items should arrive no later than six weeks prior to the first day of the month of publication. Address correspondence to: Editor, OR/MS Today, 506 Roswell Street, Suite 220, Marietta, GA 30060. The opinions expressed in OR/MS Today are those of the authors, and do not necessarily reflect the opinions of INFORMS, its officers, Lionheart Publishing Inc. or the editorial staff of OR/MS Today.

Membership subscriptions for OR/MS Today are included in annual dues. INFORMS offers non-member subscriptions to institutions, the rate is $62 USA, $79 Canada & Mexico and $85 all other countries. Single copies can be purchased for $10.50 plus postage. Periodicals postage paid at Catonsville, MD, and additional mailing offices. Printed in the United States of America. POSTMASTER: Send address changes to OR/MS Today, INFORMS-Maryland Office, 5521 Research Park Dr., Suite 200, Catonsville, MD 21228. OR/MS Today copyright ©2016 by the Institute for Operations Research and the Management Sciences.

All rights reserved.

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Welcome to Analytic Solver ® Cloud-based Data and Text Mining that Integrates with Excel

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Full-Power Data Mining and Predictive Analytics.

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distributions, 50 statistics and risk measures, rankorder and copula correlation, distribution fitting, and charts and graphs. And it has full-power, point-and-click optimization, with large-scale linear and mixed-integer programming, nonlinear and simulation optimization, stochastic programming and robust optimization.

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President’s Desk

‘Me m

b e r-in- C h ie f Me m o’

Ed Kaplan

INFORMS President president@informs.org

Irrevocably allocating resources As of early September when this memo was written, the race for the White House had heated up to become one of the hottest contests in memory.

By the time many of you read this, the election could be history, Americans will have made their decision, and the next president of the United States will have been chosen. Flying beneath the radar of cable television and social media, another election is in play at present, namely, the race for presidentelect and 2018 president of INFORMS. Again by the time you read this, the newest elected leader of INFORMS will be known.

Both of these elections are examples of collective decisions, and both reflect the by now classic O.R. definition of “decision” introduced by Ron Howard in his 1966 paper “Decision Analysis: Applied Decision Theory.” Howard’s definition: “A decision is an irrevocable allocation of resources, irrevocable in the sense that it is impossible or extremely costly to change back to the situation that existed before making the decision.

Thus for our purposes a decision is not a mental commitment to follow a course of action but rather the actual pursuit of that course of action.” Indeed, once the president of either INFORMS but especially the United States is chosen, it would be extremely costly and difficult to deliberately roll back the clock and return to the state where those elected were no longer so!

It is this commitment to and implementation of action that distinguishes how operations researchers think about decisions compared to, say, historians and psychologists. And, it is exactly this focus on decisions-as-resource-allocation that is the hallmark of so many of our research 8 | ORMS Today

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October 2016

contributions over the 60+ years our professional association has existed, dating back to the founding of ORSA in 1952.

Indeed, we are the exper ts of decision-aiding technology. That is reflected in the terminology of even our most technical contr ibutions.

Optimization models encode choices via the use of decision variables. The entire field of decision analysis à la Howard Raiffa, Ron Howard, Ralph Keeney and others has evolved within our professional world to the point where INFORMS boasts both its own Decision Analysis Society and supporting journal titled, appropriately enough, Decision Analysis. And, in the idiosyncratic work of our members across many disparate areas – communications, e-commerce, health care, manufacturing and service operations, military operations, policy modeling and analysis, transportation – models of varying complexity are constructed to capture the most salient features of whatever is studied in order to help evaluate the consequences of alternative decisions en route to identifying the best course of action.

Paraphrasing one of the four goals in the INFORMS strategic plan adopted during our Winter 2016 board meeting: Decision-makers will have access to and use our approaches to transform visions/ tasks into better choices to achieve better outcomes. While members surely agree that this is a worthy goal, simply saying this is so does not make it so.

Simply put, INFORMS could use your advice regarding how to better reach out to decision-makers to provide better awareness of and access to ready-to-go decision-aiding tools.

Some of you have already provided wonderful examples of what can be

achieved by creating websites from which your models can be deployed, either via download or in real time online. As an example, consider the RealOpt© suite of models developed

by Professor Eva Lee and her colleagues at Georgia Tech to help public health systems plan and allocate resources for all hazards emergency response. Developed for the Centers for Disease Control, the system is available to any public health system. Perhaps INFORMS could create an online library of links to functioning models (and how-to users guides) that could then be publicized by INFORMS as a resource for decision-makers in different areas.

INFORMS already offers var ious educational programs and focused conferences across our areas of expertise. Perhaps there is also room for a conference showcasing our best decision-aiding tools for a carefully targeted audience of leading decision-makers.

Beyond the usual goals of our meetings, this meeting would have the tightly focused goal of technology transfer: have decision-making tools, will help make decisions!

Election season reminds us what is at stake when high-profile decisions must be made. And make no mistake – decisions will be made, with or without our input. Members of INFORMS, let’s do all that we can to make sure our decades of research and expertise in decision-making are used when consequential decisions are made, rather than merely provide a lens for outside commentary after the fact. Indeed, promising approaches to reaching decision-makers with the best we have to offer deserve the irrevocable allocation of INFORMS resources. ORMS ormstoday.informs.org

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INFORMS in the News

Compiled by Ashley Kilgore and Olivia Schmitz

STEM literacy, CAP, 2016 elections and more INFORMS members, initiatives and journals continue to make news on a wide range of topics in a variety of forums. Following are recent examples of “INFORMS in the News”: STEM crisis, STEM surplus and STEM literacy Is there a STEM (science, technology, engineering and mathematics) crises or a STEM surplus, and if STEM literacy is so important for today’s job seekers, why don’t more young people take STEM courses? Those are some of the questions a recent article in The Wall Street Journal considered, an article that leaned heavily on a 2012 opinion piece by Massachusetts Institute of Technology professor and former president of INFORMS Richard Larson, who says, “A person has STEM literacy if she can understand the world around her in a logical way guided by the principals of scientific thought.”

- The Wall Street Journal, Aug. 16

Standing out in the crowd: CAP certification helps distinguish young analytics talent As the demand for analytics professionals continues to grow, and more and more universities are adding or expanding their analytics programs, it is increasingly important for young analytics professionals to stand out to potential employers. In an editorial for KDnuggets, INFORMS member Alan Br iggs, a project manager and data scientist with Elder Research, Inc., discusses how the new Associate Certified Analytics Professional (aCAP™) program can place emerging analytics professionals on the path to success.

- KDnuggets, Sept. 13

Building CEO trust in data According to a recent KPMG study, CEOs are relying on an abundance 10 | ORMS Today

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October 2016

of data and analytics to make critical management decisions, however many CEOs do not trust the data they receive.

INFORMS member and University of Notre Dame Professor Scott Nestler discusses the value of the Certified Analytics Professional (CAP®) program in an editorial for insideBIGDATA. The high standards adhered to by the CAP certification program can instill confidence in CEOs and other leadership of the quality of an analytics professional’s data.

- insideBIGDATA, Sept. 13

Minimizing supermarket line wait times Tired of waiting in line at the supermarket? You aren’t alone. According to Massachusetts Institute of Technology professor and for mer president of INFORMS Richard Larson, Americans spend an estimated 37 billion hours a year waiting in lines. However, keeping certain tips and tricks in mind can help minimize your wait time.

- The New York Times, Sept. 7

Consumer online search habits provide opportunity for retailers and advertisers After identifying a sample of 1,000 digital camera purchases from the browsing and purchase history of more than two million consumers, INFORMS members Bart Bronnenberg of Tilburg University and Carl Mela of Duke University, with Jun Kim of the Hong Kong University of Science and Technology, discovered unique insight on how advertisers and retailers can influence

the final purchase. Their findings will be published in the INFORMS journal Marketing Science.

- The Times of India, Sept. 7

Leading the data analytics pack As women are making an increasingly significant impact on the data analytics field, Forbes featured a list of nine accomplished female analytics experts, including Brenda L. Dietrich, former INFORMS president, who leads the data science function of IBM Business Analytics Insights as a Service unit.

- Forbes, Aug. 29

Using analytics to predict the 2016 elections Starting with the 2000 presidential elections, INFORMS member Sheldon Jacobson, professor with the University of Illinois, and a team of fellow researchers and students, have used a combination of poll numbers, Sheldon Jacobson algorithms, and analysis to make a state-by-state assessment of who is most likely to be elected in the upcoming presidential and Senate elections [see page 30].

- Fox Illinois, Aug. 19

Why we ignore security alerts Naked Security, the online news room for data security company Sophos, highlighted an article in the INFORMS journal Information Systems Research addressing the effectiveness of systemgenerated computer security warnings.

As much as 87 percent of these warnings are simply ignored, due to a combination of badly timed interruptions and our inability to multitask.

- Naked Security, Aug. 19

Maximizing 2016 Olympics’ coverage Press covering the Olympic Games in Rio this summer faced multiple challenges in their efforts to attend as many events as possible, including event ormstoday.informs.org

timing and location, weather and travel logistics. Carnegie Mellon professor and INFORMS member Michael Trick helps a New York Times reporter create a plan to approach his coverage of the 2016 games.

- The New York Times, Aug. 18

As the CEO, a good golf score may mean you are underperforming in the office A study published in the INFORMs journal Marketing Science explores the relationship between a CEO’s golf game and his or her cor porate perfor mance. This study found that the more time CEOs spend on the golf course, the less time and effort they are likely to commit to their organization. The study also found that CEOs whose pay packages include stock options and stock grants have more incentive to focus on their work than golf as they have a greater stake in the firm’s success. In addition, according to Bigger staff , “We are finding evidence that if you play a lot of golf you tend not to be the CEO next year.”

- The Fiscal Times, Aug. 8

Clarkson University recognized by INFORMS Rothkopf Rankings The “Rothkopf Rankings,” published in May 2016 in the INFORMS journal Interfaces, recognized Clarkson University as a top U.S. school for contributions to operations research practice literature.

- North Country Now, Aug. 6

Using Twitter to predict TV program ratings INFORMS members Professor Xiao Liu of New York University and Professors Param Vir Singh and Kannan Srinivasan of Carnegie Mellon Univer sity conducted a study on which digital platforms are the most effective at gauging the success of a TV program. The study, which will be published in the INFORMS journal Marketing Science, found that Twitter is significantly more effective than other platforms, including Google Trends,

Wikipedia, IMDb and The Huffington Post, at predicting TV ratings.

- Science Newsline, Aug. 2

Kuwaiti healthcare reforms maximize efficiency According to Nicos Savva, INFORMS member and associate professor at the London Business School, the reforms to the Kuwaiti healthcare system outlined in the Kuwait Development Plan for 2015-2020 could result in one of the most efficient healthcare systems in the world. In particular, investments in specialization and preventative care hold the key to improving both patient outcomes and hospital productivity.

- Kuwait Daily News, Aug. 1

Utilizing RFID to monitor hospital hand-hygiene compliance is only part of the solution A study that will be published in the INFORMS journal Management Science was highlighted for the insight it provided on the efficiency of radio frequency identification (RFID) systems in monitoring hand-hygiene compliance in healthcare facilities. INFORMS member Professor Bradley Staats of the University of North Carolina was among the researchers on the study who found that while individual electronic monitoring can dramatically improve compliance, managerial commitment must continue for these positive results to be sustained.

- RFID Journal, Aug. 1

Smart technology, not body cameras, leads to less lethal force by police Using data from a Washington Post comprehensive report, two INFORMS members investigated the impact of technology on police performance and practice. Professors Min-Seok Pang and Paul Pavlou, both from Temple University’s Fox School of Business, found that the use of analytics and smartphones to access intelligence led to decreased instances of lethal force by police, whereas wearable video cameras were linked to an increase in lethal force on civilians by police.

- Security Magazine, Aug. 1

Revolutionizing promotional pricing Georgia Perakis, INFORMS member and professor at Massachusetts Institute of Technology, led a team of Ph.D. students, in partnership with Oracle, in developing a model approach to determine optimal promotional retail pricing. Compared to current methods, the newly developed model is able to identify the potential for 3-10 percent improvement in profits.

- The Huffington Post, July 26

Optimizing Monday Night Football Two INFORMS members from the University of Iowa’s Tippie College of Business, doctoral student Bhupesh Shetty and Associate Professor Jeffrey Ohlmann, in conjunction with Professor Gary Gaeth, developed an optimization model to improve Monday Night Football schedules. By analyzing every Monday night game played between 1993 and 2008, the researchers discovered three factors that have the greatest impact on generating high ratings: games played by Super Bowl champions, teams with high profile players or coaches joining the team, and teams with high-powered offenses.

- Science 2.0, July 26

Minimizing food waste, especially meat products, can help the environment The global demand for meat is continuing to rise, and with meat waste accounting for 21 percent of the global food waste carbon footprint, it is more important than ever to limit how much of our meat leftovers go to waste. Ronald McGarvey, INFORMS member and assistant professor at University of Missouri’s Industrial & Manufacturing Systems Engineering Department, discusses the impact that food waste, particularly meat, has on the environment.

- The Huffington Post, July 25

For links to the complete articles mentioned above, visit http://bit. ly/2dKsqtU ORMS Ashley Kilgore (akilgore@informs.org) is the public relations manager at INFORMS. Olivia Schmitz (oschmitz@informs.org) is the marketing coordinator at INFORMS.

October 2016

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Issues in Education

By Gopalakrishnan Narayanamurthy, Anand Gurumurthy and Raju Chockalingam

Lean thinking: a biz school experience The Toyota Production System in the name of lean production has been widely studied and documented in the manufacturing sector [1]. In recent years, an adapted version of lean production in the name of lean thinking (LT) has entered the healthcare sector (e.g.,Virginia Mason Medical Center, Intermountain Healthcare, Shouldice Hospital,Thedacare, HealthEast Care System, etc.) and software service sector (e.g.,Wipro Technologies, etc.).Very recently, studies have anecdotally captured the experience of LT implementation in educational institutes.The authors’ study, outlined below, adds to this limited literature by developing a framework for LT implementation in educational institutes by studying the experience of implementing process improvement in a business school.

grams. The framework we developed for LT implementation consists of five steps: Step 1. Construct process flow diagram (PFD) for all the degrees offered by the educational institute. Identify key stakeholders from the different degrees areas and involve them in the process of constructing the PFD, which should capture various function areas within a degree and associated processes, as well as interdependency between processes and function areas.

Step 2.Value stream mapping (VSM) of a specific degree to be studied. Select a degree from Step 1 for further analysis [2]. Stakeholders related to the selected degree have to be deeply involved.The selected degree can be further split into divisions based on its complexity, and a suitable division within a degree can be selected for LT application.

Among the five degrees, flagship degree Framework for LT Implementation was selected for LT implementation. This in Educational Institutes degree utilizes the majority of the physical The business school in question, lo- resources of the school and hence contains cated in India, includes an administrative huge potential for the application of LT to staff of 66, along with 64 full-time and eliminate waste and to establish efficient 26 adjunct faculty members distributed workflow. Processes in the flagship degree are across eight academic areas, and about 750 cyclical in nature and repeat on a term basis students spread across various degree proevery three months.We developed a detailed VSM for a term within the flagship degree.

Step 3. Identify different types of waste and inefficiencies in the chosen degree. In this case, we identified the following six processes: rework, motion, waiting, overprocessing, overproduction and defects.

Rework captures the defects that are irreversible. Several problems and associated waste were then identified for the processes within a term, including class scheduling, procurement and distribution, teaching sessions, feedback, assessment and grading. For example, the use of hardcopy forms for the feedback process involved three instances of waste: overprocessing, overproduction and defects.

Step 4. Implement solutions from LT Figure 1: (a) difference in number of sessions lens to eliminate waste in the degree’s absent across the terms, (b) number of unfilled value stream. Lean tools and practices seats for electives offered in each term, (c) can be selected and suitably adapted comparison of missed feedback responses in each for educational institutes to identify

potential solutions. Once the solutions are proposed, future-state VSM is constructed.

Feasible solutions using the LT lens were proposed by the stakeholders for all the problems. For the “hardcopy forms” problem in the “feedback” process, an online feedback portal ensuring a 100 percent feedback system was deployed by anchoring it to the electronic data interchange (EDI) lean practice.

Step 5. Compare the change in performance measures and pursue continuous improvement. The benefits realized must be compared by evaluating the performance measures before and after the implementation of LT. After comparing the benefits, all of the degrees have to be reanalyzed, and one of them needs to be selected to repeat Steps 2-5 in pursuit of perfection through kaizen. Archived data was collected on student attendance, elective choice and feedback from the business school. Absenteeism increased across the terms in both batches, but the amount of increase was smaller in Batch 2 (Figure 1a).The number of unfilled seats in an elective course was drastically reduced in Batch 2 (Figure 1b), which can be attributed to the readily available elective course outlines on the online portal. Missed feedback responses were also reduced after LT implementation (Figure 1c).

The proposed framework presented above lacks generalization as it was developed from the experience of a single business school. It needs to be empirically validated by applying it to multiple educational institutes in order to check the long-term impact of lean thinking. ORMS Gopalakrishnan Narayanamurthy, Anand Gurumurthy and Raju Chockalingam are faculty members in the Quantitative Methods & Operations Management (QM & OM) Area at the Indian Institute of Management, Kozhikode, Kerala, India. This article is an abridged version of their manuscript titled, “Applying Lean Thinking in an Educational Institute – An Action Research.”

REFERENCES 1. Holweg, M., 2007, “The genealogy of lean production,” Journal of Operations Management, Vol. 25, No. 2, pp. 420-437.

2. Narayanamurthy, G., and Anand, G., 2014, “Process selection for implementing lean thinking: An AHP application, NITIE-POMS International Conference 2014, Dec. 18-21, 2014, NITIE, Mumbai, Maharashtra, India.

term.

12 | ORMS Today

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October 2016

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Camping in the woods You have found yourself lost in the woods, and you don’t expect to be found for several months.You’ll need to build a camp so you are in close proximity to water, food and firewood in order to survive the coming winter.

Fortunately you have a map of the local area’s resources (Figure 1), which should help you decide where to set up your camp. The available resources are water (indicated by the blue drop icon), firewood (indicated by the brown log icon) and food (indicated by the red rabbit icon).

Choose any green location to set up your campsite with the goal of minimizing your daily travel distance to resources.

Unfortunately some resources require multiple trips per day to meet your needs. Water requires three trips per day, firewood requires two trips per day, and food requires one trip per day.

You must always return back to camp after visiting any resource location. Assume resources never run out.

For example, if you build your camp at location I9, you will have to travel a total of 32 units per day (12 units for water because it is four units round trip times three trips per day, 20 units for firewood

CALL FOR ENTRIES A $15,000 Competition with a $10,000 First Prize

Application Deadline: October 19, 2016

Wednesday, October 19, 2016 Deadline to provide a single pdf document containing a three-page summary of your achievement, and a cover page with a 60-word abstract, and the name, address, phone number, and affiliation of each author.

Monday, December 12, 2016 Finalists will be selected based on the summaries and the INFORMS/CPMS verification process.

Friday, February 10, 2017 Deadline for finalists to provide a full written paper.

Monday, April 3, 2017 Each finalist group will give an oral presentation of their work in a special session at the INFORMS Conference on O.R. Practice Business Analytics & O.R.in Las Vegas, NV, April 2−4, 2017.

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because it is 10 units round trip times two trips per day, and zero units for food because your camp occupies the same location).

Question: At which location should you build your camp?

Send your answer to puzzlor@gmail.com by Dec. 15. The winner, chosen randomly from correct answers, will receive a $25 Amazon Gift Card. Past questions and answers can be found at puzzlor.com. ORMS John Toczek is the AVP Predictive Modeling at Chubb in the Decision Analytics and Predictive Modeling department. He earned his BSc. in chemical engineering at Drexel University (1996) and his MSc. in operations research from Virginia Commonwealth University (2005).

ABOUT THE COMPETITION

The purpose of the competition is to bring forward, recognize, and reward outstanding examples of operations research, the management sciences, and advanced analytics in practice. The client organization that uses the winning work receives a prize citation; the authors of the winning work receive a cash award.

ENTRY REQUIREMENTS

Visit the website www.informs.org/edelmanaward for detailed information.

KEY DATES FOR THE COMPETITION

14 | ORMS Today

Figure 1: Where’s the optimal place to set up a campsite?

October 2016

Entries should report on a completed practical application and must describe results that had a significant, verifiable, and preferably quantifiable impact on the performance of the client organization. Finalist work will be published in the January-February 2018 issue of Interfaces.

Any work you have done in recent years is eligible, unless it has previously been described by a Franz Edelman Award finalist. Previous publications of the work does not disqualify it. Anyone is eligible for the competition except a member of the judging panel.

EMAIL SUBMISSIONS

Please email your submission to Anne.Robinson@VerizonWireless.com Anne G. Robinson, 2017 Edelman Award Competition Chair The Pr

CPMS

ormstoday.informs.org

What’s Your StORy? Terry Harrison, CAP Professor of Supply Chain and Information Systems Earl P. Strong Professor of Business Faculty Director of Business Analytics Length of INFORMS membership: If you count the heritage organizations of ORSA and TIMS, I became a member of both in 1980 or 1981.

How do you define “analytics”?

I use the INFORMS definition of “the scientific process of transforming data into insight for making better decisions.”

What was your favorite experience as INFORMS president? What did you accomplish during your tenure that you are most proud of?

Answering that is a bit of a challenge. I had a number of very good experiences during my year as president. Perhaps my favorite experience was working with the INFORMS board and administration—all very good, positive people. Helping with INFORMS nascent analytics effort was very satisfying.

What about your career might surprise us?

My “career” started as a logger and then as a forester.

If you had to work on only one project for the next year, what would it be?

Being a good husband, father, and grandfather.

What is the best advice you can give to students in your field?

Work on projects or causes that you love and believe in. It is the difference between a job and a career.

How do you relax?

I spend a lot of time outdoors. I also enjoy making furniture.

Which INFORMS journal do you read the most? Why? Management Science and Interfaces to see new methods and applications.

More questions for Terry?

Ask him in the Open Forum on INFORMS Connect!

http://connect.informs.org

INFORMS Initiatives

Annual meeting, CAP, pro bono work & more INFORMS Annual Meeting provides valuable insight for practitioners The prog ram for the 2016 INFORMS Annual Meeting in Nashville, Tenn., on Nov. 13-16 features a variety of content targeting topics of interest to analytics practitioners.

In addition to the presentation of the Daniel H. Wagner Pr ize, which recognizes excellence in analytics practice, a selection of plenary and keynote speakers from organizations such as IBM and Amazon, panel discussions, sessions and presentations will all highlight the latest news and applications of analytics. From h e a l t h c a re, t o s u p p l y c h a i n s , t o c o g n i t i ve c o m p u t i n g , m e e t i n g attendees will have access to the latest developments in all areas of analytics application. For more infor mation, visit: http://meetings2.informs.org/ wordpress/nashville2016/registration/

Associate CAP helps young analytics professionals stand out to employers The INFORMS Associate Certified Analytics Professional (aCAP™) program enables emerging analytics professionals to obtain a competitive advantage over their peers with the distinction of a certification, while affording them the opportunity to build the experience and soft skills necessary for a full CAP certification. In addition, it provides employers with a trusted and independent verification of analytics knowledge of someone who is in the early stages of their career, making it easier for hiring managers to identify the best possible analytics talent. Universities will also be able to tout the numbers of their graduates who have obtained the aCAP, and later the full CAP, as part of their marketing efforts to prospective students, helping those analytics programs further stand out.

For more information, visit: https://www. certifiedanalytics.org/associate_cap.php

Continuing Ed: Essential practice skills for analytics projects I m m e d i a t e l y f o l l ow i n g t h e upcoming 2016 Annual Meeting In Nashville, Tenn., INFORMS will host a unique continuing education oppor tunity. Patr ick S. Noonan, a professor at Emor y University’s Goizueta Business School and whose exper ience with the management consulting profession spans 30 years, will teach an intensive, hands-on, twoday course titled “Essential practice skills for high-impact analytics projects” on Nov. 17-18 in Nashville. The course, p a r t o f I N F O R M S ’ C o n t i nu i n g Education program, is aimed at analytics professionals looking to sharpen and expand their soft skill sets for realworld problem-solving. For more information, visit: https://www.informs. org/Certification-Continuing-Ed/ INFORMS-Continuing-Education

Call for INFORMS awards Deadlines are quickly approaching to submit nominations for a number of INFORMS pr izes and awards, including the Franz Edelman Award (Oct. 19), recognizing the contributions of operations research and analytics; the UPS George D. Smith Prize (Oct. 31), highlighting strong connections between industry and higher education; and the INFORMS Prize (Dec. 1), awarding organizations for the integration of advanced analytics in OR/MS. For more information, visit: https://www.informs. org/Recognize-Excellence

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October 2016

New competition for tomorrow’s leaders in O.R. & analytics A brand new INFORMS competition provides real-world workplace experience for undergraduate and master’s level students. Student teams will be given the same business problem, data sets and access

to software to solve a challenging problem using an O.R./analytics approach. A panel of industry and academic experts will judge written submissions based on teams’ use of the full analytics process, from framing the problem to methodology selection, data use, model building, and innovation. Demonstrated “soft skills” in teamwork, communication and presentation will also be considered in judging.

The top five teams will cash awards: $7,500 (first place), $5,000 (second place), $3,500 (third place), $1,500 (fourth place), $1,000 (fifth place). In addition, finalist teams will receive a stipend to offset the cost of travel and conference registration. For more infor mation, visit: http://connect. informs.org/oratc/home.

Submit a project for Pro Bono Analytics Do you know a company that would benefit from analytics assistance? Maybe it could better utilize its data to operate more effectively, or need assistance in accurately measur ing, tracking and assessing success. Pro Bono Analytics connects organizations with a volunteer expert skilled in using analytics processes and tools to help answer such tough questions. Visit the Pro Bono Analytics website where analytics volunteers and nonprofit organizations connect. For more information, visit: http://connect. informs.org/probonoanalytics/home Editor’s Cut 2016, Vol. 5 (Big Data Analytics) now available INFORMS Editor’s Cut is a new, open access, comprehensive online multimedia library that identifies and utilizes a variety of great information about operations research and analytics across a range of current topics and issues. The latest issue on Big Data Analytics provides access to a wealth of content, including journal articles, media stories, podcasts and videos, as well as a variety of additional information from INFORMS and other sources on key issues, challenges and opportunities in big data. For more information, visit: http://pubsonline.informs. org/editorscut/bigdata ORMS ormstoday.informs.org

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Viewpoint

By Joseph Byrum

Crowdfarming, or how to boost agricultural innovation Earlier this year, Land O’Lakes surveyed young people about their views on the viability of a career in agriculture. The results contained a tough truth about the need for our industry to embrace and highlight innovation driven by analytics.

The survey found the younger generation lacks an interest in lending talent to the industry responsible for feeding the nation and the world.

A mere 3 percent of college grads said that they would consider a career in agriculture [1]. The rest prefer to start a profession in technology or healthcare, which they see as more advanced with better paying opportunities.

It is clear that ag r iculture has a ser ious image problem among mathematically inclined youth. Yet

food production should absolutely be on the minds of students who want to see a job offer letter in their hands come graduation time, as opportunity is abundant. More than 22,000 ag jobs [1] go unfilled each year, according to the U.S. Department of Agriculture – and they are good jobs. Students might associate agriculture with backbreaking labor and low-tech approaches, but nearly a third of the available jobs require skills in science, engineering and math [3].

We cannot afford to allow another generation of new talent and new ideas to pass us by.

Many of the biggest players in agr iculture appear to be fine with things as they stand. After all, having a positive cash flow can lure executives

Only 3 percent of college grads say they would consider a career in agriculture.

Source: Syngenta

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October 2016

into believing that they have everything they need. They are getting by just fine, and prospering, without regular infusions of fresh ideas and perspectives.

Or so they think.

Complacency is often an invitation to disruptive innovators to enter and capture the market. Innovators know the key to upending the status quo is investing in the high-level talent needed to bring about the revolution in production and efficiency, as we have seen throughout history. The light bulb put candlemakers out of work, but the invention did not just spring out of nowhere. The team of brilliant minds working in Thomas Edison’s Menlo Park, N.J., R&D lab, the first of its kind, came up with the system that made electric lights practical. Edison understood the importance of developing talent, and the world has not been the same ever since.

I believe data analytics can bring a similar revolution to agr iculture through team-based innovation. Our experience at Syngenta has demonstrated the benefit of optimizing the breeding of soybean and other crops with advanced mathematics. Optimization essentially doubled the efficiency of our breeding program, resulting in significantly higher crop yields while minimizing the need for scarce inputs like land, nutrients and water. The benefits are tremendous, but building analytical capabilities within agriculture is extremely difficult.

Plant biology is as wonderful as it is complex. A soybean has 46,000 genes that determine its potential, creating an effectively infinite number of genetic combinations. Modeling this complexity in a single crop was a challenge that took almost a decade of hard work.

The next step that will, I believe, produce disruptive innovation in agriculture will come from applying data analytics to every crop, and every process involved in the production of food from the breeding of seeds to the construction of farm equipment and delivery of food products to store shelves.This is a monumental undertaking, but it is also one that needs to ormstoday.informs.org

happen if agriculture is going to have the productivity needed to keep up with a global population set to rise by 2 billion people in the next few decades.

To have enough food to ensure everyone is well fed, we must have a revolution in productivity. That, in turn, will require an infusion of science, engineering and mathematical talent in agriculture, which brings us back to the original problem. How do we attract young graduates in the science, engineering and mathematical fields to agriculture?

I believe crowdfarming is one way to help cultivate interest in agriculture.

By that, I mean the application of open innovation principles to lure individuals who may have never given a second’s thought to working in agriculture to participate in our biggest scientific problems. Many online platforms allow companies to post discrete challenges that offer a monetary reward to anyone

who comes up with a valid solution, and when they are properly managed, the results speak for themselves.

A g reat example of this is the Syngenta Crop Challenge in Analytics, a program administered by INFORMS that brings the power of the best minds in analytics to bear against the global problem of food security. Participants receive a data set describing how soybean varieties perform under different seasonal and soil conditions along with a second data set that describes the soil and weather conditions across the geographic regions where soybean is grown. For 2017, the winning entrant must develop a defensible methodology for selecting the mix of varieties that will achieve maximum yield in the next season.

The response to last year’s challenge was tremendous, and the entries that were submitted proved to be top-notch.

More impor tantly, many analytics professionals who have never before

worked in ag r iculture have been hooked by the rewarding nature of work in this area. Many participants have expressed interest in continuing to contribute to the effort.

By opening entries to anyone who has an interest in analytics, crowdfarming invites creativity and new ways of looking at old problems. When done right, it will also help draw badly needed talent to agriculture, ensuring the world’s farmers will have the tools they need to continue feeding everyone. ORMS Joseph Byrum, Ph.D., MBA, PMP, is senior R&D and strategic marketing executive in Life Sciences – Global Product Development, Innovation and Delivery at Syngenta.

REFERENCES 1. https://www.landolakesinc.com/lolinc/media/Pdf/ Press%20Releases/2016/3-15-16-FINAL2.pdf 2. https://nifa.usda.gov/press-release/one-bestfields-new-college-graduates-agriculture 3. https://www.purdue.edu/usda/employment/

Dynamic Ideas llc New TiTles

AdditionAl titles By dynAmic ideAs Cover_R1_4761.qxd 64446_Hard_cover_45xx.qxd

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Abhijit A. Pol and Ravindra K. Ahuja

Each topic covered is illustrated through examples and hands-on tutorials. Each chapter contains several hands-on exercises for additional practice. This book is ideally suited as a textbook but can also be used as a supplementary reference book or a self-study manual. The book Web site, www.dssbooks.com, contains supplementary material for students and instructors including additional case studies.

AUTHORS: Abhijit A. Pol is a researcher in the Department of Computer and Information Science and Engineering at the University of Florida, Gainesville. His research focus is in the area of databases with special interests in approximate query processing and physical database design.

Ravindra K. Ahuja is a professor in the Department of Industrial and Systems Engineering at the University of Florida, Gainesville. He is also the President of Innovative Scheduling, Inc., which specializes in building decision support systems for planning and scheduling problems arising in the field of transportation.

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Develops the theory of integer optimization from a new geometric perspective via integral generating sets

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■

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Covers enumerative and heuristic methods, including local search over exponential neighborhoods and simulated annealing

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Presents the major methods to construct approximation algorithms: primal-dual, randomized rounding, semidefinite and enumerative methods

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Provides a unified treatment of mixed integer and robust discrete optimization

■

Includes a large number of examples and exercises developed through extensive classroom use

Optimization over Integers

“For over a quarter of a century, Urban Operations Research has been a primary source for introducing thousands of students to the world of operations research applications.

Anyone interested in how a city can improve its critical services will find basic and advanced ideas clearly explained and grounded in practicality. Of special interest is the rare discussion on “Implementation.” Here, the novice student and the practiced researcher will find sound advice that will help ensure that their mathematical models will make a difference. Case in point, ‘Beware of the Vanishing Advocate.’”

Saul I. Gass—Professor Emeritus, Robert H. Smith School of Business, University of Maryland, College Park

“Of all the courses I took as an undergraduate and graduate student at M.I.T., Urban Operations Research undoubtedly had the greatest impact on my career and on my way of thinking about the world around me. To this day, over thirty years after taking the course, I often find myself referring to the text for insights and solutions to problems. I would recommend this book to anyone interested in operations research at any level.”

Mark S. Daskin—Bette and Neison Harris Professor of Teaching Excellence, Northwestern University

“Having gone through course after course on the theoretical underpinnings of OR, this book opened my eyes as a student to the impact that OR modeling can have on real-world problems. It showed me how rigorous analysis can be applied to address fundamental problems in society. It’s an absolute classic in the field.”

Patrick T. Harker—President, University of Delaware

“I still use my totally worn-out copy of the first edition of Urban Operations Research, bought when I was a graduate student at MIT. Dick and Amedeo’s book belongs on the desk of all operations researchers, not only those interested in efficient resource allocation of urban services. It is one of the finest examples of the power of quantitative modeling. The text is a classic and I am delighted to see it re-edited.”

Patrick Jaillet—Edmund K. Turner Professor and Department Head, Department of Civil and Environmental Engineering, MIT

“Urban Operations Research introduced me to realistic and practical modeling of very complex problems. What I learned from Amedeo and Dick changed the way I think and my approach to problem solving, setting the direction for my career. I have been using my loose-leaf, pre-publication copy ever since 1978 when I took the course.”

Urban Operations Research

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Developing Web-Enabled Decision Support Systems is a comprehensive book that describes how to build data-driven, Web-enabled decision support systems using a Microsoft Access database, VB .NET, and an ASP .NET framework, and illustrates it using several case studies arising in Operations Research, Industrial Engineering, and Business. The book contains five parts:

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“Urban Operations Research is a tremendous resource for improved modeling and decision making in today's dynamic business environment—both an essential text for preparing students and a valuable reference for experienced OR practitioners."

Dimitris Bertsimas is the Boeing Professor of Operations Research at the Massachusetts Institute of Technology and Robert Weismantel is Professor of Mathematics in the University of Magdeburg, Germany.

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ORMS Today

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Defending U.S. cyber assets against adversaries is one of the most critical tasks the U.S. military faces.

Source: U.S. Army

Using big data in cybersecurity Operations research analysts search for ‘cyber subs’

By Douglas A. Samuelson

20 | ORMS Today

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October 2016

Defending U.S. cyber assets such as computer network, operational and intelligence systems against adversaries is one of the most critical tasks the U.S. military faces. The U.S. Army Cyber Command and Second Army (ARCYBER & 2A) has implemented a new, big data approach to address the challenges inherent in this task, exemplary not only for what it is accomplishing but also as a model for how to conduct analytical studies in a fast-paced, complicated setting.The team has created an integrated structure of large data sets, quick connections between them and readily usable tools to enable swift analyses by operators in deployed real-world missions.They can create prototypes in a week and deliver functional web-based analytics at mission-relevant speeds – in often three weeks or less.

In a recent presentation at the Center for Strategic and International Studies, one of the most prominent and respected defense “think tanks” ormstoday.informs.org

representatives in the country, Lt. Gen. H. R. McMaster, pointed out the ARCYBER & 2A team as an especially good example of how analysis should be done in support of military missions. It is his job to know, as he now serves as deputy commander of the Training and Doctr ine Command (TRADOC) and director of TRADOC’s Ar my Capabilities Integration Center. He is noted both as a successful combat commander, especially as a brigade commander in Iraq in 1991, and as a provocative, iconoclastic thought leader. He wrote one of the most highly regarded cr itiques of U.S. military policy and doctrine in the escalation of the Vietnam War [1] and managed to continue to advance in the Army, no small feat.

Lt. Col. Cade Saie leads the small U.S. Army Maj. Ross Schuchard (left) and Lt. Col. Cade Saie look over a document at Fort Belvoir, Va. team that built the capability, along Source: U.S. Army with Maj. Isaac Faber, who recently returned to graduate school for Ph.D. studies, Edward Cardon chartered the creation of a small and Maj. Ross Schuchard. “Cyber is different,” ORSA (operations research/systems analysis) cell Maj. Faber explained. “Traditional statistics don’t within the command. By taking this approach, Lt. is work because everything is incredibly non-linear. Col. Saie amplified, “Analytics is then embedded There’s a high false positive rate, so operational into the daily operations routine.” commanders lose interest pretty quickly if you The ARCYBER ORSA team spent the the daily can’t do better.” first year after its founding in late 2014 doing The characteristics of these types of systems some traditional O.R. analyses and modeling, require adaptation in operations research developing some cyber operations metrics, and approaches, as well as a re-thinking of military defining requirements for a big data platform tactics. For mal O.R. approaches such as that would support the expansion of advanced regression and optimization give way to rapid analytics and cutting-edge O.R. techniques and - Lt. Col. Cade Saie adaptation and generating multiple options. dissemination of those techniques to operators Additionally, the traditional military tactics [2]. “We had a big data platform that couldn’t become transformed into a rapid feedback loop be leveraged by operators,” Lt. Col. Saie stated. between defender and adversary, so the operators’ “We needed to create a framework for the analytical requirements change along with the ORSA community to participate more readily in pace of action. analytics with tools widely available in the field One of the key principals in advocating the such as R or Python.” inclusion of O.R. methods in cyber, Maj. Gen. The focus so f ar is on just defensive John Ferrari (U.S. Army Director of Program operations, such as intrusion detection and Analysis and Evaluation), handpicked the team in response. The effort to date has also been limited 2014. He described the problem, referring back to unclassified data, possibly “For Official Use to the roots of operations research, as “searching Only,” but not more restricted than that. The for cyber subs.” As in the World War II search for key is assembling patterns of low-level anomalies attackers, the essential idea is to place the analysts that are not of much interest by themselves but with the field commands, close to the situations might, in combination, indicate something worth of interest, and have them work closely with investigating. operational commanders to define the challenges, The Building Blocks: Use Cases produce prototype solutions and rapidly implement. Showing agreement with Ferrari’s The data platform the team built now integrates sevsentiment, U.S. Army Cyber Command’s Lt. Gen. eral dozen live data streams. Defenders identify use

“Analytics embedded into

operations routine.”

October 2016

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ORMS Today

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Cybersecurity cases, that is, activities that are to some extent out of the ordinary, and they and the analysts then build analytics to address operational needs in response to the use cases. Most of these analytics now integrate regression, clustering, time series and visualizations – and heavily emphasize open source software.

Current data assembly relies on a global sensor grid that relays alerts to a central repository, consolidated by a commercial software product known as a Security Incident and Event Manager (SIEM). Queries can be complicated to formulate and slow to execute, with results that an analyst must then manually evaluate. It is difficult to answer complex questions or support even moderate mathematical algorithms. Verifying actions and their effects at multiple levels of activity is also difficult.

Big data technologies enable drastic increases in query speed and data storage limits by leveraging parallel computing. These technologies also create dynamic computing environments to support more advanced analytical tools and methods. Hence, the vision for the future is a federated network of cyber analytics platforms; that is, the data sets are all compatible in terminology and structure and therefore can easily be viewed and studied in combination.

To move toward the new structure, the team gathers problems from the Defensive Cyber Operations (DCO) community as part of the community’s Source: U.S. Army routine functioning. Then, the problem is given to a development partner (Center for Army Analysis, the “Traditional U.S. Military Academy at West Point, the Naval Postgraduate School or the Air Force Institute of Technology) or remains in-house for resolution via analytic development. Once the first version of an analytic is complete, it is deployed on a big because data training system and used/validated by DCO is community members. After feedback is incorporated, the revised analytic is then deployed onto incredibly an operational platform where it then becomes part of the operational workflow for the consuming organization.

The analytics range from simple (provid- U.S. Army Maj. ing sorted counts) to moderate (providing inIsaac Faber teractive network flows) and finally to complex (above) (such as Bayesian change point detection). Some of the most immediate impact of the work was

statistics don’t work everything

non-linear.”

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October 2016

simply observing workflow processes and creating capabilities within analytics that automated some analyst tasks, such as generating reports.

This simple act of addressing a time-consuming aspect of the cyber analyst workflow had a double benefit: helping the team gain operators’ trust and solidifying the rapid analytic development framework. Over a small period of time to test the framework, the team worked closely with a small group of personnel, with a wide range of specialties, to develop a group of use cases and, from there, to produce analytics which helped to identify certain types of malicious behavior and thwart numerous unauthorized communication attempts.

In broad terms, analytics may employ a range of standard descriptive displays, some statistical tools, and innovative data exploration methods to find patterns of activity that are identified as potentially of interest but that would tend to elude more traditional approaches. In Medicare fraud detection, combining data from different types of claims often yields findings that would not have been apparent from just one source – for example, hospital surgery claims without associated claims from a surgeon and an anesthetist, or reasonable-looking numbers of services allegedly delivered within a short time span in several different places. A similar idea of combining disparate data sources and looking for connections among events that seem innocuous by themselves applies in cybersecurity threat detection.

Another parallel to Medicare claims analysis is that the anomaly of interest may not be an outlier. Rather, it might be a number of events, each quite unremarkable by itself, with unusual frequency – or even a set of events with less variation than typical. In Medicare claims, for example, an event of interest could be a provider with a high volume of claims and no claims with values that trigger a range check, when some such values are often observed in general.

The absence of typical variation suggests that the provider may be submitting false claims for services that were never rendered; they know enough to fake unremarkable claims, but not to fake typical variation. Similarly, in cybersecurity monitoring, a “too regular” log of activity on the system could be an indicator of a log file being spoofed to conceal an intrusion.

These examples do not describe the actual use cases ARCYBER has pursued, but they are meant to illustrate the principles of reasoning in this field. In the view of some people especially knowledgeable in this topic area, too much specificity, even based on unclassified information, ormstoday.informs.org

could reveal too much to prospective adversar ies. ARCYBER produced a re p o r t , “ T h e R a p i d A n a l y t i c Development Framework,” [2] that describes many of the analytical tools and use cases in greater detail, along with a more detailed descr iption of the command and its activities.

Although an unclassified version is available, even that version of the report has distribution limitations and must therefore be requested from the organization.

Closely Embedding Analysts with Operators The examples briefly summarized here Dynamic computing environments support more advanced analytical tools and methods. and expounded in detail in the RADF Source: U.S. Army report illustrate the kinds of analytics, Summary based on use cases identified by operators, the analytical team has conducted. What is most important, The Army Cyber Command and Second Army’s however, is how the analysts do this. “We sit next to Rapid Analytic Development Framework, built the operator,” Maj. Faber says, “and we’re very adapon a big data and parallel computing architecture, tive. We put an extreme premium on change. We has produced striking improvements in defensive have tight iterative feedback, changing approaches, cybersecurity operations and provides a powerful getting new problems. Our goal is a simple solution example of how to integrate OR/MS into a real evolving to more complex with continual feedback. operating setting. “Placing analysts on station,” With this approach, parties stay interested because integrating them into the operational team to they stay involved.The end user is involved from in- identify and address problems quickly and adaptively, ception to delivery.” as Philip Morse famously recommended during The analytical focus is on reducing false World War II, remains the most effective approach to positives and identifying low-level events of using OR/MS professionals’ talents. ORMS potential interest. False positives are common Douglas A. Samuelson (samuelsondoug@yahoo.com) is and a serious challenge. Maj. Faber recounted, president and chief scientist of InfoLogix, Inc., a small R&D and consulting company in Annandale, Va. “Routine scans to see how many Windows 10 machines were active on a network set off REFERENCES intrusion alerts.” To detect the subtle elements that do not set off intrusion alerts but are more 1. H. R. McMaster, 1996, “Dereliction of Duty: Johnson, McNamara, the Joint Chiefs of Staff and the Lies That Led to Vietnam,” Harper. meaningful, a key analytical approach is finding 2.

U.S. Army Cyber Command and Second Army, 2016, “The Rapid Analytic Development correlations between heterogeneous data sets. “At Framework.” Point of contact: U.S. Army Cyber Command and Second Army, 8825 Beulah some point in the future,” he went on, “we hope Street, Fort Belvoir, Va. offensive and defensive data sets will talk easily, at some level of classification.”

Concentrating on operator-identified use For more on the topic of cases drove the implementation and the data cybersecurity from Doug Samuelson, architecture. The development and improvement see the September/October 2016 of of the large, integrated data platform provided Analytics magazine: the capability to ingest and process mission relevant data actively and quickly. The team at risk http://analytics-magazine.org/ Better metrics and measurement are crucial automated inclusion of network activity reports to reducing the threat and other incident data. Standardizing some ALSO INSIDE: formats greatly eased the task of comparing.

An additional financial benefit was enabling commands to do more analytical tasks in-house rather than having to rely on other agencies or commercial providers.

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Deloitte analytics leader Paul Roma on cognitive computing: How to avoid saying ‘I wish I would have’

October 2016

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ORMS Today

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The game of Go originated in China more than 2,500 years ago.

Image © Sergey Soldatov | 123rf.com

Google DeepMind’s AlphaGo Operations research’s unheralded role in the path-breaking achievement.

By Hyeong Soo Chang, Michael C. Fu, Jiaqiao Hu and Steven I. Marcus 24 | ORMS Today

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October 2016

AlphaGo’s shockingly dominant victory over the reigning world Go champion Lee Sedol in Seoul, Korea, in March 2016 signaled another great leap in the seemingly relentless advancement of machines becoming truly “intelligent” in the sense of being able to learn and outsmart humans.When IBM’s Deep Blue defeated world chess champion Garry Kasparov in 1997, it was thought at the time to have reached the ultimate pinnacle in computer game-playing abilities, since chess had been considered (at least in the Western world) to be the game requiring the most human brainpower, so the fact that a computer had finally surpassed the abilities of humankind’s best would seem to have indicated that some aspects only found in science fiction might be finally approaching reality.

However, the “primitive brute force-based” [1] Deep Blue appeared to be more of a showcase of hardware than software, as it relied more on its computational firepower rather than any intuition or actual learning in its approach to the game. On the other hand, because of the mind-boggling ormstoday.informs.org

number of possible configurations due to a much larger board size (19x19 vs. 8x8 for chess), such an approach is just not feasible in any foreseeable future for the game of Go. Thus, a paradigm shift was required, and at the heart of all successful Goplaying computer programs over the past decade has been the use of intelligent sampling (Monte Carlo simulation) rather than “intelligent” enumeration, which basically means immense storage of games and doing more clever enumeration (e.g., by pruning). However, all of these game-playing programs do have one thing in common: the concept of “learning,” using algorithms under the general umbrella of machine-learning techniques (where it appears that concepts such as branching, bounding, and pruning now have been absorbed under this catchall).

According to a Google blog posting [2]: “The game of Go originated in China more than 2,500 years ago. The rules of the game are simple: Players take turns to place black or white stones on a board, trying to capture the opponent’s stones or surround empty space to make points of territory. As simple as the rules are, Go is a game of profound complexity.

There are more possible positions in Go than there are atoms in the universe. That makes Go a googol times more complex than chess.

“T he objective of the game – as the translation of its name (weiqi in Mandarin) implies – is to have surrounded a larger total area of the board with one’s stones than the opponent by the end of the game.”

This article covers several aspects regarding AlphaGo’s success. We begin with an introduction to DeepMind and a brief description at a higher level of the main parts of the AlphaGo program – specifically the two “deep” neural networks and the technique of Monte Carlo tree search with upper confidence bounds (UCBs) that is used in all modern computer Go-playing (as well as other computer game-playing) programs. The main ideas of the latter can be found in a paper that appeared in the INFORMS journal Operations Research in 2005 [3], but is not well known in the computer science (CS) and artificial intelligence (AI) game-playing community. In describing this apparent disconnect, we will segue into comparing and contrasting the different academic cultures of the operations research (O.R.) and CS/AI communities, and raising questions as to how these two communities could possibly interact in a mutually beneficial manner to build upon the research strengths of both.

Figure 1: AlphaGo’s two-deep neural networks.

Source: Nature, 2016 [6]

Google DeepMind Google DeepMind’s web page on AlphaGo s c re a m s o u t i n a l l - c a p s : “ T H E F I R S T COMPUTER PROGRAM TO EVER BEAT A PROFESSIONAL PLAYER AT THE GAME OF GO” [4]. AlphaGo accomplished this incredible feat, assumed by AI experts to be many decades away, in October 2015, when it defeated the reigning European champion, Fan Hui, by a stunning margin of 5-0.

The creator of AlphaGo, Google DeepMind, is a London-based artificial intelligence company founded in 2010 by Demis Hassabis, Shane Legg and Mustafa Suleyman. As promoted on their web page [5]: “DeepMind was supported by some of the most iconic tech entrepreneurs and investors of the past decade, prior to being acquired by Google in early 2014 in their largest European acquisition to date. … The algorithms we build are capable of learning for themselves directly from raw experience or data, and are general in that they can perform well across a wide variety of tasks straight out of the box. Our world-class team consists of many renowned experts in their respective fields, including but not limited to deep neural networks, reinforcement learning and systems neuroscience-inspired models. ...

Our Nature paper … describes the technical details behind a new approach to computer Go that combines Monte-Carlo tree search with October 2016

Because of

a much larger board size (19x19 vs. 8x8), the game of

Go offers a

mindboggling number of possible configurations

compared to chess.

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ORMS Today

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AlphaGo

AlphaGo

deep neural networks that have been trained by supervised learning, from human expert games and by reinforcement learning from games of self-play.”

was first

trained using past human

games.

Then it

played against itself thousands of times

to further adjust the

neural network.

Core of AlphaGo: Deep Learning The following two-deep neural networks comprise AlphaGo’s core: value network – estimates the “value” (probability of winning) of a given board configuration; and policy network – provides a probability distribution over (opponent’s) actions for a given board configuration.

Each network has 12 layers and millions of connections, and as depicted in Figure 1 (from the 2016 Nature article [6]) takes as input a representation of the board configuration. The subscripts σ and ρ in the policy network probability correspond to two different networks used, based on supervised learning and reinforcement learning, respectively, whereas the subscript θ in the value network represents the parameterization of the function.

Because the number of “states” (board configurations) is way too huge to be enumerated, the probability distribution provides a “weighting” of which moves are more preferable by the opponent. If the optimal move in a given board configuration is known, the distribution becomes deterministic, but for a large proportion of the state space, the opponent’s move must be sampled using Monte Carlo simulation to generate sample paths of possible games. If simulated to the end, a win or loss could be determined, and then propagated backwards to update the value function.

Examples depicting the process using tic-tac-toe can be found in Fu [7].

AlphaGo was first trained using past human games, considering more than 30 million moves (supervised learning). Then it played against itself thousands of times to further adjust the neural network parameters (reinforcement learning) using Monte Carlo tree search with upper confidence bounds (UCBs), which directs which actions to take. In terms of Figure 1, the latter determines which move a* to select in a given board configuration s*, which leads to board configuration s, for which an opponent move a is sampled (simulated) from p(a|s), which leads to state s´,

at which point the value network could be used or the previous process could be repeated until a 26 | ORMS Today

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October 2016

satisfactory state (in terms of the value network) or the end of game is reached.

Monte Carlo Tree Search Monte Carlo tree search (MCTS) was coined by Rémi Coulom in his 2006 paper [8], where he also refers to the adaptive multi-stage sampling algorithm of Chang et al. [3] – to be described shortly – as a Monte Carlo tree search algorithm.The name Monte Carlo tree search captures the essence of the approach far better than “adaptive multi-stage sampling” and thus stuck in the AI community. The abstract of the survey article, “A Survey of Monte Carlo Tree Search Methods” (Browne et al., 2012 [9]), provides an overview of the approach: “Monte Carlo Tree Search (MCTS) is a recently proposed search method that combines the precision of tree search with the generality of random sampling. It has received considerable interest due to its spectacular success in the difficult problem of computer Go, but has also proved beneficial in a range of other domains.”

Browne et al. go on to provide the following summary description of MCTS: “The basic MCTS process is conceptually very simple. ... A tree is built in an incremental and asymmetric manner. For each iteration of the algorithm, a tree policy is used to find the most urgent node of the current tree. The tree policy attempts to balance considerations of exploration (look in areas that have not been well sampled yet) and exploitation (look in areas which appear to be promising). A simulation is then run from the selected node and the search tree updated according to the result. This involves the addition of a child node corresponding to the action taken from the selected node, and an update of the statistics of its ancestors. Moves are made during this simulation according to some default policy, which in the simplest case is to make uniform random moves. A great benefit of MCTS is that the values of intermediate states do not have to be evaluated, as for depth-limited minimax search, which greatly reduces the amount of domain knowledge required. Only the value of the terminal state at the end of each simulation is required.”

In practice, most implementations of Monte Carlo tree search, including all of those in the best Go-playing computer programs, use an algorithm called UCT (upper confidence bound 1 applied to trees) introduced in Kocsis and Szepesvári (2006, [10]), based on the UCB1 formula of Auer et al.

(2002, [11]) and the provably convergent algorithm ormstoday.informs.org

first applied to multi-stage decision-making models (specifically, Markov decision processes) by Chang et al. (2005, [3]), a paper published in Operations Research.

Connection to Operations Research The Operations Research paper (Chang et al.

2005) cited above was first submitted in May 2002 and presented just pr ior to that at the Cornell ORIE Colloquium on April 30. The adaptive multi-stage sampling (AMS) algorithm of Chang et al. chooses to sample the action that maximizes the upper confidence bound (UCB).

As described in Chang et al., AMS “approximates the optimal value to break the well-known cur se of dimensionality in solving finite hor izon Markov decision processes (MDPs).

The algorithm is aimed at solving MDPs with large state spaces and relatively smaller action spaces. The approximate value computed by the algorithm not only converges to the true optimal value, but it does so in an ‘efficient’ way.

The algorithm adaptively chooses which action to sample as the sampling process proceeds, and the estimate produced by the algorithm is asymptotically unbiased.”

Kocsis and Szepesvári (2006) cited the work as follows: “Recently, Chang et al. also considered the problem of selective sampling in finite horizon undiscounted MDPs. … At each node they sample (recursively) a sufficient number of samples to compute a good approximation of the value of the node. The subroutine returns with an approximate evaluation of the value of the node. … Similar to our proposal, they suggest to propagate the average values upwards in the tree and sampling is controlled by upperconfidence bounds.”

Coulom (2006) writes: “Our approach is similar to the algorithm of Chang, Fu and Marcus [sic] … In order to avoid the dangers of completely pruning a move, it is possible to design schemes for the allocation of simulations that reduce the probability of exploring a bad move, without ever letting this probability go to zero. Ideas for this kind of algorithm can be found in …n-armed bandit problems, … (which) are the basis for the Monte-Carlo tree search algorithm of Chang, Fu and Marcus [sic].”

CAREER CENTER The INFORMS Career Center offers employers expanded opportunities to connect to qualified O.R. and analytics professionals, as well as a complete line of services to be used alone or in conjunction with the Career Fair at the 2016 Annual Meeting. Both give applicants and employers a convenient venue to connect. The Career Center is free to INFORMS members.

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Learn more about the 2016 INFORMS Annual Meeting Career Fair, http://meetings.informs.org/nashville2016/career-fair.html October 2016

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ORMS Today

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AlphaGo

AlphaGo represents a formidable

AI achievement stemming from

several research streams, for which the

OR/MS community has played

a role.

28 | ORMS Today

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In other words, as mentioned earlier, Coulom himself refers to the AMS algorithm as a Monte Carlo tree search. The AMS algorithm was the first work to explore the idea of UCB-based exploration and exploitation in constructing sampled/simulated (Monte Carlo) trees and is clearly the main seed for UCT. A Tale of Two Cultures in Academia As described, a core element in AlphaGo is MCTS with UCB, which came from the 2005 Operations Research journal paper, but the two 2006 AI conference papers (which as noted already did cite the 2005 paper) receive all the publicity (and citations; well over 2,000 in Google Scholar versus 75 for the Operations Research paper as of Sept.11, 2016), because much of the AI community is unaware of O.R. advances.

Much of the CS community publishes primarily in conference proceedings, whereas, in general, the OR/MS community doesn’t value conference proceedings papers for promotion and tenure (especially in business schools, where they may even be viewed negatively), and journal papers take years to get published. Moreover, once a work is published in a conference, it becomes more difficult to publish it in a journal, which is probably the main reason the main INFORMS conferences have no proceedings.

In contrast, the CS (and AI community within it) culture values conference proceedings the most, which puts the research agenda in a very different mode, always seeking to meet the next deadline (e.g., NIPS, AAAI, ICML).There’s nothing like a deadline for increasing productivity, and CS/AI conference papers generally get much higher citation counts than our journal papers; however, this modus operandi is not without its costs. For example, due to the tight reviewing deadlines, mathematical proofs are rarely if ever closely checked, and many unsubstantiated claims end up being published. Many CS communities, such as the AI community, have tighter links with industry, at least the research-oriented groups within such giants as Google, Microsoft, Facebook and Yahoo, and this is evidenced by the active participation in the previously mentioned conferences.

It should be noted that many IEEE societies (of which both the CS/AI and OR/MS communities participate to some degree) have a hybrid model.

For example, the IEEE Conference on Decision and Control, for which INFORMS is one of the sponsoring organizations, has a system whereby work submitted for the conference and published in the proceedings can also be considered (in lengthier form) for a corresponding journal, the IEEE Transactions on Automatic Control. Perhaps this is a model that could be considered by some INFORMS-sponsored conferences.

October 2016

One attempt to bridge the gap between the O.R. and AI communities was a National Science Foundation (NSF)-sponsored workshop entitled, “A Conversation Between Computer Science and Operations Research on Stochastic Optimization.”

As described in Fu and Barton (2012, p.36, [12]), “This workshop is co-funded and co-sponsored by the Robust Intelligence (the new name for artificial intelligence (AI) at NSF) Program in CISE, and is motivated by a mutual feeling by the Robust Intelligence Program Director Sven Koenig and the OR Program director that the AI and OR communities carry out research on essentially the same topics oftentimes unaware of the contributions from the other community due to differences in terminology and notation. Such differences prevent research ideas from being understood and shared, so the workshop aims to break down such barriers, focusing on one broad area of interest to both communities, encompassing well-known topics such as AI planning and Markov decision processes.” The workshop, led

by Warren Powell (Princeton) and Satinder Singh (Michigan), was held May 31-June 1, 2012 on the campus of Rutgers University. It was there that one of us first heard about the UCB Monte Carlo tree search algorithm, which sounded so similar to the AMS algorithm that an O.R. participant (not one of us) noted it.

At the time, a co-author of the paper that is credited with “inventing” UCT turned to one of us to say, “We cited your paper.” Sure enough, this was confirmed, and it was at that time that it was first revealed to the O.R. community that this algorithm was being used successfully in Go-playing computer programs. Most of the participants likely do not even remember this seemingly trivial exchange, as confirmed when one of us checked with the O.R. participant who had noted the algorithmic resemblance at the time. To find out more about the workshop, the web page for the workshop is still available at http://castlelab.princeton.edu/nsfcsor.html.

Conclusion AlphaGo represents a formidable AI achievement stemming from several research streams, for which the OR/MS community has played a role such as neural networks, learning algorithms, Monte Carlo tree search and multi-armed bandit models. What makes the work perhaps more impressive, at least on the surface, is that unlike IBM’s DeepBlue and Watson, which were basically tuned to a single application – playing chess or playing Jeopardy, the machinery behind AlphaGo can be easily adapted to other games and applications. In other words, the general neural network/Monte Carlo tree search architecture can be viewed as a very general-purpose ormstoday.informs.org

tool for games or sequential decision-making under uncertainty, much like regression is used for the social sciences. However, the devil’s in the details, in this case the selection of the appropriate “features” in the neural networks, so that there is still as much art as science at this point.

Finally, a broader theme that we touched upon is raising conscientiousness in the OR/MS community as to how better to promulgate our research to other communities such as CS/AI. Clearly, INFORMS is aware of this general challenge, as evidenced by its seizing the initiative in claiming a well-deserved piece of the analytics pie. ORMS Hyeong Soo Chang (hschang@sogang.ac.kr) is a professor in the Department of Computer Science and Engineering at Sogang University in Seoul, South Korea.

Michael C. Fu (mfu@umd.edu) is the Ralph J. Tyser Professor of Management Science in the Robert H. Smith School of Business (with a joint appointment in the Institute for Systems Research, A. James Clark School of Engineering) at the University of Maryland, College Park. Jiaqiao Hu (jqhu@ams.sunysb.edu) is an associate professor in the Applied Mathematics and Statistics Department at Stony Brook University. Steven I. Marcus (marcus@umd.edu) is a professor in the Department of Electrical Engineering (with a joint appointment in the Institute for Systems Research) in the A. James Clark School of Engineering at the University of Maryland, College Park.

REFERENCES 1. Wikipedia, “Deep Blue versus Garry Kasparov,” accessed April 28, 2016.

2. “AlphaGo: Using Machine Learning to Master the Ancient Game of Go,” Jan. 27, 2016; https:// googleblog.blogspot.nl/2016/01/alphago-machine-learning-game-go.html.

3. Chang, H. S., Fu, M. C., Hu, J. and Marcus, S, I., 2005, “An Adaptive Sampling Algorithm for Solving Markov Decision Processes,” Operations Research, Vol. 53, pp. 126-139.

4. https://deepmind.com/alpha-go.html, accessed May 11, 2016.

5. deepmind.com, accessed May 11, 2016.

6. Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., Dieleman, S., Grewe, D., Nham, J., Kalchbrenner, N., Sutskever, I., Lillicrap, T., Leach, M., Kavukcuoglu, K., Graepel, T., and Hassabis, D., 2016, “Mastering the game of Go with deep neural networks and tree search,” Nature, Vol. 529 (Jan. 28), pp. 484-503.

7. Fu, M.C., 2016, “AlphaGo and Monte Carlo Tree Search: The Simulation Optimization Perspective,” Proceedings of the 2016 Winter Simulation Conference, to appear (downloadable at http://informs-sim.org after mid-December).

8. Coulom, R., 2006, “Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search,” Computers and Games, 5th International Conference, CG 2006, Turin, Italy, May 29-31.

9. Browne, C., Powley, E., Whitehouse, D., Lucas, S., Cowling, P.I., Rohlfshagen, P., Tavener, S., Perez, D., Samothrakis, S., and Colton. S., 2012, “A Survey of Monte Carlo Tree Search Methods,” IEEE Transactions on Computational Intelligence and AI in Games, Vol. 4, No. 1, pp.1-49.

10. Kocsis, L. and Szepesvári, C., 2006, “Bandit based Monte-Carlo planning,” Proceedings of the 17th European Conference on Machine Learning, Berlin, Germany: Springer, 282-293.

11. Auer, P., Cesa-Bianchi, N., and Fisher, P., 2002, “Finite-time Analysis of the Multiarmed Bandit Problem,” Machine Learning, Vol. 47, pp. 235-256.

12. Fu, M.C. and Barton, R.R., 2012, “O.R. and the National Science Foundation (part 2),” OR/MS Today, June, pp. 34-38.

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Are you the best in OR/MS/Analytics education?

The UPS George D. Smith Prize is created in the spirit of strengthening ties between industry and the schools of higher education that graduate young practitioners of operations research. INFORMS, with the help of CPMS, will award the prize for the effective and innovative preparation of students to be good practitioners of operations research, management science, or analytics to an academic department or program.

The prize will include a trophy and $10,000 award. The UPS George D. Smith Prize will be announced at the 2017 Edelman Gala at the INFORMS Conference on Business Analytics and Operations Research, in Las Vegas, NV.

For more information, questions can be sent to Robin Lougee, 2017 Smith Prize Chair at rlougee@us.ibm.com.

www.informs.org/smithprize

2016 UPS Smith Prize Winners Carnegie Mellon University, H. John Heinz III College, School of Information Systems and Management, and School of Public Policy and Management

ing ties hen t g en str

ups george d smith prize October 2016

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ORMS Today

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Election analytics Student-driven STEM learning lab’s election forecasting website predicts presidency and Senate races.

By Wenda Zhang, Jason J. Sauppe and Sheldon H. Jacobson

Numerous political pundits believe that the 2016 presidential election will be unlike any other election in the past. It is not because of the prevalence of social media or the wall-to-wall coverage from cable news organizations, both of which have already played significant roles in the past several elections. Rather, the 2016 election is unique in the amount of contention generated by the two major party candidates even before the general election kicked off. The word “unprecedented” has been employed many times to describe how repeatedly surprised people have been over the course of last year; and no matter what the outcome will be come Nov. 8, this election almost certainly deserves its own chapter in the history books.

The “unprecedented” nature of this election means that people are even more curious about election forecasts. National polling usually offers only limited insight into the odds of a candidate winning the White House, but state-by-state polling can be used to create more powerful predictions using advanced analytics. The Election Analytics (electionanalytics.cs.illinois.edu) team, housed in the Department of Computer Science at University of Illinois, has a wealth of past experience in doing just that. In 2008, the team first introduced their election forecasting website. The model behind their forecasts makes use of all state-level polling data to compute probabilities of each candidate winning each state; these probabilities are then used to determine how many electoral votes each candidate will receive. In 2008, their model correctly predicted the outcomes for 50 out of 51 states (with the District of Columbia included).

The 2016 presidential race between Hillary Clinton and Donald Trump is unlike any other election.

Source: Election Analytics

30 | ORMS Today

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October 2016

ormstoday.informs.org

In 2012, the team launched a new and improved website to predict national elections, focusing on the presidency and the Senate. More components, such as a trend chart that showed predictions over time, were added to the website in order to present information regarding the races and forecasts more clearly. On Election Day, the model was able to correctly predict the outcomes for 50 out of 51 states (District of Columbia included) for the presidential race, as well as the outcomes for 31 out of 33 Senate races.

2014 saw another big update for the website, with a complete redesign, incorporating modern web design concepts to make it streamlined and responsive, with all past prediction data readily available for viewing. For the Senate races that year, the model was able to correctly predict 35 of 36 races.

In anticipation of the 2016 election cycle, the Election Analytics team has added several new features for the website. One significant addition is forecast customization, which allows users to modify the existing forecasts in various ways.

These custom forecasts still rely on the same mathematical model for constructing candidates’ probabilities of winning, but allow a user to experiment with some additional assumptions regarding the polling data itself, providing a means to conduct sensitivity analysis based on such data.

First, the customization options allow a user to exclude polling data from certain sources. By default, each forecast is constructed using all available polling data. This includes polls from sources that a user may consider to be biased; by excluding these sources, the user can get a forecast that they consider to be more accurate.

Another customization option allows the user to control the impact of undecided voters on the election. By default, the undecided voters are assigned evenly to the major party candidates; however, users can now shift these percentages toward either the Democrat or the Republican candidates, if they believe that these undecided voters will break one way or the other on Election Day. This is also the year that independent candidates are positioned to have noticeable impacts on the final results. Both Libertarian Party candidate Gary Johnson and Green Party candidate Jill Stein have been polling above nor mal (around 9 percent for Johnson and 3 percent for Stein, as of mid-September) in national polling averages, indicating that their effect on the election cannot be ignored. This

is particularly true for Johnson, who will be appearing on the ballot in all 50 states; he also has the potential to reach 15 percent in polls, which would grant him a spot in the presidential debate.

Should he succeed in doing that, he may even (albeit unlikely) be able to win electoral votes.

[Editor’s note: Johnson did not qualify for the first debate.]

The more likely scenario is that he will alter the results of some states, and hence, possibly the final result for who gains the White House. Given this, another customization option allows for the users to construct forecasts using polling data that either includes or excludes Johnson and Stein.

Hence the word “unprecedented” appears justified. At the time of this wr iting (midSeptember), the Election Analytics forecast gives Clinton 304 expected electoral votes, with a probability of 0.53 of winning at least 300 electoral votes. By adding a very strong Republican lean to the undecided voters, Clinton’s expected electoral votes drop to 286, with a probability of 0.15 of winning at least 300 electoral votes. Clearly, Clinton (at the time of this writing) has the lead, though this lead has been eroding since mid-August. Also at the time of this writing, the Election Analytics forecast gives the Republicans a probability of 0.87 of retaining control of the Senate. Any number of unpredictable events, domestic or international, could resulting in these leads shr inking or widening.

All these factors suggest that it will be a challenging election to predict. At the same time, it is also a great opportunity for the Election Analytics team to test operations research and advanced analytic methodologies on a real-world application. Election Analytics is a studentdriven STEM learning lab, providing a unique opportunity for students to transition their classroom knowledge into a practical tool that draws widespread national interest. The goal is to demonstrate, once again, that through careful data analysis and analytics, even the future is not completely obscured from the eyes of the population. ORMS

It will be

a challenging election to predict.

It is also

a great opportunity for the

Election Analytics team to

test O.R. on a

real-world application.

Wenda Zhang is a graduate student at the University of Illinois at Urbana-Champaign. Jason J. Sauppe is an assistant professor at the University of Wisconsin-La Crosse. Sheldon H. Jacobson is a professor at the University of Illinois at Urbana-Champaign. Their web site (electionanalytics.cs.illinois.edu) provides daily forecasts for the presidential and Senate races. The University of Illinois at Urbana-Champaign students involved in the design, execution and updating of Election Analytics during the 2016 election cycle are Siddhartha Duri, Rishi Jain, Niraj Pant and Victor Jarosiewicz.

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Present and future of analytics education Panel discussion: Directors from four of the nation’s top university analytics programs share their insights and expertise.

According to the IBM Tech Trends Report in 2011, analytics has been identified as one of the four major technology trends in the 2010s.

However, as predicted by McKinsey Global Institute, by 2018, the United States alone will face a shortage of more than 140,000 people with deep analytics skills, as well as a shortfall of 1.5 million managers without knowledge on how to leverage the big data techniques to make effective decisions. Consequently, many universities have been establishing master’s degree programs or concentrations in data analytics to fill the resource requirements in the current job market. While some efforts have been made in the past, there is still a lack of formal discussions and communications among these analytics programs, which poses a significant challenge for students and industries to understand the unique strengths and characteristics of different analytics programs.

This article is intended to provide some insights regarding this topic, which

By Kaibo Liu, Diego Klabjan, are digested from a featured panel discussion on “Present and Future of Analytics David Shmoys and Joel Sokol Programs” at the Industrial and Systems Engineering Research Conference (ISERC) that was held on May 30-June 2, 2015, in Nashville,Tenn. In particular, four panelists joined this session, including professors Joel Sokol (Georgia Institute of Technology), Diego Klabjan (Northwestern University), David Shmoys (Cornell University) and Michael Rappa (North Carolina State University), who are all the current program directors from their respective analytics programs.

Professor Kaibo Liu (University of Wisconsin-Madison) chaired the session.

The panelists discussed a wide range of topics, including the effective ways of teaching analytics courses, the balanced designs of course curriculum from multidisciplines, the unique strengths and resources of different analytics programs, the expected skills for students after the analytics training program, the experience and challenges of the past and current analytics program, and future strategies for better education, improvement and sustainability of the analytics program.The goal of this article is to push the frontiers and increase the Many universities have established programs or concentrations in data analytics to meet the job exposures of the analytics programs market demand. by establishing an interactive forum Image © dotshock | 123rf.com for better discussion and sharing of 32 | ORMS Today

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information among the analytics community. With such efforts, we intend to provide: 1) insights for students to decide which analytics programs to apply for, 2) information and guidelines for industrial companies to better understand the expected skills of students after the analytics program trainings, and 3) useful experience and successful stories for other universities who are also interested in establishing an analytics program in the future.

Analytics Program Overview Based on the information provided from the four panelists, Table 1 shows a detailed summary of the similarities and differences among the four analytics programs featured in the panel discussion. In addition, some unique features of each analytics program are summarized as follows: Cornell University offers a concentration in data analytics as part of the Master of Engineering degree in operations research and information engineering.The data analytics concentration is designed in the way to complement the current strong operation research core curriculum. The data analytics curriculum includes many OR courses, and also two statistical data analysis courses, one data technology course, and one marketing and pricing strategy course.

Georgia Tech offers a Master of Science degree in analytics. The curriculum of this program is an integration of the strengths from three colleges: College of Computing, College of Engineering and Scheller College of Business. The program allows students to build skills based on three tracks of specifications, including analytical tools, business analytics and computational data analytics. In addition, it also provides flexible course selections based on students’ interests (half of courses are elective).

Northwestern University offers a Master of Science degree in analytics. The program provides a highly applied and comprehensive curriculum that integrates three disciplines: data science, information technology and business. The courses are all newly designed and taught by faculty from different fields and departments of the university. This program aims to equip students with the essential techniques of extracting and communicating the value of data. During the program trainings, the students are exposed to a wide range of software tools, including R, Python, D3, SAS,Tableau and Hadoop (MapReduce, Spark, Pig and HBase).

North Carolina State University offers a Master of Science program in analytics that is run by the Institute for Advanced Analytics, a university-wide collaboration that is organized independently of college and department units. It is widely recognized as the first Master of Science in analytics program in the country. One unique feature of the program is

that there is no conventional concept of courses; instead, faculty members directly determine the appropriate lectures and materials that they think useful for students. Also, the program does not intend to grade and rank students; instead, it emphasizes a balance of mixed skills and trainings, including technical, tools, teamwork, communication and problem-solving with an integrated multidisciplinary curriculum in math, statistics and computer science.

Diego Klabjan

Key Tools and Software for Analytics Students While there are many choices and differences in the tool/ software offered by school anMichael Rappa alytics programs, the panelists indicated that the ability to learn a new tool is more important than learning a particular tool/software, as software selection will continuously change and evolve over time.

Upon graduation from an analytics program, the students are expected to acquire some popular tools, such as R, to build a “toolbox” that they can David Shmoys consistently build upon. However, students need to realize that the existing “toolbox” is always going to grow in the future, and new knowledge has to be timely updated based on their working experience and requirements to ensure their success beyond college.

The panelists also suggested that it is more important to provide a wide overview of Joel Sokol a potential toolbox in the beginning of the program and then guide students to actively teach themselves about the details of each programming language. In this way, students can not only achieve a basic understanding of the strengths and uniqueness of different tools and software, but also acquire the skills of actively learning a new tool when it becomes important. Furthermore, the panelists also highlighted the essentials of teamwork training in the analytics program, which helps students to better October 2016

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Analytics Education communicate in a future working environment with others who may use different programming languages.

Design Models of Analytics Programs The panelists provided insights and shared useful information regarding the design models of their respective analytics programs, which should be helpful to those who are interested in establishing new data analytics programs at their universities in the future.

Considering that analytics is an interdisciplinary

field, the panelists suggested that it could be more effective to consider the program as a “standalone” unit rather than an “additional” element in an existing programs, such as statistics, computer science, business or industrial engineering. In this way, faculty from different departments can contribute to the analytics program with their unique expertise via course instruction and student advice.

The panelists also commented that it is more important to provide a breadth of curriculum to students

CORNELL

GEORGIA TECH

NC STATE

NORTHWESTERN

Degree granted:

M.Eng. in ORIE with a Data Analytics concentration

M.S. in Analytics

M.S. in Analytics

M.S. in Analytics

Year started:

2004

2014

2007

2012

Location:

Ithaca, NY

Atlanta, GA

Raleigh, NC

Evanston, IL

Number of faculty:

25

58

NA

12

Program format:

Full time

Full or Part time

Full time

Full time

Time duration in months:

9 or 14

12

10

15

Curriculum:

Core & Electives

Core & Electives

Fully Defined

Fully Defined

Enrollment per year:

3~6

about 45

about 115

<=40

% Female:

NA

38%

41%

45%

% International:

NA

42%

15%

40%

Acceptance rate:

NA

18%

13%

NA

Applicant undergraduate GPA requirements:

NA

NA

NA

>=3.0

Applicant TOEFL requirements:

Total >=100

Total >=100

No

Total >=95

Application fee

$95

$75 with $2,000 matriculation fee

NA

$75

Only GRE accepted

GRE or GMAT accepted

No

GRE or GMAT accepted

NA

60%

>50%

56%

Number of graduates:

<30

45

419

61

Sponsored team project:

Yes

Yes

Yes

Yes

Internship requirement:

No

Yes

No

Yes

Average starting salary:

NA

$95,000

$96,400

$103,250

100%

100%

100%

100%

$48,900

$39,000/ $52,400

$25,000/ $42,800

$64,800

David Shmoys

Joel Sokol

Michael Rappa

Diego Klabjan

Applicant GRE/GMAT requirements: Matriculated students with prior work experience:

Latest job placement by 90-days after graduation: Total tuition cost for in state/out of state students: Program directors:

(ORIE Chair) Kathryn Caggiano (MEng Director)

Table 1.

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rather than focusing on introducing in-depth knowledge in a particular topic in the analytics program. Students are expected to have enough prior knowledge in different fields and to have the ability to quickly learn new knowledge in their daily life going forward.

Should Analytics Programs Provide Online or a Residential Degree?

While there have been many discussions about offering online degrees, the panelists agreed that the residential degree for their analytics program is essential, at least for now. For example, according to panelist Joel Sokol, “One of the key aspects of Georgia Tech’s program is what goes on outside of the classroom. We offer special training sessions in leadership, ethics, creativity, communication, privacy, etc., as well as a required applied analytics practicum.

Those are hard to offer in an online format. Some of the other aspects of the curriculum are also part ‘art’ and part science, such as data wrangling, building good modeling intuition, learning how to get projects implemented, etc., and those also might be hard to translate to an online format.”

However, the panelists also acknowledged the advantages of the online courses, such as reaching broad audience, and thus believe that certainly parts of the curriculum could be offered online in the future. These online courses will serve as a complementary role to the residential program.

Analytics or Data Science Degree?

The panelists agreed that most of the top data science programs focus mainly on the computing and statistics pieces (some include a little O.R.), but they do not cover the business side. This is a unique difference between Master of Science programs in analytics and data science. For example, Georgia Tech’s master’s degree in analytics is interdisciplinary between engineering (statistics and operations research), computing and business, and the inclusion of the business piece is a significant differentiator for the program. The students are more likely to come out with a broader business understanding of the use and application of the technical side, and are therefore hopefully more likely to advance to significant leadership positions within organizations in the long run.

Another important difference is that an analytics program is more about understanding the tools available to provide better decision-making support and using them to guide data-driven decisionmaking. While analytics has certain overlap with data science, the focus on the application of big data, rather than simply the manipulation and maintenance of the data itself, is a basic distinction between the two disciplines.

Collaborations with Healthcare Informatics Analytics is a very broad field. There are many healthcare nursing and physician informatics programs currently available in the United States.

Those programs are mainly certification-based, and the curriculum is often not an analytics- or statistics-driven program. Thus, many clinical experts are willing to get more intensive training in the analytics programs. One challenging question is how to better collaborate with clinical experts and ensure the analytics program is suitable to those groups of people with a different skill or background.

The panelists suggested two solutions: One is to provide more practical/clinical-related elective courses in the curriculum, and the other is to establish more collaborations with clinical providers through healthcarerelated analytics projects. For example, David Shmoys from Cornell University mentioned that the students in his program commonly conduct two analytics projects a year with providers such as the Cayuga Medical Center in Ithaca, N.Y., the Hospital for Special Surgery in New York City, and the New York Presbyterian Hospital/ Weill Cornell Medical College. Diego Klabjan from Northwestern University mentioned that his analytics program indeed has bioinformatics students.

While these students are required to take technical/IT coursework, at the same time they are also flexible to choose elective courses based on their interests, e.g., genomics instead of marketing. Sokol added that his program provides many healthcare analytics electives to students and applied practicum projects in healthcare analytics to accommodate the ever-growing needs in this field. In addition, one of the program’s industry advisory board members is a director for a healthcare provider. ORMS

Most of the

top data science programs focus on the

computing and statistics pieces, but they

do not cover the

business side.

Kaibo Liu is an assistant professor at the department of Industrial and Systems Engineering, University of Wisconsin-Madison. His research interests are system informatics and data analytics with an emphasis on data fusion for process modeling, monitoring, diagnosis and prognostics.

Diego Klabjan is a professor at Northwestern University, Department of Industrial Engineering and Management Sciences, and a founding director of the Master of Science in Analytics program at Northwestern. He is also a founder of Opex Analytics LLC. David Shmoys is the Laibe/Acheson Professor and director of the School of Operations Research and Information Engineering at Cornell University. He is a Fellow of INFORMS, SIAM and ACM, and a recipient of the Lanchester Prize from INFORMS. Joel Sokol is the Fouts Family Associate Professor in Georgia Tech’s H. Milton Stewart School of Industrial and Systems Engineering. He is founding director of Georgia Tech’s interdisciplinary Master of Science in analytics degree program, served two terms as INFORMS vice president of Education, and is the recipient of Georgia Tech’s highest awards for teaching and student impact.

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D E C I S I O N A N A LY S I S SOFTWARE SURVEY

Past, present and future of dynamic software emphasizes continuous improvement of vital O.R. tool.

Image © Sergey Nivens | 123rf.com

By Samantha Oleson

Decision analysis Fifty years have elapsed since the founding of the field of decision analysis by Howard Raiffa [1] and Ron Howard [2]. 2016 is not only a milestone year due to the anniversary but also because it marks the passing of one of the founders, Howard Raiffa. Such significant events make this year a time for reflection. Seasoned decision analysts can celebrate their contributions to the advancement of the field, while young O.R. professionals should take this time to imagine how their current and future contributions will shape the next 50 years of the field.

In a 1988 paper on the state of the field of decision analysis, Ron Howard wrote, “the accomplishments and promise of the field are impressive” and improvements to the “procedures for formulating, eliciting, evaluating, and appraising the decision problem” occur every day. He further explained that despite the improvements, decision analysis has “not [yet] become commonplace even in very important decisions.” However, he believed that as of 1988, “decision analysis [was] poised for a breakthrough in its usefulness to human beings” that would be achieved in part 36 | ORMS Today

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October 2016

using “[computer-based] intelligent decision systems … to provide the benefits of decision analysis on a broader scale than ever before” [3].

Now, 30 years after the 1988 article, we can agree with Ron Howard that decision analysis has accomplished much since its founding. He was also correct in predicting that technology would play an ever-increasing role in the decision analysis field and that more contributions are still to come. Although a very difficult task, it is possible to identify several of these contr ibutions as defining ormstoday.informs.org

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achievements for the first 50 years of the field of decision analysis. These include: • establishment of university programs and classes focused on decision analysis, • adoption of decision analysis techniques and principles in everyday business practices, and • integration of computing methods and tools.

During a 2011 meeting of members of the Decision Analysis Society of INFORMS, leading decision analysts contemplated the future of the field. Their conclusions mirrored Ron Howard’s 1988 predictions in that they identified two factors that would characterize the future of decision analysis: 1) collaboration with other fields of study and, 2) advances in technology [4]. Eric Horvitz, managing director of Microsoft Research’s Redmond lab, cited the role of “decision-theoretic ideas” in the development of artificial intelligence as a prime example of the significant contributions the field of decision analysis has made in the past and will make in the future. He went on to conclude that, “There is great opportunity for more interaction between the communities … to date the surface has only been scratched” [5]. Many attendees agreed that future work in decision analysis will not only prove the practice to be indispensable to the field of computer science but also to “such realms as healthcare, climate change, energy and national security” [4].

Now, standing on the threshold of the next 50 years of decision analysis we must ask ourselves, “How can we make the visions of our founders and current leaders a reality?” Helping to tackle the present and future challenges of inter-field collaboration and integration of advanced computing methods are the vendors that develop the decision analysis tools used by the O.R. community today.

This year’s software survey seeks to catalog these tools and the features they offer to practitioners.The goal is to help readers to use these tools to continue to further spread the use of the field of decision analysis.

The Survey This 2016 Software Survey assists readers in evaluating the featured decision analysis software products in three categories: 1) decision analysis applications, 2) usability features, and 3) licensing and training options. Decision analysis applications examine the analytical uses of the tools, as well as features offered for elicitation of decision problem components. Usability features highlight available features that make the tools user-friendly, compatible with other software and operating systems, and useful in communicating results. Since the 2014 survey, we added questions to this category to more closely examine this area.

The final category, licensing and training options, asks for the options provided by the vendors for purchasing and achieving proficiency with the products.

The approach and collection method of this year’s survey did not differ from previous years.Vendor representatives com-

threshold of the next 50 years of decision analysis, we must ask ourselves, “How can we make the visions of our founders and current leaders a reality?”

Standing on the

pleted an online questionnaire consisting of approximately 60 questions. Vendors who completed the 2016 survey include those who participated in previous surveys or who recently came to the attention of OR/MS Today staff.Vendors who have not yet participated in the 2016 decision analysis software survey may submit details of their product to the online version of the survey by filling out the questionnaire available at http:// lionhrtpub.com/ancill/dassurvey.shtml.

Results of the 2016 software survey are presented, verbatim, as part of this article. OR/MS Today does not intend for the results to imply quality or cost effectiveness, but rather to provide a detailed catalogue of possible decision analysis tools available on the market today.

2016 Results The 2016 software survey features 29 software packages from 19 vendors (see page 40). Companies from the United States, United Kingdom, Belgium, Finland, Canada, New Zealand and Sweden are represented in this year’s survey.

These companies provide their decision analysis packages to a variety of industries, with the healthcare, defense, energy and mining industries reported most frequently. While OR/MS Today did not receive responses from all of the vendors who participated in 2014, they did receive first time responses for eight software packages. Three of these new responses were for products just launched in 2016. The following sections provide a brief overview of the results of each of the three survey categories: Decision analysis applications: Vendors most frequently reported that their products could be applied to decision problems involving multiple competing objectives and uncertainty. A smaller number of products offered features for risk tolerance, sequential decision-making and evidential reasoning. Other features reported by vendors that were not specifically queried in the survey included Monte Carlo simulation, trade-off analysis, group value elicitation, game theory and decision framing. Vendors reported that more than 75 percent of tools could be used for elicitation of value functions/scores and model structure. Decision analysis features less frequently offered by the products included elicitation of probabilities, criteria/attribute weighting and the value of imperfect information.

Usability features: Not surprisingly, most of the products provide their users with common usability features such as the ability to import and export components, document Software Survey, continued on 38

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D E C I S I O N A N A LY S I S Software Survey, continued from 37

model structure and/or judgments with text and display analytical results graphically. Additionally, vendor responses show that nearly 90 percent of the decision analysis tools featured are capable of interfacing with other software, and approximately 50 percent have XML and/or API features.

Thirteen of the 29 packages are offered as web implementations. Of the 13, three are veteran products providing web-based access as a new feature and two are software just released in 2016.

Licensing and training: Most of the responding vendors reported that their products can be purchased for either educational or commercial use. Nearly 35 percent of the products offer an enhanced or high-performance version of the tool. Many of the products are offered free or at a discounted rate for educational use, while the price of enhanced or high-performance and commercial versions of the tools vary depending on the licensing plan. All but five vendors reported that training programs are available to users either through the vendor itself or through a third party. Fifteen of these vendors offer web-based training, two of which are returning products that did not previously offer web-based training.

Current and Future Trends Although it is difficult to conduct detailed statistical analysis of the data set due to the small sample size and changes in the list of participants year to year, it is possible to identify several trends: Collaboration: With each year of the survey, vendors report the expanded capability of their tools to provide collaborative decision analysis solutions. Today’s tools not only feature group collaboration capabilities such as group elicitation, and simultaneous data input and viewing, but also features that lay the groundwork for inter-field collaboration. Compatibility with other software and/or XML and API features make decision analysis techniques more readily accessible to other industries and fields of study. The forward-thinking development and continuous improvement of decision analysis tools will help users to realize the collaborative future envisioned by both Ron Howard in 1988 and by the 2011 workshop attendees.

Web implementation and cloud computing: Continuing the trend from 2014, a growing number of vendors offer web-based implementations of their products and webbased training and support. In fact, two of the respondents this year specifically stated that their packages are cloudbased products. With the increasing use of “the cloud,” it is likely that products will be offered in this environment more and more frequently.

Visualization: Improvements in computing technology have made it easier than ever to interact with the decision space through the data and values that define it. With this in mind, OR/MS Today introduced new questions to the 2016 survey that examine the communication and visualization features offered by the various products. Vendors reported 38 | ORMS Today

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October 2016

Leading voices in decision analysis say there is room to expand through collaboration with other fields and through the application of advanced computing methods. that about 75 percent of tools have customizable visualization features that allow users to perform actions such as drag-and-drop chart development and manipulation, or color and formatting selection. As for decision space exploration using interactive graphics, displays, or interfaces, about 70 percent of the products surveyed had this capability. While visualization and communication may not be the primary focus of tools used for decision analysis, the number of vendors reporting significant updates to the reporting, graphing and formatting features of their tools suggest they understand that there will be a strong need for these features in years to come.

Final Thoughts In 2016, we not only celebrate the accomplishments of Ron Howard and Howard Raiffa but also the accomplishments of the many decision analysts who used their founding concepts to expand the field even further. As a young decision analyst, it is difficult to imagine that the founders left much room for further innovation. How are we supposed to continue to advance the field over the next 50 years?

Leading voices in decision analysis say there is room to expand through collaboration with other fields and through the application of advanced computing methods, so we must focus our energies in these areas. There is much uncertainty associated with the roles we will play in the future of decision analysis, however, this is the type of problem we have been well trained to overcome. It’s time to leap into the next 50 years. ORMS Samantha Oleson (soleson@innovativedecisions.com) is an analyst with Innovative Decisions, Inc., an analytics consulting firm specializing in decision and risk analysis, operations research and systems engineering.

REFERENCES 1. Gavel, Doug, 2016, “Harvard Remembers Howard Raiffa,” Harvard Gazette, News.harvard.edu, July 11, 2016. Web access: Sept. 7, 2016.

2. Stanford University, 2016, “Profiles: Ronald Howard,” accessed Sept. 9, 2016.

3. Howard, Ronald A., 1988, “Decision analysis: practice and promise,” Management Science, Vol. 34, No. 6, pp. 679-695.

4. Abbas, Ali, 2012, “Decision analysis: past, present and future,” OR/MS Today, February 2012.

5. Horvitz, Eric, Abbas, Ali, 2012, “Decision Analysis Workshop.” Procedures of Decision Analysis Workshop, Palo Alto, Calif., OR/MS Today, February 2012 (print version).

ormstoday.informs.org

What’s Your StORy? Thiago Serra

PhD Candidate and President of the INFORMS Student Chapter at Carnegie Mellon INFORMS member since 2012 What advice do you have for new students entering this field? Including how you handle work/life/school balance.

No one is ever done mastering math, coding, writing, presenting, and time management.

The mathematician Terry Tao has great career advice on his blog. My favorite is the suggestion to always push yourself to do things slightly out of your comfort zone. Read the “Handbook of Writing for the Mathematical Sciences” and “The Official TED Guide to Public Speaking.”

Watch Randy Pausch’s video on time management.

What prompted you to enter this field? Why? I was a freshman and looking for something meaningful for a career as software developer—I found that with computational optimization. I fell in love with the idea of coding systems to make better decisions, pushing myself to learn more math, and measuring the impact of my work in terms of money, resources, and time saved for everyone around.

Which INFORMS event are you most looking forward to this year?

The INFORMS Computing Society Conference in Austin, where I am chairing a session on new paradigms for cut generation. I am glad that Chen Chen (Columbia), Joseph Paat (Johns Hopkins), and Yuan Zhou (UC Davis) have accepted my invitation to present. They have all been doing great work. Based on the first session held at the Optimization Society Conference in Princeton, I am expecting a good and engaging audience.

What is something you learned in the last week?

George Dantzig, the father of the simplex method, learned about upper bounds the hard way.

When his doctor told him to limit his calorie intake, he tried to formulate his own diet problem to maximize his feeling of satisfaction. But some constraints were still missing, so he got the following unusual suggestions in his first attempts: consume 500 gallons of vinegar, then 200 bouillon cubes, and lastly two pounds of bran a day!

More questions for Thiago?

Ask him in the Open Forum on INFORMS Connect!

http://connect.informs.org

Does Product Contain the Following Usability Features

Does Product Implement the Following Decision Algorithms

Other?

Support Elicitation of Decision Analysis Component

Window s Mac OS Unix/Lin ux Web Im plemen tation Multiple Competi ng Obje Uncerta ctives inty Probab ilistic D epende Risk To ncies lerance Sequen tial Dec (e.g., Dec ision-M aking ision Tree s) Portfoli o Decis ion-Ma Two-Wa king y Sensit ivity An Multiple alysis Stakeho lders Co Evidenti llaborati a on (e.g., Bay l Reasoning esian Bel ief Netw orks) Model S tructure /Brains Value F torming unction s/Score Criteria s /Attribu te Weighti Probab ng ilities Risk To lerance Value o f Imperf ect Info Strateg rmation y Tables List Com Multiple ponents Whic hP Method s of Elic rovide itation

Software Product Listing

Used for the Following Decision Analysis Applications

Interfac es to Oth er Softw Import are (e.g., da tabase, Export (e spreadsh .g., prese eet) n tation g XML raphics, data) API (em bedded decision Can Mo support d system) Displaye el Segments b e d on Sc reen an Copied, Moved d Printe , Protect d Data fro m Other Protect Users Model S tructure Docume and Form nt Struc ulae ture & J Tools fo udgmen r Group ts w/text E li citation Decentr ?

If alized G roup Eli yes: Simulta citation neous D ata Inpu Keep R t & View ecord o ing f Model MODA/M Evolutio AUT n AHP

Support for Operating System(s)

@RISK

y – – – y y y y n y y – n y y y y y y y

–

1000Minds

y y y y y y n n y y n y n y y y n n n n

Value functions/ scores, criteria/ attribute weighting

Analytic Solver Platform for Excel

y – – – n y y y y y y n n n y n y y n y

–

Analytica

y – – y y y y y y y y y – y y y y – n y Probability y y y y y y y y y y y n n y n – distributions.

Powerful enough to build elicitation tools

AnalyticSolver.com

– – – y n y y y y y y n n n y n y y n n

–

y y y n n y y n y n – – – n n –

ChemDecide

y – – – y y n y n y n y n y y y n y n n

–

y y y y n y y n y n n n n y y MARE, ELECTRE III

D-Sight CDM

y y y y y n n n n y y y n n y y n n n n

–

n y y y n y y y y y y y n y y PROMETHEE

DEA SolverPro

y – – – y y y y – y y y – y y y y y y y

–

y y y n n y y y n n n n n n n Data Envelopment Analysis

DecideIT

Consey y – y y y n y y n y n n y y y y y n n y y n n y n n y n n n n y n The Delta quence decision library values, for imprecise probabilities, information. criteria weights

Decision Explorer

y – – – y y n n n n n y n y n n n n n n

Decision Quality Desktop (including DTrio and TreeTop)

y – – – y y y y y n y y y y y y y y y y Expert y y y n y y n n y y y y n y y User definable interviewing; decision metrics uncertainty & reliability charac. templates;

Palisade Corporation

1000Minds

Frontline Systems Inc.

Lumina Decision Systems, Inc.

Frontline Systems Inc.

Britest Limited

D-Sight

SAITECH, Inc.

Preference

Banxia Software Ltd.

Decision Frameworks

40 | ORMS Today

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October 2016

–

y y y n y y y y y n – – – n n –

y y y y y y y y y y y y y y n PAPRIKA

y y y n n y y n y n – – – n n –

y y y y y y y y y y n y n n n –

ormstoday.informs.org

y

y n n y http:// www. palisade. com/ academic

http:// www. palisade. com/risk

http:// www. palisade. com/risk

y y n

y

y y y y Free for teaching and unfunded research

POA

POA

y y y

n

y y n y

–

$4,995

y y y

Specific Industries or Market Specific Applications in which Segments in which the Product the Product is More Widely is More Popular Used

Comments

S

y y y y

–

Palisade is a registered education provider for PMI and AACE. Palisade is also registered with NASBA.

Finance, insurance, oil/gas/energy, Six Sigma, manufacturing, pharmaceuticals, aerospace, government and more.

VAR and NPV evaluations, schedule risk, cost estimation, project management, reserves estimation, supply chain mgmt.

Uses Monte Carlo Simulation to show possible outcomes in spreadsheet model – and how likely they are to occur.

Annual y y y y license or project license

–

Group facilitation tools to aid elicitation of criteria, compare intuitive rankings and test inter-rater reliability.

Health, education, academia, government, agribusiness.

Patient prioritization, social services targeting, business consulting, project portfolio management, conjoint analysis

Suite of online tools for prioritization, group decision-making, conjoint analysis and maximizing value for money. Free trial.

y y y y

–

Monte Carlo Energy, Simulation on decision pharmaceuticals trees, yielding full distributions at nodes.

Heavily used in MBA education

Comprehensive analytics in Excel, including decision analysis, simulation/ risk analysis, optimization, forecasting, etc.

y

y y y y Analytica Enterprise Professional Multiuser y y y y Free 101. $2,795, $995, & Floating

Others Analytica licenses 50% of Optimizer Cloud and group commercial $4,995 Player plans price available

–

Monte Carlo and Optimization to support large and complex decision models

Most industries, with special concentration in energy and environment and finance, industry and government

Practical online decision support tools, risk analysis, optimization multistakeholder, multiattribute DA.

Provides key DA tools, esp. influence diagrams, to analysts who may not be DA experts and find spreadsheets inadequate

y y y

n

y y n y

Free student 140-day license in Fall 2016.

–

–

–

Too new to cite.

AnalyticSolver.com Too new to cite.

Comprehensive cloud-based analytics, includes decision analysis, simulation/risk analysis, optimization, forecasting, etc.

y y y

y

n n n n

N/A

N/A

Only for License y n y y Britest – Britest for Britest Facilitator members members Training only

Chemical and Pharma Route selection, chemical storage, equipment selection and sourcing decisions

y y y

y

n n n y Annual license per user available for academics

N/A

Contact vendor for details

–

y y y y

–

–

D-Sight CDM is easily set up by the customer themselves and is therefore used in academic, public and private sector.

D-Sight CDM is easily – set up by the customer themselves and is used throughout a variety of decisionmaking contexts.

y y y

y

y n n y

See Website

–

See Website

–

n y y n

–

–

Ranking of heterogeneous entities, performance and efficiency comparison

Public sectors, hospitals, banking, retail, manufacturing, service industries

y y n

n

y y n y Free of charge

–

€1990

Standard y y y n price €1990.

Multi-user license on request

–

–

Public decisionICT for development, making, policymaking health policy

n n n

y

n y y y 295 GBP per user

–

495 GBP per user

Licensed y – – y per user

–

Causal mapping tool with analytical language to manage complexity and gain insight into complex issues

Management of complex issues within organizations to make the best decisions

Strategy development, – conflict resolution, stakeholder analysis, Scenario building

Decision framing; decision governance; D&R timelines; game theory; cumulative prob charts; tornado comparisons; etc.

Upstream oil & gas; energy; tech; pharmaceuticals

Project development; project and company strategy; value of information; R&D; optimization; operational decisions

$60

Contact vendor for details

(personal version 99 GBP)

y y y

y

Open TreeTop enrollment Enterprise development with classes; proprietary webinars; links videos

Contact vendor for details

Vendor 3rd Part y Classro om Online

multane

Describ e Comme Licensing Op rcial Ve ti rsion (e ons for the al, #si .g., individu

Comme rcial

Enhanc ed/High Perform ance

y y y

Features not Explicitly Stated Previously which Support DA

Describ e Instructo Certification P ro rs or Re cognize grams for d Profic iency

Traing Classes Offered

mu ous use lti-user, rs/token s)

Pricing & Licensing Information

Graphic al Sens itivity A Graphic nalysis al Displa y of Ana User-cu lytical R stomize esults d Graph Interacti ics v e Interfac Graphics, D is e Analytic s that Allow U plays or se al Comp onents rs to Adjust Expecte d Value Tornado Decisio Diagram n Trees s Influenc e Diagra m s Limited Use (run -time) o r Demo Version Educati on

Does Product Support the Following Visualization Features and Outputs

Contact vendor for details

Contact vendor for details

y y y y

(personal version 99 GBP)

–

y y y y

Named y n y y Decision Frameuser; works flexible supports period; Society of corporate Decision license Prof.cert.

October 2016

|

–

1000+ users worldwide; desktop, floating, network and classroom licenses available Implements the Delta decision library for decision evaluation with imprecise information, such as interval-values and rank statements.

Decision Quality Desktop includes DTrio for Decision Framing and TreeTop for Decision and Uncertainty Analysis

ORMS Today

| 41

Support Elicitation of Decision Analysis Component

Does Product Contain the Following Usability Features

Does Product Implement the Following Decision Algorithms

Other?

Window s Mac OS Unix/Lin ux Web Im plemen tation Multiple Competi ng Obje Uncerta ctives inty Probab ilistic D epende Risk To ncies lerance Sequen tial Dec (e.g., Dec ision-M aking ision Tree s) Portfoli o Decis ion-Ma Two-Wa king y Sensit ivity An Multiple alysis Stakeho lders Co Evidenti llaborati a on (e.g., Bay l Reasoning esian Bel ief Netw orks) Model S tructure /Brains Value F torming unction s/Score Criteria s /Attribu te Weighti Probab ng ilities Risk To lerance Value o f Imperf ect Info Strateg rmation y Tables List Com Multiple ponents Whic hP Method s of Elic rovide itation

Software Product Listing

Used for the Following Decision Analysis Applications

Interfac es to Oth er Softw Import are (e.g., da tabase, Export (e spreadsh .g., prese eet) n tation g XML raphics, data) API (em bedded decision Can Mo support d system) Displaye el Segments b e d on Sc reen an Copied, Moved d Printe , Protect d Data fro m Other Protect Users Model S tructure Docume and Form nt Struc ulae ture & J Tools fo udgmen r Group ts w/text E li citation Decentr ?

If alized G roup Eli yes: Simulta citation neous D ata Inpu Keep R t & View ecord o ing f Model MODA/M Evolutio AUT n AHP

Support for Operating System(s)

DiscoverSim

y y – – y y y y n n y n n n n n y y n n

DPL

y y – y y y y y y y y y y y y y y y y y Probabilities, y y y y y y n y y n – – – y n Decision Tree value of roll-back using information, expected values, strategy Monte Carlo tables, etc.

Simulation, Multiagent

Equity3

y – – – y n n y n y n y n y y y n n n n

–

y y y y n y n n n n n n n y n –

FOCUS

y – – – y y n y n y y y n y y y y y n n

–

y y y y n y y y y y n y y y n –

GoldSim

y – – – y y y n y y y y – y n n y n y n

–

y y y – y y y y y n – – – y – –

Hiview3

y – – – y n n y n n y y n y y y n n n n

–

SigmaXL, Inc.

Syncopation Software, Inc.

Catalyze Ltd.

Catalyze Ltd.

GoldSim

Catalyze Ltd.

–

y y y n n y y y n n – – – n n Monte Carlo Simulation

y n y y n y y n y n n n n y n Hiview3 MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique)

Intelligent Decision System (IDS)

y – – y y y y y n n y y y y y y y y y n Contact Vendor

Logical Decisions v7.2

y – – – y y n y n y y y n y y y y y y n

MeenyMo

y y y y y y n n n y n n n y y y n n n n

–

y y n n n n y y n n – – – y n PAPRIKA

SensIt

y y – – n y n n n n y n n n n n n n n n

–

y y y y n y y y y n – – – n n Automated Sensitivity Analysis: One-Way Tornado and Spider; TwoWay Tornado

SimVoi

y y – – n y y n n n n n n n n n n n n n

–

y y y y n y y y y n – – – n n Automatically determines value of information for uncertain input variables

Decision and Cognitive Sciences Research Centre, Alliance Manchester Business School, The University of Manchester

Logical Decisions

1000Minds

TreePlan Software

TreePlan Software

42 | ORMS Today

|

October 2016

y y y n y y n y y n n n n y y Evidential Reasoning approach

Value y y y n y y n n y y n y n y y – Functions/ Scores, Criteria/ Attribute Weighting

ormstoday.informs.org

y n n y

$160

–

Bundled with SigmaXL Medical devices for statistical and (validated), graphical analysis. communication products, healthcare and cosmetics.

Quality, design for Six Excel Add-In for Monte Sigma, risk and project Carlo Simulation and management Global Optimization with MIDACO Solver

Capital investment strategy, project valuation, risk management, portfolio prioritization

DPL is a proven tool for decision analysis, risk analysis, real option valuation and Monte Carlo Simulation.

R&D investment prioritization, strategy planning, resource allocation, zero-based budgeting and business prioritization.

MCDA portfolio modelling tool for helping you construct your most efficient portfolio of investments. Ideal for group workshops.

multane

–

y y y

y

$1,995 $1,495 Named- y n y y y y y y Individual from $59; Enterprise Professional user Department version version; licenses site $249 $1,995 and Group Enterprise licenses version available

–

Real options analysis, policy trees/policy summaries, influence diagram/decision tree hybrid models, Monte Carlo Simulation

y y y

y

n n n y 1,000 GBP

y n y n

–

Efficiency frontier and Multiple sectors and analysis. Trade-off industries analysis.

1,950 GBP

S

y n n n

(fully functional perpetual license)

–

Comments

Describ e Instructo Certification P ro rs or Re cognize grams for d Profic iency

mu ous use lti-user, rs/token s)

Specific Industries or Market Specific Applications in which Segments in which the Product the Product is More Widely is More Popular Used

–

individu

Comme rcial

$995

Features not Explicitly Stated Previously which Support DA

Vendor 3rd Part y Classro om Online

n

Traing Classes Offered

Describ e Comme Licensing Op rcial Ve ti rsion (e ons for the al, #si .g.,

y y y

Enhanc ed/High Perform ance

Pricing & Licensing Information

Graphic al Sens itivity A Graphic nalysis al Displa y of Ana User-cu lytical R stomize esults d Graph Interacti ics v e Interfac Graphics, D is e Analytic s that Allow U plays or se al Comp onents rs to Adjust Expecte d Value Tornado Decisio Diagram n Trees s Influenc e Diagra m s Limited Use (run -time) o r Demo Version Educati on

Does Product Support the Following Visualization Features and Outputs

–

(site licence)

/250 GBP

Oil & gas, electric power, utilities, mining, life sciences, financial services, new product development, infrastructure

(instructor)

/50 GBP (student)

y y y

y

y n n n

–

–

Please contact Catalyze

Multi- n n n n user site licenses

–

–

Engineering, Scientific Strategic planning, – and Defence business prioritization, balance of investment

y y y

y

y y y y

Free

–

$4,450

Individual y y y – licenses; multi-user network licenses

–

–

Mining, engineering consulting, water resources, environmental engineering, hazardous and radioactive waste mgmt.

y y n

n

n y n y 1,000 GBP

–

1,050 GBP

y n y n

–

–

Mine water balance, water resources, radioactive waste management, engineering risk analysis

–

Value Tree. MACBETH Multiple sectors and can be used to build industries preference scales and value functions

Capital projects, policy setting, strategy selection, relocation issues, problemsolving and budget resourcing.

MCDA option appraisal and evaluation of options. Highly configurable for a host of applications. Ideal for group workshops.

–

Inputs can have missing data & vague judgments. Outputs include probability distributions for informative decision-making.

Health care, fault diagnosis, financial investment decisionmaking

Risk and safety assessment and management

Evidential Reasoning extends Bayesian reasoning for handling imprecise probabilities and evidence which may not be fully reliable.

–

–

Military, Intelligence, Health, Automotive, Education

Analysis of Alternatives, MODA, Portfolio Analysis

Logical Decisions– Version 7.2 helps evaluate choices requiring critical preference and value judgments.

n n n n

–

Many decision Individuals and templates are provided. consumers.

Supports rich information about alternatives, e.g., URLs, map location, images.

Personal and consumer decisionmaking, product selection.

Focused on personal decision-making. Ease of use is given priority over academic analysis, with templates to help people get started.

(site licence)

/250 GBP (instructor)

/50 GBP (student)

y y y

y

n n n y Student Full version £600 per Contact y y y y version no for research license software exp. date, and £1,200 per developer up to 50 teaching is license for atttributes, £600 per details and is free license

y y y

y

n n n y

$295 professor, $65 Student

Group $1,895; Portfolio $2,895; Both $3,895

$895

y y n

n

n n n y

Free

Free

Free

n y y

n

y n n y Single license $17 and volume discounts

–

Single Single n n n n license $59 license and volume $59 and discounts volume discounts

–

–

All industries and market segments using spreadsheet what-if planning models

Sensitivity analysis of a spreadsheet model to create spider and tornado charts

Sensitivity analysis add-in for Microsoft Excel (Windows and Macintosh)

n y y

n

n n n y Single license $23 and volume discounts

–

Single Single n n n n license $79 license and volume $79 and discounts volume discounts

–

Automatically determines value of information for uncertain input variables

All industries and market segments using spreadsheet what-if planning models

Monte Carlo Simulation of spreadsheet planning models and automatic estimation of value of information

Monte Carlo Simulation add-in for Microsoft Excel (Windows and Macintosh)

Multi- y y y n user, Individual, #Simultaneous –

October 2016

|

ORMS Today

| 43

Does Product Contain the Following Usability Features

Does Product Implement the Following Decision Algorithms

Other?

Support Elicitation of Decision Analysis Component

Window s Mac OS Unix/Lin ux Web Im plemen tation Multiple Competi ng Obje Uncerta ctives inty Probab ilistic D epende Risk To ncies lerance Sequen tial Dec (e.g., Dec ision-M aking ision Tree s) Portfoli o Decis ion-Ma Two-Wa king y Sensit ivity An Multiple alysis Stakeho lders Co Evidenti llaborati a on (e.g., Bay l Reasoning esian Bel ief Netw orks) Model S tructure /Brains Value F torming unction s/Score Criteria s /Attribu te Weighti Probab ng ilities Risk To lerance Value o f Imperf ect Info Strateg rmation y Tables List Com Multiple ponents Whic hP Method s of Elic rovide itation

Software Product Listing

Used for the Following Decision Analysis Applications

Interfac es to Oth er Softw Import are (e.g., da tabase, Export (e spreadsh .g., prese eet) n tation g XML raphics, data) API (em bedded decision Can Mo support d system) Displaye el Segments b e d on Sc reen an Copied, Moved d Printe , Protect d Data fro m Other Protect Users Model S tructure Docume and Form nt Struc ulae ture & J Tools fo udgmen r Group ts w/text E li citation Decentr ?

If alized G roup Eli yes: Simulta citation neous D ata Inpu Keep R t & View ecord o ing f Model MODA/M Evolutio AUT n AHP

Support for Operating System(s)

SLIM

y y y y y y y y y y y y n n y y y – y y

–

y y y y y y y y y n – – – n n MJC2 in-house algorithms

Smart Decisions

y – – y y y n n n y y y n y y y n n n y

–

n y y y n n n n y y y n y y n –

Smart-Swaps

y y y y y n n n n n n n n y n n n n n n

–

n n n n n n y n y n – – – n n Even swaps method

The DecisionTools Suite

y – – – y y y y y y y – y y y y y y y y

–

y y y n y y y y y n – – – n n –

TransparentChoice

– – – y y n n y n y y y n y y y n y n n

AHP, scoring, online ideation

y y y n n y y y y y y y y n y –

TreePlan

y y – – n y y y y n n n n n n n n n n n

–

y y y y n y y y y n – – – n n Decision tree rollback using expected value or risk utility

Web-HIPRE

y y y y y n n n n n – y n y y y n n n n

–

n n n n n n y n y y y y n y y Various MAVT weighting techniques

MJC2

Cogentus

Systems Analysis Laboratory, School of Science, Aalto University

Palisade Corporation

TransparentChoice Limited

TreePlan Software

Systems Analysis Laboratory, School of Science, Aalto University

VENDOR DIRECTORY Banxia Software Ltd. 141 Highgate Kendal, Cumbria LA9 4EN UK +44 1539 815660 info@banxia.com www.banxia.com

Britest Limited The Innovation Centre Sci-tech Daresbury Daresbury, Cheshire WA4 4FS UK +44 (0)1925 607030 enquiries@britest.co.uk https://www.britest.co.uk/

Catalyze Ltd. 1000Minds 31 Connell Street Dunedin, Te Waipounamu 9013 NZ +64 3 974 8270 enquiries@1000minds.com https://www.1000minds.com, https:// meenymo.com

44 | ORMS Today

|

42 Main Road Colden Common Winchester, Hampshire SO21 1RR UK 01962 775923 ambermorgan@catalyzeconsulting.com www.catalyzeconsulting.com

October 2016

Cogentus Suite 17, Projection West Merchants Place Reading, Wiltshire SN11 9PF UK +44 1189 505 927 sales@cogentus.co.uk www.cogentus.co.uk

D-Sight 4 Rue des PËres Blancs Brussels, 1040 Belgium +32 2 737 67 37 info@d-sight.com http://www.d-sight.com/solutions/dsight-cdm

Decision and Cognitive Sciences Research Centre. Alliance Manchester Business School.

The University of Manchester Manchester, M13 9SS UK 0044 161 306 3427 Jian-Bo.Yang@Manchester.ac.uk

https://php.portals.mbs.ac.uk/ JianBoYang/Research/tabid/1074/Default. aspx

Decision Frameworks 9821 Katy Freeway Suite 550 Houston, TX 77024 USA 713-647-9736 sales@decisionframeworks.com www.decisionframeworks.com

Frontline Systems Inc. P.O. Box 4288 Incline Village, NV 89450 USA 775-831-0300 info@solver.com www.solver.com, https://analyticsolver.com

GoldSim 22500 SE 64th Place Suite 240 Issaquah, WA 98027 USA 425-295-6985

ormstoday.informs.org

POA

y y n

y

n n n y

–

–

–

n n –

–

n – – –

–

–

–

y y y

y

y y y y http:// www. palisade. com/ academic

http:// www. palisade. com/risk

y y y

y

n n n y Depends on use case free to few thousand dollars

NA

n y y

n

n y n y Single license $17 and volume discounts

–

y y –

–

n – – – Free at www.hipre. hut.fi

–

Logical Decisions 9206 Saint Marks Pl. Fairfax, VA 22031 USA 303-725-2898 gary@logicaldecisions.com www.logicaldecisions.com

Lumina Decision Systems, Inc 26010 Highland Way Los Gatos, CA 95033 USA 650-212-1212 sales@lumina.com www.Lumina.com

MJC2 33 Wellington Business Park Crowthorne, Berkshire RG45 6LS UK 1344760000 info@mjc2.com https://www.mjc2.com/strategicplanning-logistics.htm

–

y y y n

–

–

Logistics, transport, Logistics and supply manufacturing, supply chain optimization chain

Platinum, y n y y Gold, Silver and Bronze Editions available

–

Includes high-quality brainstorming functionality for options generation.

Creativity techniques plus Triz.

Government and private sector.

–

Support for the Even General multiple Swaps process: criteria decision finding of dominated making alternatives, suggestions for next swaps, backtracking of swaps

–

n n n n

Comments

S

Describ e Instructo Certification P ro rs or Re cognize grams for d Profic iency

POA

multane

POA

Specific Industries or Market Specific Applications in which Segments in which the Product the Product is More Widely is More Popular Used

Vendor 3rd Part y Classro om Online

n y n n

Features not Explicitly Stated Previously which Support DA

Describ e Comme Licensing Op rcial Ve ti rsion (e ons for the al, #si .g.,

Comme rcial

y

individu

Enhanc ed/High Perform ance

y y y

software@goldsim.com www.goldsim.com

Traing Classes Offered

mu ous use lti-user, rs/token s)

Pricing & Licensing Information

Graphic al Sens itivity A Graphic nalysis al Displa y of Ana User-cu lytical R stomize esults d Graph Interacti ics v e Interfac Graphics, D is e Analytic s that Allow U plays or se al Comp onents rs to Adjust Expecte d Value Tornado Decisio Diagram n Trees s Influenc e Diagra m s Limited Use (run -time) o r Demo Version Educati on

Does Product Support the Following Visualization Features and Outputs

http:// Contact y y y y Education Monte Carlo Simulation, www. vendor for provider optimization, distripalisade. details for PMI bution fitting, custocom/risk & AACE; mized reports, time registered series and more. w/NASBA

–

Evaluation and project Best in class features portfolios for MCDA software.

Multiple criteria evaluation of a set of alternatives

–

Finance, insurance, oil/gas/energy, Six Sigma, manufacturing, pharmaceuticals, aerospace, government and more.

VAR and NPV evaluations, schedule risk, cost estimation, project management, reserves estimation, supply chain mgmt.

An integrated set of programs for risk analysis and decision-making under uncertainty that runs in Microsoft Excel.

Easy to use, yet powerful AHP-based collaborative online software.

$5k to Pricing n y n y None six-figures depends on use case and capacity

–

Government, aerospace, manufacturing, life-sciences, IT decision-making and many more...

Prioritization (of project, product features, R&D initiatives), policy selection (gov’t), procurement, site selection, etc.

Single Single n n n n license $59 license and volume $59 and discounts volume discounts

–

–

Finance, energy, pharma, legal

Analysis of sequential Decision tree add-in decision problems for Microsoft Excel under uncertainty (Windows and Macintosh)

–

–

Product evaluation, environmental decision making, strategic decisionmaking, policy analysis

Evaluation of discrete choice alternatives, multiple stakeholders, academic courses on decision analysis

Contact vendor

–

n n n y

Palisade Corporation 798 Cascadilla St. Ithaca, NY 14850 USA 607-277-8000 sales@palisade.com www.palisade.com

Preference Villa Bjaelbo, Elfvik, Lidingˆ SE - 181 90 Sweden +46 (0) 768 349 007 info@preference.bz http://www.preference.bz

SAITECH, inc.

P.O. Box 431 Holmdel, NJ 07733 USA 732-410-9192 dea@saitech-inc.com http://www.saitech-inc.com

SigmaXL, Inc.

MCDA software with several MAVT weighting techniques and AHP. Web browser interface.

Aggregation of models into a group model

TransparentChoice Limited

305 King Street West Suite 503 Kitchener, Ontario N2G 1B9 Canada +1-888-SigmaXL (744-6295) info@SigmaXL.com http://sigmaxl.com/DiscoverSim.shtml

Syncopation Software, Inc

ideaSpace West 3 Charles Babbage Road Cambridge CB3 0GT UK +447403714714 contact@transparentchoice.com www.transparentchoice.com

TreePlan Software

6 State St. Suite 308 Bangor, ME 04401 USA +1 866-796-2375 +1 866-796-4688 www.syncopation.com

2105 Buchanan St. San Francisco, CA 94115 USA 415.310.7190 Mike@TreePlan.com http://www.treeplan.com

Systems Analysis Laboratory, School of Science, Aalto University P.O. Box 11100 Aalto FIN-00076 FINLAND +358-500-677942 raimo.hamalainen@aalto.fi http://www.smart-swaps.hut.fi, http://www.hipre.hut.fi

October 2016

|

ORMS Today

| 45

2016

All activities on this page will be held in the Exhibit Hall A in the Music City Center on Level 3.

INFORMS

COFFEE BREAK

EXHIBITORS

ANNUAL MEETING

Come and get your caffeine fix!

Sun: 4–4:30pm Mon-Tues: 9:30–10am and 4–4:30pm Wed: 9:30–10am and 2:15–2:45pm

!

EXHIBIT Sun: 12–5pm, 7:30–9pm

HALL

HOURS

Mon-Tues: 9am–5pm Wed: 9am–3pm

WELCOME RECEPTION

Dozens of booths where you can visit and learn about new products and technologies.

Meet the INFORMS Board and Staff Sunday evening at the INFORMS Center, 7:30–9pm with hors d'oeuvres and a cash bar.

POSTER

Space for attendees to relax, hang out, and meet others. Make sure to follow @informs2016 for special pop-up events.

SESSIONS Researchers, practitioners, and students share their research in these special sessions on Mon & Tues 12:30–2:30pm

NETWORKING LOUNGE

REGISTRATION CHARGING STATIONS

INFORMS CENTER

Outta juice? Stop by the INFORMS Center to recharge your devices.

Sun-Tues: 7am–5pm Wed: 7am–4:30pm

For quickest queue, register before you get to Nashville.

FREE

WIFI

TECHNOLOGY

CENTER

Check your email or online schedule of INFORMS Center events.

2017 During Exhibit Hall Hours

MEMBERSHIP

RENEWAL

This dynamic space is the hub for your key Annual Meeting activities.

Be sure to stop by and see INFORMS leadership and staff, and learn more about the many programs and activities taking place both at the Annual Meeting and throughout the year. Make sure to check the Mobile App or the website for an up-to-date schedule of INFORMS Center activities.

Bring your member ID for fast and easy renewal.

CAREER CENTER

Career Fair for job seekers, one-on-one interviews, résumé review and drop off.

Nashville 2016

Make sure you’re there to optimize your Annual Meeting experience.

meetings.informs.org/nashville2016

ormstoday.informs.org

news

Inside News

48 In Memoriam: Charles D. Flagle

49 In Memoriam: András Prékopa

49 In Memoriam: Leo Kroon

50 Guide to vendor exhibitors

53 People

54 Meetings

In Memoriam

Jack Borsting (1929-2016) Jack Borsting, an INFORMS Fellow and a former assistant secretary of defense whose extensive and influential professional career included numerous top-level positions in academia, the government and the corporate world, passed away Aug. 16 in Monterey, Calif., not far from the Naval Postgraduate School where he maintained a career-long alliance. He was 87.

Dr. Borsting was the 24th president of the Operations Research Society of America (ORSA, a forerunner of INFORMS). In addition to being elected an INFORMS Fellow, he received the Kimball Medal from ORSA for distinguished service to the Institute and the profession, as well as the Steinhardt Prize for military O.R. research.

Born in Portland, Ore., in 1929, Dr. Borsting earned a bachelor’s degree (1951) in mathematics from Oregon State University and a master’s (1952) and Ph.D. (1959) in mathematics from the University of Oregon. He joined the faculty at the Naval Postgraduate School (NPS) in 1959, where he taught mathematics and operations research. At the age of 35, he was asked to chair the school’s Department of Operations Research.

“He immediately began to grow the department’s faculty in response to Navy demand for its curriculum, and to recruit new faculty,” recalls NPS Distinguished Professor of Operations Research Dave Schrady. “Jack set the groundwork for what is now arguably considered the best teaching and research faculty in operations research anywhere.”

In 1974, Dr. Borsting was promoted to provost at NPS, a post he held until 1980.

Although he would go on to hold many other prestigious positions throughout his illustrious career, Dr. Borsting maintained close ties to the NPS in some capacity,

whether it was on the NPS Advisory Board or on a student’s dissertation committee.

One of his proudest professional moments, according to family members, was when President Carter and President Reagan appointed him assistant secretary of defense (comptroller) for the U.S. Department of Defense from 1980 to 1983.

Dr. Borsting returned to academia in 1983 when he was named dean of the University of Miami’s School of Business Administration, a post he held until1988.

From 1988 to 1993, Dr. Borsting served as professor and dean of the University of Southern California’s (USC) Marshall School of Business Administration. Following his years as dean, he continued at USC Marshall as the E. Morgan Stanley Professor of Business Administration and executive director of the Institute for Communication Technology Management. In 2011, his contributions to the university were honored with the USC Faculty Lifetime Achievement Award, presented to a very select number of retired faculty members at the annual Academic Honors Convocation.

“We have lost a dear member of our Trojan family, a gifted teacher, a dedicated public servant and an admired scholar,” said school dean James G. Ellis. “Jack was a warm and wonderful man who will be deeply missed.”

Winter Simulation Conference 2016 The 2016 Winter Simulation Conference (WSC) has been the premier international forum for disseminating recent advances in the field of systems simulation for almost 50 years. The longest-running conference devoted to simulation as a discipline, this year’s WSC will be held on Dec. 11-14 at the Crystal Gateway in Arlington, Va., just outside of Washington, D.C. The theme for WSC 2016 is “Simulating Complex Service Systems.”

WSC is designed for professionals and academics from all backgrounds and across a broad range of interests. Academic tracks include analysis methodology, modeling methodology, simulation optimization, agent-based simulation and hybrid simulations. Applied uses of simulation include social and behavioral simulation, defense and security, modeling and analysis of semiconductor manufacturing, healthcare application, logistics, manufacturing applications, networks and communications, project management and construction, environmental and sustainability applications, and general applications. Additionally, WSC features introductory and advanced tutorials, simulation education, case studies, Ph.D. colloquia, poster sessions, an extensive group of exhibitors and vendor tutorials.

Along with the lineup of tracks and speakers, WSC 2016 will also have a special cross-fertilization track.

WSC 2016 is sponsored by technical cosponsors ACM/SIGSIM, ASA, ASIM, IEEE/ SMC and NIST, along with IIE, INFORMSSIM and SCS. Early registration ends Nov. 1. Register now at www.wintersim.org.

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Along with his term as president of ORSA, Dr. Borsting served as president of the Military Operations Research Society (MORS) and was a recipient of its Vance Warner Award for distinguished service to the profession. Among his many other honors, he was honorary treasurer of the International Federation of Operational Research Societies (IFORS), a Fellow of the American Association for the Advancement of Science (AAAS) and of MORS, and a Trustee of the Institute for Defense Analyses (IDA). In 1982, Dr. Borsting received the Distinguished Service Award from Oregon

State University, and he was twice awarded the U.S. Department of Defense’s Medal for Distinguished Public Service. In 2005, he was designated an Alumni Fellow by the University of Oregon, and he was a dean emeritus at both NPS and USC. In the business sector, Dr. Borsting served on the corporate boards of Northrop Grumman Corporation, Security First Trust, PLATO Learning, Inc., Storer Communications, McDonnell Douglas Finance Corporation, Coast Savings Bank, Sun Bank of Miami, Ivax Diagnostics and Whitman Education Group and several

other companies. He also served as chair of the Board of Trustees of the Orthopedic Hospital Foundation, trustee of the Rose Hills Foundation, lead governor of the American Stock Exchange and as a member of the Army Science Board.

Dr. Borsting is survived by his wife of 63 years Peggy Anne Borsting, his daughter Lynn C. Hammond and his son Eric J. Borsting, along with his three grandchildren, Jessica M. Edwards, Matthew A. Borsting and Catherine A. Borsting. ORMS Sources: NPS, USC, INFORMS, Monterey Herald

In Memoriam

Charles D. Flagle (1919-2016) Charles D. Flagle, a pioneer in bringing operations research to bear on public health issues through his groundbreaking work at Johns Hopkins University and Johns Hopkins Hospital starting in the mid-1950s, passed away Sept. 4. He was 97.

An INFORMS Fellow, Dr. Flagle received the George E. Kimball Award in 1984 from INFORMS for distinguished service to the profession of operations research and the management sciences from the Operations Research Society of America (ORSA), a forerunner of INFORMS, and in recognition of his role in the establishment and growth of the ORSA Health Application Section. In 2002, he published an article concerning the origins of operation research in medicine and health sciences as seen through the lens of his career.

A Johns Hopkins Bloomberg School of Public Health professor emeritus, Flagle’s work in operations research and health services touched upon numerous subjects throughout his career. His work in the field helped advance the application of O.R. in key medical areas such as disease screening, diagnosis and therapy and medical application. He also studied the allocation of hospital resources and personnel scheduling problems.

“Dr. Flagle was among the founders of the field of health services research,” said Karen Kruse Thomas, historian of the Bloomberg School. “He pioneered applying mathematical and managerial approaches

to streamline large-scale health systems, including computerization and progressive patient care. His reforms at Johns Hopkins Hospital to group patients by their need for intensive, medium or semi-independent levels of care were adopted by hospitals to increase their admissions and improve the quality of care. The American health system owes him a great debt of thanks.”

Born and raised in the Baltimore, Md., area, Dr. Flagle received his bachelors of engineering degree in 1940 from Johns Hopkins University, and went on to design jet engine controls for the United States Army during the Second World War. He returned to Johns Hopkins in the 1950s as a graduate student, and worked under Robert H. Roy, the dean of the Johns Hopkins’ Department of Engineering, where he was introduced to the Hopkins’ Operations Research Office (ORO).

Dr. Flagle completed his doctoral program in 1955 and began teaching courses in queuing theory and stochastic process as an assistant professor in operations research and industrial engineering at Johns Hopkins. It was around this time that personnel in the ORO were beginning to work their way into the various Johns Hopkins Medical institutions. Visiting these facilities, Flagle noted, “Everywhere I looked, there were stochastic processes.” In 1956, Flagle was appointed head of the Operations Research division of the Johns Hopkins Hospital Director’s staff.

Dr. Flagle was invited to join the United States’ Public Health Service intramural research team in the late 1950s to evaluate the progression of patient care. Working with the USPHS, Flagle learned that he was not the only one interested in bringing O.R. principles to health services. With the sponsorship of the Nuffield Provincial Hospitals Trust, Dr. Flagle organized the first meeting on operations research and healthcare issues between professionals from the United States and the United Kingdom in 1960.

Dr. Flagle served as a special assistant to the U.S. surgeon general for applied health technology from 1967 to 1968, where he worked to implement electronic medical records systems. In 1978, he was elected to the Institute of Medicine of the National Academy of Sciences.

After retiring from teaching and being named a professor emeritus at Johns Hopkins, Dr. Flagle maintained a close relationship with his alma mater. The Charles D. Flagle Fund provides awards to graduate students at the Johns Hopkins Bloomberg School of Public Health. The Alumni Association at Hopkins awarded Dr. Flagle its Distinguished Alumnus Award in 2000.

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“What I will remember most about him was his incredible wit and good humor,” said Ellen J. MacKenzie, a Johns Hopkins public health professor and chair

of the Department of Health Policy and Management. “He was a great storyteller and very much a Renaissance man. He also cared deeply for the students and was,

himself, a great teacher and mentor. He will be sorely missed by many.”ORMS Sources: INFORMS, Johns Hopkins, Carroll County Times, Baltimore Sun

In Memoriam

András Prékopa (1929-2016) Dr. András Prékopa, mathematician, operations researcher, member of the Hungarian Academy of Sciences (“MTA”) and a 2014 recipient of the INFORMS President’s Award, passed away on Sept. 18 at the age of 87, surrounded by his family.

András Prékopa was born Sept. 11, 1929, in Nyiregyháza, Hungary. He graduated from Kossuth Lajos High School in 1947 and obtained a Master of Sciences degree in mathematics, physics and descriptive geometry in 1952 from the University of Debrecen.

He defended his Ph.D. in 1956, for which he obtained a Grünwald Géza Prize from the János Bolyai Mathematical Society.

From 1956 and 1968, Dr. Prékopa was a professor of Eötvös Loránd University (“ELTE”), and he subsequently became a professor of the Budapest Technical University. Between 1985 and 2015, he was a distinguished professor of operations research and statistics at RUTCOR at Rutgers University in New Brunswick, N.J., where he was affiliated with the Department of Management Science and Information Systems. Dr. Prékopa retired from Rutgers in 2015 as a distinguished professor emeritus.

In addition to his university responsibilities, between 1970 and 1985 Dr. Prékopa was the head of the Operations Research Department of the MTA’s Computer Science Center. He subsequently became the founder and head of the Applied Mathematics Division of the Computer Science and Automation Research Institute of the MTA. In 1979 the MTA awarded him corresponding membership, which was followed by full membership in 1985.

In 1983, Dr. Prékopa founded the Operations Research Department at ELTE and became its first chairman. In 1977, the Mexican Academy of Sciences awarded him corresponding membership. In 1991, he founded and became the honorary president of the Hungarian Operations Research Society,

and in 1996, the János Bolyai Mathematical Society awarded him honorary presidency.

Dr. Prékopa was the founding editor in chief of the Applied Mathematics Journal. From 1981 and 1989, he served as president of the Mathematical Programming Society’s Stochastic Programming Committee.

Dr. Prékopa’s scientific work was characterized by the high-level unification of theory and application. Some excellent examples of this are the applications and implementations of his models and procedures in the areas of hydrology, electric power production, economics, finance and biology, among others. Fiftyeight scientists obtained advanced degrees under Dr. Prékopa’s guidance, among them 16 at RUTCOR. Along with the INFORMS President’s Award and the Khachiyan Prize from the INFORMS Optimization Society, Dr. Prékopa received many other honors

including the Commander’s Cross of the Order of Merit of the Republic of Hungary.

During his scientific career, Dr. Prékopa published 20 books, several hundred scientific papers and 150 educational and popular scientific articles.

With his departure, the operations research community lost an outstanding scholar, an excellent teacher of operations research and applied mathematics, as well as a scientific event organizer with extraordinary abilities and energies. ORMS Source: INFORMS Open Forum (posted by Jonathan Eckstein, Rutgers University)

In Memoriam

Leo G. Kroon 1959-2016 Leo G. Kroon, a professor of quantitative logistics at Rotterdam School of Management, Erasmus University (RSM), and a logistics consultant in the Department of Process Quality and Innovation at Netherlands Railways (NS), passed away Sept. 14 at the age of 57.

Professor Kroon was a member of the NS team that won the prestigious INFORMS Edelman Award in 2008 for its model-based contributions to the development of the 2007 NS timetable. He was also the recipient of the 2008 ERIM Impact Award.

During his 32-year career at RSM, Professor Kroon served in many positions and roles: scientific researcher, professor,

ERIM member and ERIM Fellow, as well as a supervisor to many master’s students and Ph.D. candidates, and as chairman of the Examination Board.

Professor Kroon was instrumental in building a world-class research group on decision support tools for the planning and real-time operations control of public transport systems.

He will be remembered as a brilliant and erudite colleague who was committed to his students, Ph.D. candidates and colleagues. ORMS Source: RSM October 2016

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Exhibit Hours

Sunday, Nov. 13, 12 p.m.-5 p.m. • Welcome Reception: 7:30 p.m.-9:30 p.m.

Monday, Nov. 14, 9 a.m.-5 p.m. • Tuesday, Nov. 15, 9 a.m.-5 p.m. • Wednesday, Nov. 16, 9 a.m.-3 p.m.

2016 INFORMS Annual Meeting guide to exhibitors The following companies and organizations will feature innovative software products, publications and resources at the 2016 INFORMS Annual Meeting in Nashville on Nov. 13-16.

AIMMS Booth #48 www.aimms.com

AIMMS is an innovative technology company with offices in Europe, the United States and Asia. Half of the global Fortune top 20 corporations rely on AIMMS because of our unique analytics, modeling and optimization platform that supports both strategic and daily operational challenges such as supply chain optimization, strategic sourcing, pricing, workforce optimization, portfolio optimization and production planning and scheduling.

Amazon Booth #54 www.amazon.com/about

Amazon’s mission is to be Earth’s most customer-centric company where people can find and discover anything they want to buy online. Amazon’s evolution from website to e-commerce and publishing partner to development platform is driven by the pioneering spirit that is part of the company’s DNA. The world’s brightest technology minds come to Amazon to research and develop new technologies that improve the lives of our customers: shoppers, sellers, content creators, and developers around the world. Because that’s what being Earth’s most customer-centric company is all about, and it’s still Day 1 at Amazon.

AMPL Optimization Inc. Booth #40 www.ampl.com

AMPL’s modeling language and system give you an exceptionally powerful and natural tool for developing and deploying the complex optimization models that arise in diverse business applications. AMPL lets you formulate problems the way you think of them, while providing access to the advanced algorithmic alternatives that you need to find good solutions fast. It features an integrated scripting language for automating analyses and building iterative optimization schemes; access to spreadsheet and database files; and application programming interfaces for embedding within larger systems. AMPL works with over 30 powerful optimization engines including all of the most widely used large-scale solvers.

AnyLogic North America, LLC Booth #27 www.anylogic.com

Bayesia Booth #33 http://www.bayesialab.com/

BayesiaLab 6 is a powerful artificial intelligence software (Win/Mac/Unix), which provides scientists a comprehensive “lab” environment for machine learning, knowledge modeling, analytics, simulation and optimization – all based on the Bayesian network paradigm. BayesiaLab employs sophisticated learning algorithms to generate structural models from data for knowledge discovery. It enables researchers to explore high-dimensional problem domains like never before. BayesiaLab’s inference algorithms allow users to leverage Bayesian network models for complex evidential reasoning, even under uncertainty. In this context, BayesiaLab is unique in its ability to perform both observational and causal inference, facilitating the correct simulation of interventions in a system.

Cambridge University Press Booth #34 www.cambridge.org

Cambridge University Press’ publishing in books and journals combines state-of-the-art content with the highest standards of scholarship, writing and production. Visit our stand to browse new titles, available at a 20 percent discount, and to pick up sample copies of our journals. Visit our website to find out more about what we do: www.cambridge.org.

COIN-OR Booth #23 www.coin-or.org

The Computational Infrastructure for Operations Research publishes high-quality, free, open source tools for O.R. professionals and students, suitable for commercial, educational and personal use. COIN-OR is the place to go when you need a “white box” for algorithm research and development. COIN-OR is a strategic partner of the INFORMS Computing Society.

Cornell Tech

AnyLogic Software is the first and only tool that brings together System Dynamics, Process-centric (Discrete Event) and Agent Based methods within one modeling language and one model development environment is the leading provider of dynamic simulation tools, technologies and consulting services for business applications. The language of AnyLogic has unmatched flexibility enabling modelers to capture the complexity of business, economy and social systems at any level of detail to gain deeper insight into interdependent processes inside and around an organization.

Artelys Booth #47 www.artelys.com

Artelys is a global provider of decision-support solutions through numerical optimization and analytics technologies, with offices in France, United States, Canada and United Kingdom. The organization is particularly active in the energy and environment, logistics and transportation, telecommunications, finance and defense sectors with half of their clients coming from the top French stock market index (CAC 40). Artelys offers a superior level of expertise to help governments and commercial entities with highqualified consultants. The company also develops and supports a comprehensive portfolio of efficient and robust optimization tools such as Artelys Kalis, FICO Xpress

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Optimization suite, KNITRO and AMPL. In addition, many of our customers are professional who use the Artelys Crystal suite, a set of user-friendly software dedicated to the optimization of energy and transportation systems.

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Booth #7 http://tech.cornell.edu/

Cornell Tech has reinvented graduate tech education for the digital age, bridging the gap between academia and industry.

Our students are digital pioneers who believe in technology’s power for impact and change. At Cornell Tech, students across programs learn and work side-by-side, spending one-third of their experience together working together on a studiobased core curriculum. They collaborate with the tech industry and postdoc-level researchers to build start-up companies and new products. By bringing these talents together at the start, there is enormous potential for better, more impactful and ultimately more successful companies and products.

Master’s degree programs: Computer Science, Electrical and Computer Engineering, Operations Research and Information Engineering. Dual degree programs: Connective Media, Health Tech, and Law, Technology and Entrepreneurship.

Darden Business Publishing Booth #16 http://store.darden.virginia.edu

Darden Business Publishing markets case-based educational materials written by the renowned faculty at the University of Virginia Darden School of Business. Darden maintains a catalogue of student-centered learning materials that energize classrooms around the world with dynamic interactive simulations and thought-provoking paper cases.

Dynamic Ideas, LLC Booth #49 www.dynamic-ideas.com

Dynamic Ideas is a publisher of scientific books that have quality and originality in the areas of Operations Research and Applied Mathematics. The key objective of our titles is to “educate the next generation.” Many of our books are currently being used as the main textbook in academic courses in some of the finest universities and research institutions in the world.

Elsevier Booth #23 www.elsevier.com

Elsevier publishes leading journals in OR/MS and Decision Sciences, including European Journal of Operational Research, Computers & Operations Research and OmegaInternational Journal of Management Science. Elsevier journals occupy seven of the top 10 Impact Factor positions in the Thomson Reuters “Operations Research & Management Science” category. Come to the booth to find out more, including how to use Elsevier’s researcher centric tools to develop your research. Want to know more now? Visit https:// www.elsevier.com/social-sciences/decision-sciences.

FDA/Center for Drug Evaluation and Research Booth #38 www.fda.gov/AboutFDA/CentersOffices/ OfficeofMedicalProductsandTobacco/CDER/

The Center for Drug Evaluation and Research (CDER) performs an essential public health task by making sure that safe and effective drugs are available to improve the health of people in the United States.

FICO Booth #5 www.fico.com

FICO is a leading analytics software company, helping businesses in 90+ countries make better decisions that drive higher levels of growth, profitability and customer satisfaction. The company’s groundbreaking use of Big Data and mathematical algorithms to predict consumer behavior has transformed entire industries. FICO provides analytics software and tools used across multiple industries to manage risk, fight fraud, build more profitable customer relationships, optimize operations and meet strict government regulations.

Many of our products reach industry-wide adoption. These include the FICO® Score, the standard measure of consumer credit risk in the United States. FICO solutions leverage opensource standards and cloud computing to maximize flexibility, speed deployment and reduce costs. The company also helps millions of people manage their personal credit health.

Frontline Systems, Inc. Booth #39 www.solver.com

Frontline Systems is democratizing analytics, enabling business analysts and developers to get results quickly with just a browser, spreadsheet or programming language, instead of expensive enterprise software with steep learning curves. See how easily you can solve optimization, simulation/risk analysis, forecasting and data mining problems – starting for free, and scaling up easily to the largest models – using AnalyticSolver.com, Analytic Solver® for desktop Excel and our RASON® modeling language and REST API. Use our Solver and XLMiner® SDKs for C#, Java, C++, R and Python to create your own analytics applications.

Find your fastest path to real analytics results.

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GAMS Development Corporation Booth #4 www.gams.com

The General Algebraic Modeling System (GAMS) is a highlevel modeling system for mathematical programming and optimization. It consists of a language compiler and a stable of integrated high-performance solvers. GAMS is tailored for complex, large-scale modeling applications, and allows you to build large maintainable models that can be adapted quickly to new situations. Come to our booth to learn more about GAMS or ask for an evaluation license. You can also visit our technology workshop or software demo.

Gurobi Optimization, Inc. Booth #21 www.gurobi.com

Gurobi Optimization is dedicated to helping our users succeed with optimization. We provide the leading math programming solvers, offering best-in-class performance as well as a broad array of tools for developing and deploying optimization applications on top of these solvers. We support all of the most popular programming languages, as well as client-server architectures, cloud computing, and distributed optimization. We also provide outstanding, easy-to-reach support and transparent, no-surprises pricing.

IBM Booth #35 www.ibm.com

Critical business decisions can be made with ease when you know what is likely to happen in the future and how you should respond. IBM is paving the way to the next generation of analytics solutions and platforms by combining descriptive, predictive and prescriptive analytics with the power of cloud and cognitive insights. These advanced analytics capabilities provide robust, user-friendly platforms aimed at helping you solve even the most complex business and research problems. Visit the IBM Advanced Analytics booth to learn more about our family of offerings.

clearly and concisely, and it has links to Excel and databases that make data handling easy. LINDO API is a callable library that allows you to seamlessly embed the solvers into your own applications.

MathWorks Booth #8 www.mathworks.com

The MATLAB and Simulink product families are fundamental applied math and computational tools at the world’s educational institutions. Adopted by more than 5,000 universities and colleges, MathWorks products accelerate the pace of learning, teaching and research in engineering and science. MathWorks products also help prepare students for careers in industry worldwide, where the tools are widely used for data analysis, mathematical modeling and algorithm development in collaborative research and new product development. Application areas include data analytics, mechatronics, communication systems, image processing, computational finance and computational biology.

Military Operations Research Society Booth #10 http://www.mors.org/

MORS is a professional society of nearly 1,000 operations researchers and national security analysts. Since 1966 MORS’ mission has been to enhance the quality of analysis to address real-world national security interests through the advancement of the operations research profession.

Today, MORS services include the Annual MORS Symposium with 500+ classified and unclassified sessions, year-round communities of practice, geographic chapters, an annual Education and Professional Development Colloquium for students and young analysts, classified and unclassified special meetings/workshops, tutorials and CEU courses, Phalanx the magazine of national security analysis and a catalog of original books, reports and republished historical manuals.

MIT Sloan School of Management

Ivey Publishing Booth #9 www.iveycases.com

Ivey Publishing is the leader in providing business case studies with a global perspective. With over 35,000 products in our library, Ivey Publishing adds more than 350 classroom-tested case studies each year. Virtually all Ivey cases have teaching notes. Clear, concise and current, Ivey cases are lauded by the academic community as meeting the rigorous demands of management education by responding to the ever-changing needs of business and society. Meet with one of our case experts on how to publish with us and how you can integrate world-class cases into your curriculum.

LINDO Systems, Inc. Booth #29 www.lindo.com

Exceptional ease of use, widest range of capabilities and flexibility has made LINDO software the tool of choice for thousands of Operations Research professionals across nearly every industry for over 30 years. LINDO offers a full range of solvers to cover all your optimization needs.

The Linear Programming solvers handle million variable/ constraint problems fast and reliably. The Quadratic/SOCP/ Barrier solver efficiently handles quadratically constrained problems. The Integer solver works fast and reliably with LP, QP and NLP models. The Global NLP solver finds the guaranteed global optimum of non-convex models.

The Stochastic Programming solver has a full range of capabilities for planning under uncertainty.

LINDO provides a set of versatile intuitive interfaces to suit your modeling preference. What’s best is an add-in to Excel that you can use to quickly build spreadsheet models that managers can use and understand. LINDO has a fullfeatured modeling language for expressing complex models

Booth #52 http://mitsloan.mit.edu/

MIT Sloan is a mission-driven organization. We develop principled, innovative leaders who improve the world and generate ideas that advance management practice. Our diversified, specialized and action-oriented curriculum exemplifies our commitment to balancing innovative ideas and theories with hands-on, real-world application. The coursework at MIT Sloan is markedly rigorous and further distinguished by emphasis on real-world engagement that turns innovative ideas into practical solutions to the world’s problems. MIT Sloan School offers a variety of degree programs to help you advance your career. The two-year, full-time MBA program allows you to customize your curriculum to focus on specific areas of interest. Optional tracks and certificates in Enterprise Management, Entrepreneurship & Innovation, Finance, Healthcare and Sustainability help you dive more deeply into your career interests. The new one-year Master of Business Analytics program is tailored for graduating college seniors and early-stage professionals. The 12-month and 18-month Master of Finance program (MFin) is designed for students who want to become leaders in the field of finance.

MOSEK ApS Booth #46 www.mosek.com

MOSEK ApS provides optimization software to help clients making better decisions. It specializes in creating advanced software for solution of mathematical optimization problems.

In particular, the company focuses on solution of large-scale linear, quadratic and conic optimization problems. MOSEK ApS was established in 1997 by Erling D. Andersen and Knud D. Andersen. Our customer base consists of financial institutions and companies, engineering and software vendors, among others.

Neusrel Booth #19 www.neusrel.com

NEUSREL is the leading software for exploring cause-effect networks using the Universal Structure Modeling approach.

Because it leverages machine learning techniques, it is a self-learning system and the only methodology to explore previously not hypnotized nonlinearities (of any form) or interactions (of any type). It is the first system meeting the needs of researchers to explore success factors instead of just falsifying a giving set of hypothesis. It bridges the largely relevant gap between qualitative exploration and statistical testing/modeling. NEUSREL Causal Analytics is dedicated to provide software as well as training and statistical consulting to the academic community.

North Carolina State University, Industrial and Systems Engineering Booth #51 http://www.ise.ncsu.edu/

The Edward P. Fitts Department of Industrial and Systems Engineering at N.C. State University is among the top ranked programs in the country. The department brings together industry professionals and academic leaders across innovative and cutting-edge curriculum including regenerative medicine, health systems and advanced manufacturing.

Now Publishers Booth #30 http://www.nowpublishers.com

Now Publishers publishes a suite of reference journals called Foundations and Trends including Information Systems, Machine Learning, Operations Management, Optimization and Systems and Control, academic journals including the DEA Journal and Review of Behavioral Economics, and scholarly books in the fields of business and technology. We will also represent World Scientific, which publishes about 600 new titles a year and 130 journals in various fields. Started in 1981, it has established itself as one of the leading scientific publishers in the world, and the largest international scientific publisher in the Asia-Pacific region.

Optimization Direct Inc. Booth #24 www.optimizationdirect.com

Optimization Direct Inc., markets IBM® ILOG® CPLEX Optimization Studio®, the world’s leading software product for modeling and optimization. CPLEX Optimization Studio solves large-scale optimization problems and enables better business decisions and resulting financial benefits in areas such as supply chain management, operations, healthcare, retail, transportation, logistics and asset management. It has been applied in sectors as diverse as manufacturing, processing, distribution, retailing, transport, finance and investment.

Palgrave Macmillan Booth #6 www.palgrave.com

Palgrave Macmillan is proud to publish a unique crosssection of high-quality research work fundamental to understanding contemporary issues and developments in operations research and information technology. Our growing portfolio in this area includes the journals of the OR Society and the OR Essentials series.

Palisade Corporation Booth #53 www.palisade.com

Palisade Corporation is the maker of the market leading risk and decision analysis software @RISK and the DecisionTools® Suite. Virtually all Palisade software adds in to Microsoft Excel, ensuring flexibility, ease-of-use, and broad appeal across a wide range of industry sectors. Free trial downloads at www.palisade.com.

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Exhibit Hours

Sunday, Nov. 13, 12 p.m.-5 p.m. • Welcome Reception: 7:30 p.m.-9:30 p.m.

Monday, Nov. 14, 9 a.m.-5 p.m. • Tuesday, Nov. 15, 9 a.m.-5 p.m. • Wednesday, Nov. 16, 9 a.m.-3 p.m.

GUIDE TO EXHIBITORS, continued from p. 51 Princeton Consultants

SAS JMP Division

Booth #20 http://www.princeton.com

Booth #3 www.jmp.com

Founded in 1980, Princeton Consultants blends advanced analytics, data science, software development and management consulting to help industry leaders and fastgrowing innovators transform performance. Based on our track record of developing and implementing critical operational systems, we review and improve optimization and predictive analytics models through our quality assurance service. We are a member of the INFORMS Roundtable.

Provalis Research Booth #28 www.provalisresearch.com

Provalis Research is a leading developer of text analytics software with ground-breaking qualitative and quantitative analysis programs, such as QDA Miner, an innovative mixedmethods qualitative data analysis software; WordStat, a powerful add-on module for computer assisted content analysis and text mining; and Simstat, an easy yet powerful statistical software. One of the most distinctive features of these tools is their interoperability, allowing researchers to integrate numerical and textual data into a single project file and to seamlessly move back and forth between quantitative and qualitative data analysis, as well as to easily explore relationships between numerical and textual data.

Responsive Learning Technologies Booth #18 www.responsive.net

Responsive Learning Technologies provides compelling business simulations to teach Operations Management and Supply Chain Management in a dynamic context and adaptive self-study software to help students prepare for beginning a degree program. Our software has enriched courses at the undergraduate, graduate, and executive levels for thousands of students at hundreds of institutions in dozens of countries. Our products are developed with leading scholars, to achieve well-defined learning objectives.

Rensselaer Polytechnic Institute Booth #45 https://lallyschool.rpi.edu/

At the Lally School of Management at Rensselaer Polytechnic Institute in Troy, N.Y., we develop aspiring business leaders who have a passion for innovation with the ability to work across business functions. Our programs are built around innovation, technology, and entrepreneurship in the global economy.

The Lally School offers eight undergraduate concentrations including: Accounting, Business Analytics, Entrepreneurship, Finance, International Management, Management Information Systems, Marketing and Supply Chain Management. It also offers an MBA; M.S. degrees in business analytics, supply chain management, technology commercialization and entrepreneurship, quantitative finance and risk analytics or management; and a Ph.D. in management.

SAS Booth #1 & 2 www.sas.com

The effective use of analytics is more important than ever for today’s organizations. The most effective analytics are coordinated, and the best and most complete set of coordinated analytic capabilities comes from SAS. Data integration, statistics, data and text mining, econometrics and forecasting integrate deeply with operations research features like optimization, simulation and scheduling. SAS helps organizations around the world build analytic models, populate them with relevant data and insights, communicate recommended decisions effectively, and surface these capabilities within accessible, business-oriented interfaces.

See how SAS can help you understand the past and present, anticipate the future, and make better decisions.

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Taylor & Francis Booth #25 http://taylorandfrancis.com/

JMP® statistical discovery software from SAS is the tool of choice for scientists, engineers and other data explorers worldwide. JMP links dynamic data visualization with powerful statistics, in memory and on the desktop. Interactive and visual, JMP reveals insights that raw tables of numbers or static graphs tend to hide. JMP simplifies data access, cleanup and processing, and makes it easy to share results.

It includes comprehensive capabilities for: statistical analysis, design of experiments, multivariate analysis, quality and reliability analysis, scripting, graphing and charting, and more.

Taylor & Francis boasts a first-class journal portfolio publishing Manufacturing and Operational Engineering articles as well as a wide range of scholarship from related disciplines. Our journals are edited by some of the most prominent academics in the world and offer a variety of accommodating options for our authors. Our prominent journals include International Journal of Production Research, Production & Manufacturing Research: An Open Access Journal and INFOR: Information Systems and Operational Research.

SIAM

University of Illinois Department of Industrial and Enterprise Systems Engineering

Booth #44 www.siam.org

Visit the Society for Industrial and Applied Mathematics booth to check out our new publications, including recent titles in the MOS-SIAM Series on Optimization such as “MinimumVolume Ellipsoids: Theory and Algorithms” (Todd) and “Electrical Transmission System Cascades and Vulnerability: An Operations Research Viewpoint” (Bienstock), plus other bestselling SIAM books, all available at a conference discount.

You’ll also find sample issues of SIAM’s renowned journals, including SIOPT, along with information and applications for anyone interested in becoming a SIAM member. And don’t forget to pick up a copy of SIAM News for the road.

Simio Booth #41 www.simio.com

Simio Simulation and Scheduling Software is the most advanced solution on the market. With simulation, it is the only software that is fully object oriented with process and objects being defined graphically with no programming. Unlike other scheduling software, Simio allows you to introduce risk into your production schedule with its patented Risk-Based Planning and Scheduling. This dual function in Simio not only helps you improve your business performance from a facility design perspective, but also helps you maximize business results by optimizing the use of critical resources and assessing the risk associated with operational decisions.

SIMUL8 Booth #17 http://www.simul8.com/

Booth #50 http://ise.illinois.edu/

The Department of Industrial and Enterprise Systems Engineering at the University of Illinois, Urbana-Champaign, innovates the engineering discipline with leading-edge research and scientific discoveries; educates a new generation of leaders in systems, industrial and financial engineering; and serves education, industry and society.

University of Tennessee Knoxville – Department of Industrial & Systems Engineering Booth #22 http://ise.utk.edu/

Department of Industrial & Systems Engineering (ISE) at UTK offers graduates and scientific professionals a Master of Science (MS) degree, a MS in Reliability and Maintainability Engineering, a dual-degree option (MS and MBA), a Ph.D. degree with a major in IE and a concentration in Engineering Management. Located in the recently dedicated John D. Tickle Building, the ISE Department has about 163 undergraduate and 130 graduate students enrolled. The ISE department has been active in the research areas of Operations Research, Management Systems, Lean, Statistics and Human Factors with applications in manufacturing, healthcare, service, transportation, energy, finance, entertainment and logistics.

University of Tennessee Knoxville – Haslam College of Business Booth #31 http://haslam.utk.edu/

For over 20 years SIMUL8 Corporation has been producing powerful simulation software. SIMUL8’s Educational Software is used in universities worldwide and gives tutors the ability to teach simulation, not software, thanks to its intuitive interface.

When teaching simulation, the purpose is not for students to learn software; it’s to get them understanding the benefits that simulation can bring to decision-making.

SIMUL8 was created with this in mind and as a result our software allows students to build and run their first simulation in less than an hour and see the results.

The Haslam College of Business at the University of Tennessee, Knoxville, was founded in 1914 and consists of approximately 5,500 undergraduate and graduate students, 130 faculty members and 125 staff members. Our departments, centers, institutes, forums and graduate and executive education programs reach across the for-profit, not-for-profit and governmental sectors of business, with a heavy emphasis on practical research. From our top-notch supply chain management and highly regarded accounting programs to our renowned business analytics and Physician EMBA programs, Haslam students and faculty create the change that changes our world for the better.

Springer

Wiley

Booth #42 & 43 www.springer.com

Looking to publish your research? Discover Springer’s print and electronic publication services, including open access!

Get high-quality review, maximum readership and rapid distribution. Visit our booth or www.springer.com/authors.

You can also browse key titles in your field and buy (e)books at discount prices. With Springer you are in good company.

Booth #32 www.wiley.com

Wiley is a global provider of knowledge and knowledgeenabled services in areas of research, professional practice and education. We develop digital education, learning and assessment and certification tools, partner with societies, and support researchers to communicate discoveries. Our digital content, books and 1,600 online journals build on a 200-year heritage of quality publishing.

ormstoday.informs.org

ormstoday.informs.org

People James Franklin Sharp, chairman of Sharp Seminars in New York, was recently honored by the University of Illinois as a Distinguished Alumnus.

A 1959 industrial James Franklin Sharp engineering graduate at Illinois, Sharp is a member of the University of Illinois President’s Council and has established the annual Sharp Outstanding Teaching Award in Industrial Engineering, as well as the annual Sharp Outstanding Graduate Student Award in Industrial Engineering.

Sharp was previously named an Outstanding Alumnus at Perdue University, where he earned a master’s degree and a Ph.D. in industrial engineering. A member of Purdue President’s Council, Sharp established the Professor James H. Greene Outstanding Graduate Educator Award in Industrial Engineering at Purdue to honor his Ph.D. advisor.

Sharp went on to become an associate professor of quantitative methods at New York University’s Stern Graduate School of Business and a full professor of finance at Pace University’s Lubin Graduate School of Business, He also held management positions at AT&T. In 1986, Professor Sharp founded Sharp Seminars, which became a major provider of training to Wall Street analysts and portfolio managers.

A past president of the New York Chapter of TIMS (The Institute of Management Sciences, which eventually merged with the Operations Research Society of America to created INFORMS), Sharp has published many papers in leading journals, including Management Science. He has also written 36 books involving statistics, economics, accounting, corporate finance, stock analysis, bond analysis, options and futures analysis, real estate and private equity analysis, portfolio management and ethics.

A team led by Hui Yang of Penn State University received $299,954 in funding from the National Science Foundation (NSF) for research focused on improving Hui Yang healthcare delivery to patients who have had cardiac surgery. Yang, the Harold and Inge Marcus Career Associate Professor of Industrial Engineering in the Department of Industrial and Manufacturing, is one of three researchers on the collaborative two-year project titled, “Sensing, Modeling and Optimization of Postoperative Heart Health Management.”

According to the American Heart Association, heart disease affects more than 83.6 million Americans – which is approximately 35.3 percent of the U.S. population – and costs the United States $448.5 billion annually. Of those affected with heart disease, around 51.4 million patients undergo in-patient heart procedures each year in this country.

“Postoperative care is critical to the quality of life of these patients,” Yang said.

“However, once they are discharged from the hospital, there are currently few sensing and decision-support systems that extend to their homes, workplaces and communities, which increases the chance of another cardiac event occurring.”

The goal of the research is to develop a collaborative sensing, statistical modeling and decision-making strategy to optimize postoperative cardiac care to these patients. The research will be collaboratively pursued by faculty and students at Penn State and Texas Tech University, as well as clinicians at the James A. Haley Veterans’ Hospital. The team includes Dongping Du of Texas Tech and Fabio Leonelli from the James A. Haley Veterans’ Hospital, along with industrial engineering graduate students Yao Bing, Chen Kan, Pei Shenli and Matenga Zvikomborero.

INFORMS Fellow Bob Bordley has accepted a 25 percent appointment as program director for the University of Michigan’s master ’s degree program in Systems Engineering and Bob Bordley Design. In addition to teaching responsibilities at the university, Bordley continues to work at Booz-Allen-Hamilton (a member of the INFORMS Roundtable).

Bordley is a retiree from General Motors Corporation (another Roundtable member), where he was part of Project Trilby, a task force charged with introducing systems engineering into vehicle design. Bordley also worked at the National Science Foundation as program director of Decision, Risk and Management Sciences (along with former INFORMS President Robin Keller). Bordley has a Ph.D. in industrial engineering and operations research from the University of California, Berkeley.

Douglas A. Samuelson, president and chief scientist of InfoLogix, Inc., was appointed to the Board of the Health Services Agency of Northern Virginia, a private non-profit Douglas A. Samuelson group that advises the state government about whether to permit establishment or expansion of certain regulated healthcare facilities.

In other news, Samuelson made a guest contribution to a recently released book by Douglas W. Hubbard and Richard Seiersen, “How to Measure Anything in Cybersecurity Risk” (Wiley).

Samuelson’s essay outlines new methods for cyber-counterintelligence, a topic he also writes about in this issue of OR/MS Today and in a recent issue of Analytics magazine. ORMS October 2016

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n ews 2017 INFORMS election results The following individuals were elected to serve on the INFORMS Board beginning Jan. 1, 2017:

President-Elect Nicholas Hall

Treasurer

Meetings

INFORMS Annual & International Meetings Nov. 13-16, 2016

July 26-July 28

INFORMS Annual Meeting

INFORMS 2017 Healthcare Conference

Music City Center & Omni Nashville Nashville, Tenn.

Chair: Chanaka Edirisinghe, RPI http://meetings.informs.org/nashville2016

De Doelen International Congress Centre Rotterdam, the Netherlands Chair: Joris van de Klundert, Erasmus University Rotterdam http://meetings2.informs.org/wordpress/healthcare2017/

April 2-4, 2017

Oct. 22-25, 2017

INFORMS Conference on Business Analytics & Operations Research

INFORMS Annual Meeting

Caesars Palace, Las Vegas Las Vegas, Nevada Chair: Maher Lahmar, Science Solutions & Walmart http://meetings2.informs.org/wordpress/analytics2017/

Michael Fu

Vice President-Education Jill Hardin Wilson

Vice PresidentInformation Technology Marco Lübbecke

Vice President-Meetings Ron Askin

Vice President-Publications Jonathan Bard

Go to www.informs.org/Conf for a searchable INFORMS Conference Calendar.

George R. Brown Convention Center & Hilton Americas Houston, Texas Chair: William Klimack, Chevron

INFORMS Community Meetings Dec. 11-14, 2016

June 8-10

Winter Simulation Conference

INFORMS Marketing Science Conference

Crystal Gateway Marriott Arlington, Va. Chair: Todd Huschka, Mayo Clinic http://meetings.informs.org/wordpress/wintersim2016/

University of Southern California, Los Angeles Los Angeles

Jan. 15-17, 2017

INFORMS Computing Science Conference Westin Austin at the Domain Austin, Texas Chair: Neil Dimitrov, UT- Austin https://ie.clemson.edu/ics2017/

Feb. 2-5

INFORMS College on Organization Science Grand Summit Hotel, Canyons Resort Park City, Utah Chair: Mary Zellmer-Bruhn, University of Minnesota http://pubsonline.informs.org/page/orsc/winter-conference

June 29-30

INFORMS Revenue Management & Pricing Section Conference Centrum Wiskunde & Informatica (CWI) Amsterdam https://www.informs.org/Community/revenue-mgt/ Conferences

July 10-12

INFORMS 19th Applied Probability Conference Northwestern University Evanston, Ill.

Industry News Frontline Systems launches AnalyticSolver.com Frontline Systems, developer of the Solver in desktop Microsoft Excel, has released AnalyticSolver.com, a SaaS (software as a service) Azure-based platform that offers business analysts point-and-click tools to create predictive and prescriptive analytics models themselves, without needing expert data scientists or programmers – yet taking advantage of the full spectrum of analytic methods, from forecasting and data mining to simulation and optimization.

Though brand new in its first release, AnalyticSolver.com inherits both the power of Frontline’s full analytics product line and ease of use from more than 25 years’ experience supporting business analysts using 54 | ORMS Today

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these methods in practice. Unlike most optimization and simulation vendors who are still desktop based, Frontline now offers full-power prescriptive analytics in the cloud, with an interface that’s familiar and immediately usable by Excel users, including generations of MBA students. Frontline has also released Analytic Solver Platform V2016-R3, a new version of its analytics tools for desktop Excel, to complement AnalyticSolver.com. For more information, visit http://www.solver.com.

AIMMS recognized by Gartner for analytics, network design AIMMS, a leading vendor of prescriptive analytics software, is pleased to announce that it has been named in Gartner’s report,“Hype

Cycle for Chief Supply Chain Officers, 2016.”The company is listed in the report as a sample vendor in the areas of prescriptive analytics and network design.

According to Gartner, in order to thrive in this fast-paced business environment, organizations need to “build a successful bimodal supply chain, chief supply chain officers must balance operational excellence with disruptive innovation.” The report provides an overview of the critical technologies, business frameworks and competencies supply chain leaders need to achieve this. AIMMS can be leveraged to build several of these competencies, including prescriptive analytics capabilities and network design. For more information, visit http://aimms.com/. ORMS ormstoday.informs.org

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Quickly identify and target those critical areas that will have the greatest impact on improved performance. Frontier Analyst® 4 adds new data envelopment analysis (DEA) models, sideby-side comparisons and more visualization tools to allow you to undertake an objective and integrated assessment of performance and develop strategies to counter identified weaknesses.

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The SMART Scholarship for Service Program

Distribution Fitting Software

Logical Decisions® for Windows™ Version 7.2

Stat::Fit ® sta tistically fits analytical distributions to user data. Version 3 is faster, includes new graphics capabilities and has a new, more intuitive user interface.

It continues to have 32 distributions for fitting. The AutoFit function automatically fits continuous and discrete distributions, provides relative comparison between distribution types, and gives an absolute measure of each distribution’s acceptability. The Export function translates the fitted distribution into specific forms for simulation software. The distribution viewer allows interactive display of distributions, providing for quick no-data representations. Additional features include descriptive statistics, parameter estimates, goodness of fit tests, graphical analysis, random variate generation and more.

Logical Decisions®, Version 7.2 helps you evaluate choices requiring critical preference and value judgments. It lets you combine qualitative and quantitative concerns in a single model. It also lets you simultaneously consider many variables, separate facts from value judgments and explain your choice to others. Logical Decisions is the most powerful alternatives evaluation software available. It comes in individual, portfolio, and group versions, including a LAN-based version for groups. Logical Decisions Portfolio is a sophisticated tool for budget and resource constrained decisions. Version 7.2 includes brainstorming and a facilitator to help navigate the software. You can buy Logical Decisions online at www.logicaldecisions.com.

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Reserve Your Space Today!

Your Logo Here DEA SolverPro has been widely used all over the world. In response to numerous customer requests, we have released Version 13 with “SBM Max.”

Showcase your product or service with a 70-word description, image and contact information for an incredibly reasonable cost!

On top of more than 186 models in 48 clusters, Version 13 added a new model, called SBM Max, replacing SBM Variations released earlier.

The basic slacks-based measure models (SBM) usually report the worst efficiency scores for inefficient DMUs, i.e. the projected point is the farthest one on the associated efficient frontier. In contrast, SBM Max looks for the nearest point on the associated efficient frontier. Hence, the efficiency score is approximately maximized as contrasted to the ordinary SBM models. This KAIZEN model will open the door to the QC community.

The SMART Scholarship for Service Program is an opportunity for students pursuing a Science, Technology, Engineering, and Mathematics (STEM) focused degree to receive a scholarship and employment after graduation as a civilian scientist or engineer at a Department of Defense facility. Scholarships awarded include a stipend up to $38,000 a year, full tuition, health insurance contribution, and miscellaneous supplies allowance.

Note network or floating licenses are available for multi-user or multi-machine options. Visit our website for pricing and ordering information.

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TO RESERVE YOUR SPACE IN APRIL 2017, CONTACT: Sharon Baker, Advertising Sales Lionheart Publishing, Inc. Phone: 813.852.9942 Email: sharon.baker@mail.informs.org or Aileen Kronke, Advertising Sales Lionheart Publishing, Inc. Phone: 888.303.5639, Ext. 212 Fax: 770.432.6969 Email: aileen@lionhrtpub.com

P. O. Box 431 Holmdel, NJ 07733, U.S.A. Phone: (732) 410-9192 Fax: (732) 444-5911 email: dea@saitech-inc.com URL: www.saitech-inc.com

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CLASSIFIEDS

SPECIAL ADVERTISING SECTION | View Classifieds Online at: http://www.orms-today.org

Operations and Supply 1617-007 Assistant Professor - Business Analytics EFFECTIVE DATE: Fall 2017

MINIMUM QUALIFICATIONS: Ph.D. or equivalent in Business Analytics, Data Sciences, Operations Research, Management Sciences, Operations Management or a related discipline. Candidates must demonstrate teaching excellence, a record of published research commensurate with years of experience, and the ability to develop and sustain a research program that will lead to original, peer-reviewed publications. Candidates must be able to communicate effectively and work cooperatively with departmental colleagues and an ethnically and culturally diverse campus community.

DESIRED/PREFERRED QUALIFICATIONS: Preference will be given to applicants with business and or teaching experience in Business Analytics and Big Data Analytics, the ability to deliver applied learning experiences, and the competence to teach current topics and technologies for developing and implementing business intelligence program. Preference will be given to applicants with demonstrated intercultural competence with diverse groups in teaching, research and/or service.

DUTIES: The new faculty member is expected to teach one or more core undergraduate courses (Business Statistics, Data Analysis, Introduction to Data Analytics, Introduction to Business Analytics) and one or more MBA courses (Business Intelligence and Statistics for Management). Integration of Business Analytics into the curriculum is a priority goal of the Operations and Supply Chain Management department and the successful candidate will support and contribute to this goal by developing and teaching new courses in the area of Business Analytics and Supply Chain Management such as Data and Text Mining, Big Data and Business Intelligence, Big Data Analytics in Supply Chain Management. The new faculty member will also be expected to sustain quality research, publish in peer-reviewed journals, and actively engage in activities serving the department, college, university and community.

APPLICATION (must include): • Cover letter indicating how the applicant meets the above minimum/desired/preferred qualifications • Curriculum vitae • Statement of teaching philosophy • Reprints of representative publications • If available, copies of student teaching evaluations • Three current letters of recommendation • Copies of all transcripts that include relevant course work • Faculty Application Submit application materials and direct any inquiries to: OSCM1617@csusm.edu Request for information should be addressed to: Search Committee Chair- Operations and Supply Chain Management Department Soheila Jorjani, sjorjani@csusm.edu Review of applications will begin on November 1, 2016 and continue until the position is filled. Early response is encouraged.

The University is particularly interested in applicants who have experience working with students from diverse backgrounds and a demonstrated commitment to improving access to higher education for under-represented groups.

This position is subject to employment verification, education verification, reference checks and criminal record checks. A background check (including the criminal records check) must be completed satisfactorily before any candidate can be offered a position with the CSU. Failure to satisfactorily complete the background check may affect the application status of applicants or continued employment of current CSU employees who apply for the position.

CSUSM has been designated as a Hispanic Serving Institution (HSI) and an Asian American Native American Pacific Islander Serving Institution (AANAPISI) and was recently named one of the top 32 Colleges most friendly to junior faculty by the Collaborative on Academic Careers in Higher Education.

Visit http://www.csusm.edu/facultyopportunities for more information.

California State University San Marcos is an Affirmative Action/Equal Opportunity Employer strongly committed to equity and diversity and seeks a broad spectrum of applicants in terms of race, color, religion, ancestry, national origin, sex, sexual orientation, gender identity, gender expression, age, disability and veteran status.

The Computing and Mathematical Sciences (CMS) department at the California Institute of Technology (Caltech) invites applications for tenure-track or tenured faculty positions. CMS is a unique environment where innovative, interdisciplinary, and foundational research is conducted in a collegial atmosphere. Candidates in all areas of computing and mathematical sciences are invited to apply, including (but not limited to) learning and computational statistics, security and privacy, networked and distributed systems, optimization and computational mathematics, control and dynamical systems, theory of computation and algorithmic economics, scientific computing, etc. Additionally, we are seeking candidates who have demonstrated strong connections to other fields, including the mathematical, physical, biological, and social sciences.

A commitment to world class research, high-quality teaching, and mentoring is expected. The initial appointment at the Assistant-Professor level is for four years and is contingent upon the completion of a Ph.D. degree in Computer Science, Applied Mathematics or related field.

Applicants are encouraged to have all their application materials on file by October 21st, 2016, but applications will be accepted until the end of December. For a list of documents required and full instructions on how to apply on-line, please visit http://www.cms.caltech.edu/search.

Seeking 3 Open Rank positions to include the: Jerry S. Dobrovolny Chair in Systems Engineering and Design ($2M endowed chair)

The Department of Industrial and Enterprise Systems Engineering at the University of Illinois at UrbanaChampaign invites applications for at least three fulltime open-rank faculty positions in the areas of:

• Systems Engineering and Design - This position is • • • •

supported by a $2M endowment.

Healthcare Systems Engineering and Cognitive Engineering (especially Aging Populations) Controls/Optimization/Operations Research Internet of Things/Analytics/Big Data Physical Ergonomics/Biomechanics

Successful candidates are expected to direct graduate students in research, teach in the undergraduate and graduate programs, and develop a strong externallyfunded research program in the area of systems engineering and design. Salary will be commensurate with qualifications and experience. Candidates must have a PhD in Industrial Engineering, Systems Engineering, Mechanical Engineering, or a closely related discipline.

For complete position announcement and application instructions, see http://jobs.illinois.edu. Review of applications will be ongoing, and will continue until the position is filled. The proposed start date is August 16, 2017. Questions should be referred to Shawna Graddy, sgraddy@illinois.edu, (217) 244-8788.

The University of Illinois conducts criminal background checks on all job candidates upon acceptance of a contingent offer. Illinois is a EEO Employer/Vet/ Disabled (www.inclusiveillinois.illinois.edu) and committed to a family-friendly environment (http://provost.illinois.edu/worklife/index.html).

Questions about the application process may be directed to: search@cms.caltech.edu.

Caltech is an Equal Opportunity/Affirmative Action Employer.

Women, minorities, veterans, and disabled persons are encouraged to apply.

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ormstoday.informs.org

SPECIAL ADVERTISING SECTION | View Classifieds Online at: http://www.orms-today.org

CLASSIFIEDS

FACULTY POSITIONS Business - Marketing Department of Operations Information and Decision The Wharton School UNIVERSITY OF PENNSYLVANIA The Operations, Information and Decisions Department at the Wharton School is home to faculty with a diverse set of interests in behavioral economics, decision-making, information technology, information-based strategy, operations management, and operations research. We are seeking applicants for a full-time, tenure-track faculty position at any level: Assistant, Associate, or Full Professor. Applicants must have a Ph.D. (expected completion by June 2017 is preferred but by June 30, 2018 is acceptable) from an accredited institution and have an outstanding research record or potential in the OID Department’s areas of research. The appointment is expected to begin July 1, 2017.

More information about the Department is available at: https://oid.wharton.upenn.edu/index.cfm Interested individuals should complete and submit an online application via our secure website, and must include: • A curriculum vitae • A job market paper • (Applicants for an Assistant Professor position) Three letters of recommendation submitted by references To apply, please visit this web site: https://oid.wharton.upenn.edu/faculty/faculty-recruiting/ Further materials, including (additional) papers and letters of recommendation, will be requested as needed.

To ensure full consideration, materials should be received by November 1st, 2016.

Contact: OID Department The Wharton School University of Pennsylvania 3730 Walnut Street 500 Jon M. Huntsman Hall Philadelphia, PA 19104-6340 The University of Pennsylvania is an affirmative action/equal opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.

NYU SHANGHAI NYU Shanghai is seeking to fill tenure-track or tenure positions in the field of Marketing, beginning in the Fall Semester of 2017. Positions are available at all ranks: Assistant Professor, Associate Professor and Full Professor.

The terms of employment tenure-track or tenure Business faculty positions in NYU Shanghai are comparable to NYU Stern in terms of compensation and research funds, and include housing subsidies and educational subsidies for children. Faculty may also spend time at NYU New York and other sites of the NYU global network, engaging in both research and teaching.

Applications are due no later than January 20, 2017. The review of applications will begin immediately, and will continue until the positions are filled . To be considered, applicants should submit a curriculum vitae, separate statements of research and teaching interests (no more than three pages each), and electronic copies of representative publications. To complete the online process, applicants will be prompted to enter the names and email addresses of three referees. Each referee will be contacted to upload their reference letter. Please visit our website at ht t p://shanghai . nyu .edu/en/a bout/work- here/open - positions- faculty for instructions and other information on how to apply. If you have any questions, please e-mail shanghai.faculty.recruitment@nyu.edu.

About NYU Shanghai: NYU Shanghai is the newest degree-granting campus within New York University’s global network. It is the first higher education joint venture in China authorized to grant degrees that are accredited in the U.S. as well as in China. All teaching is conducted in English. A research university with liberal arts and science at its core, it resides in one of the world’s great cities with a vibrant intellectual community. NYU Shanghai recruits scholars of the highest caliber who are committed to NYU’s global vision of transformative teaching and innovative research and who embody the global society in which we live.

NYU’s global network includes degree-granting campuses in New York, Shanghai, and Abu Dhabi, complemented by eleven additional academic centers across five continents. Faculty and students circulate within the network in pursuit of common research interests and cross-cultural, interdisciplinary endeavors, both local and global.

NYU Shanghai is an equal opportunity employer committed to equity, diversity and social inclusion. We strongly encourage applications from individuals who are underrepresented in the profession, across color, creed, race, ethnic and national origin, physical ability, and gender and sexual identity. NYU Shanghai affirms the value of differing perspectives on the world as we strive to build the strongest possible university with the widest reach.

EOE/AA/Minorities/Females/Vet/Disabled/Sexual Orientation/Gender Identity Employer

THE HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY Faculty Positions in the Department of Industrial Engineering and Logistics Management (Job ID: 3074)

Carnegie Mellon University: Tepper School of Business TENURE TRACK POSITION IN BUSINESS TECHNOLOGY / BUSINESS ANALYTICS

The Department of Industrial Engineering and Logistics Management at the Hong Kong University of Science and Technology (HKUST) invites applications for substantiation-track faculty positions at all levels of Professor, Associate Professor and Assistant Professor. Candidates should have a PhD degree in Industrial Engineering, Operations Research, or a closely related area, and demonstrated strong potential for excellent teaching and research in the area of Operations Management and Logistics Management.

The Tepper School of Business at Carnegie Mellon University invites applicants for a tenure-track position as an Assistant Professor in Business Analytics to begin in September 2017. The ideal candidate will play an important role in advancing the school's analytical approach to business, which is a long-standing differentiator of the Tepper School’s approach to business education and research. We are looking for candidates who can explore and solve business problems using quantitative methods utilizing big data or unstructured information. We are especially interested in those candidates who apply machine learning (e.g., natural language processing, computer vision, deep learning, and artificial intelligence) and causal inference (e.g., econometrics, structural modeling, observational studies, and experiments) to business applications. The ideal candidate will conduct innovative research in topics including, but not limited to: ecommerce, mobile marketing, social media, digital advertising, the Sharing Economy, crowdsourcing or solving business problems through new technologies.

HKUST is an international university in a world city, Hong Kong, and has been consistently ranked among the world’s top 30 in the field of Engineering and Technology for the past 6 years in a row by the Times Higher Education World University Rankings and QS World University Rankings. The Department has made notable strides and received international recognition. We have a strong group of researchers specializing in logistics & operations management, and design, manufacturing & quality. Located at the gateway to Mainland China and the most dynamic logistics hub of Asia, the Department is expected to experience rapid growth.

More information about the Department can be found at http://www.ielm.ust.hk.

Starting salary will be commensurate with qualifications and experience. Fringe benefits including annual leave, medical and dental benefits will be provided.

Housing benefits will also be provided where applicable. Initial appointment for Assistant Professor/ Associate Professor will normally be on a three-year contract, renewable subject to mutual agreement. A gratuity will be payable upon successful completion of contract.

Application Procedure Applications with a full C.V., statement of research and teaching, transcript of graduate work, copies of 2 research publications, names, emails and addresses of at least three referees, should be directed to the Faculty Search Committee, Department of Industrial Engineering and Logistics Management, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong [email : ielm@ust.hk]. Review of applications will start immediately and continue until the positions are filled.

(Information provided by applicants will be used for recruitment and other employment-related purposes.)

Applicants are expected to have a doctoral degree at the time of appointment in Information Systems, Computer Science, Marketing, Statistics, or related fields. The appointee will be part of the Business Technology group. The Tepper School of Business and Carnegie Mellon University have a strong culture of collaboration across disciplines. This open environment provides unique opportunities for highly innovative work and interdisciplinary work is encouraged.

Carnegie Mellon University seeks to meet the needs of dual-career couples and is a member of the Higher Education Recruitment Consortium (HERC) that assists with dual-career searches.

Applicants should submit an application letter, vita, three publications or unpublished research papers, research and teaching statements, and three recommendation letters. If you have any questions about the application please contact Mr. Philip Conley at isgroup@andrew.cmu.edu or 412-268-6212.

To receive full consideration, applications must be submitted by November 1, 2016.

APPLICATION PROCEDURE: Faculty applications and all supporting documents must be submitted to: https://apply.interfolio.com/37175 Carnegie Mellon University is an equal opportunity employer and is committed to increasing the diversity of its community on a range of intellectual and cultural dimensions. Carnegie Mellon welcomes faculty applicants who will contribute to this diversity through their research, teaching and service, including women, members of minority groups, protected veterans, individuals with disabilities, and others who would contribute in different ways.

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SPECIAL ADVERTISING SECTION | View Classifieds Online at: http://www.orms-today.org

THE UNIVERSITY OF TEXAS AT DALLAS The Naveen Jindal School of Management

OPERATIONS MANAGEMENT Faculty Positions Ningbo Supply Chain Innovation Institute China Ningbo, China

We are pleased to announce the opening of the sixth center within MIT’s Global Supply Chain and Logistics Excellence (SCALE) Network in China.

The newly created Ningbo Supply Chain Innovation Institute China (NSIIC) will be joining the existing centers within the SCALE Network: the MIT Center for Transportation & Logistics or MIT CTL (Cambridge, MA, USA), the Zaragoza Logistics Center or ZLC (Zaragoza, Spain), the Center for Latin-America Logistics Innovation or CLI (Bogota, Colombia), the Malaysia Institute for Supply Chain Innovation or MISI (Shah Alam, Malaysia), and the Luxembourg Centre for Logistics or LCL (Luxembourg City, Luxembourg).

Together, this network of centers educates hundreds of masters students, doctoral candidates, and executives each year.

We are recruiting for multiple faculty positions at all levels (Senior, Associate, and Assistant Professor) to support research activities in the area of transportation, logistics and supply chain management.

For more information and directions on submitting an application for these positions, please visit: https://academicjobsonline.org/ajo/SCM

OPEN RANK FACULTY POSITION a tenure-track faculty position in Operations Management, beginning in Fall 2017. The position is open rank. All areas of research in Operations Management will be considered.

All candidates must have earned a Doctorate degree prior to the beginning of the Fall 2017 term. UTD’s rapidly growing OM department is well recognized in research. It offers programs and degrees at all levels, including Ph.D. The OM faculty and students are also involved in industry projects sponsored by our Center for Intelligent Supply Networks.

Applicants should submit an application, curriculum vitae, other documents (research interests, teaching philosophy, teaching and student evaluations) and at least three letters of reference online at http://jobs.utdallas.edu/postings/6318.

Review of application material will commence on October search is closed.

Action employer and strongly encourages applications from candidates who would enhance the diversity of the University’s faculty and administration.

APPLICATIONS INVITED FOR FACULTY POSITIONS IN INDUSTRIAL ENGINEERING AND MANAGEMENT SCIENCES Faculty Position #051186 in Information Technology and Operations Management

SMU’s Cox School of Business invites applications for a full-time faculty position in Information Technology and Operations Management (ITOM). The ideal candidate must possess strong quantitative/analytical skills and a Ph.D. in information systems or a related field. While an appointment at the rank of Assistant Professor, is anticipated, extraordinary candidates at all levels will be considered. The ITOM Department offers courses in the School’s BBA, MBA, MS and EMBA programs. The position begins Fall 2017.

The Cox School is a nationally ranked business school located in Dallas, Texas, the premier business center in the US Southwest. The ITOM department has a well-respected research faculty and excellent relations with the corporate and business community, providing a unique and exciting environment for high-quality research. The School offers a collegial working environment, generous faculty support and outstanding facilities. The Dallas Fort-Worth (DFW) Metroplex offers a thriving business community in one of the fastest-growing regions of the country, a relatively low cost of living and myriad cultural and recreational activities and resources. Information about the School can be found at http://www.smu.edu/cox.

Priority will be given to applications received by October 15, 2016, although the search committee will continue to accept applications until the position is filled. The ITOM faculty will be conducting initial interviews at the INFORMS National Meeting in Nashville, TN in November 2016, and the International Conference on Information Systems (ICIS) in Dublin, Ireland, in December 2016.

Applications must be submitted electronically to https://apply.interfolio.com/35112 SMU will not discriminate in any program or activity on the basis of race, color, religion, national origin, sex, age, disability, genetic information, veteran status, sexual orientation, or gender identity and expression. The Executive Director for Access and Equity/Title IX Coordinator is designated to handle inquiries regarding nondiscrimination policies and may be reached at the Perkins Administration Building, Room 204, 6425 Boaz Lane, Dallas, TX 75205, 214-768-3601, accessequity@smu.edu.

SMU is an Affirmative Action/Equal Opportunity Institution

The Industrial Engineering and Management Sciences Department at Northwestern University invites applications and nominations for two faculty positions beginning September, 2017. The positions are at the Assistant Professor or Associate Professor level. The searches are broad, with a preference for candidates in the following two areas: (1) computational statistics and (2) production, logistics, or healthcare. A strong commitment to rigorous and relevant research is essential.

The hires would have opportunities for interdisciplinary collaboration via broad University research initiatives in Optimization and Statistical Learning (www.osl.northwestern.edu), Engineering and Healthcare (www.ceh.northwestern.edu), and Transportation and Logistics (www.transportation.northwestern.edu).

The IEMS Department offers an undergraduate program, a Ph.D. program, a full-time professional master’s degree in analytics and a part-time professional master’s degree in engineering management. Both the undergraduate and graduate programs have been consistently ranked among the top ten by US News & World Report.

Submit application electronically at www.mccormick.northwestern.edu/industrial/career/.

Materials to be uploaded include a cover letter and a curriculum vitae detailing educational background, research and work experience. Applicants at the assistant professor level should also include one research paper and a statement of their current and future research program.

Candidates will be asked to provide contact information for three references on the application site. To receive full consideration, all materials should be received by October 15, 2016; earlier application is encouraged.

Chair, Faculty Recruiting Committee Department of Industrial Engineering and Management Sciences Northwestern University 2145 Sheridan Road, Room C210 Evanston, IL 60208-3119 facultysearch@iems.northwestern.edu Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes, including veterans and individuals with disabilities. Women, underrepresented racial and ethnic minorities, individuals with disabilities, and veterans are encouraged to apply.

Hiring is contingent upon eligibility to work in the United States.

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MULTIPLE FACULTY POSITIONS Department of Electrical and Systems Engineering The School of Engineering and Applied Science at the University of Pennsylvania is growing its faculty by 33% over the next five years. As part of this initiative, the Department of Electrical and Systems Engineering is engaged in an aggressive, multi-year hiring effort for multiple tenure-track positions at all levels. Candidates must hold a Ph.D. in Electrical Engineering, Systems Engineering, or related area. The department seeks individuals with exceptional promise for, or proven record of, research achievement, who will take a position of international leadership in defining their field of study, and excel in undergraduate and graduate education. Leadership in cross-disciplinary and multi-disciplinary collaborations is of particular interest. We are interested in candidates in all areas that enhance our research strengths in 1. Nanodevices and nanosystems (nanoelectronics, MEMS/NEMS, power electronics, nanophotonics, integrated devices and systems at nanoscale), 2. Circuits and computer engineering (analog, RF, mm-wave, and digital circuits, emerging circuit design, computer engineering, IoT, embedded and cyber-physical systems), and 3. Information and decision systems (control, optimization, robotics, data science, network science, communications, information theory, signal processing, markets and social systems).

Prospective candidates in all areas are strongly encouraged to address large-scale societal problems in energy, transportation, health, food and water, economic and financial networks, critical infrastructure, and national security. We are especially interested in candidates whose interests are aligned withthe schoolâ&#x20AC;&#x2122;s strategic plan(www.seas.upenn.edu/PennEngineering2020).

Diversity candidates are strongly encouraged to apply. Interested persons should submit an online application at http://www.ese.upenn.edu/faculty-positions and include curriculum vitae, statement of research and teaching interests, and at least three references. Review of applications will begin on December 1, 2016.

The University of Pennsylvania is an Equal Opportunity Employer. Minorities/Women/Individuals with Disabilities/Veterans are encouraged to apply.

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SPECIAL ADVERTISING SECTION | View Classifieds Online at: http://www.orms-today.org

VACANCY ANNOUNCEMENT The Logistics & Operations Management (LOM) Department in the College of Business Administration at the University of Missouri-St. Louis is seeking two full-time tenure-track Associate/Assistant Professors for Fall 2017.

Applicants are expected to have research and teaching interests in supply chain management, logistics, operations management, operations research, and/or business analytics. The position requires strong research potential and a commitment to teaching. Applicants should also be interested in building academic strength in the department, collaborating on research grants, and active involvement in our doctoral program in Logistics & Supply Chain Management.

Individuals who expect to have a completed doctoral degree (in Supply Chain Management, Operations Management, Operations Research, or another related field) by August 2017 are encouraged to apply. Applicants at the Associate Professor level are expected to play a leadership role in the department and the College’s doctoral program.

The University of Missouri-St. Louis is an urban public research university located in suburban St. Louis. It is part of the four-campus University of Missouri System and is located in Missouri’s most economically vibrant region. The College of Business Administration is accredited by AACSB and provides a supportive environment for teaching, research, and service. Active researchers enjoy reduced teaching loads. The LOM department teaches courses at the undergraduate and master’s levels, and houses the College’s doctoral program. The College’s Center for Business and Industrial Studies and Center for Transportation Studies generate applied research projects.

Further information about the LOM department and its activities can be found in http://www.umsl.edu/divisions/business/ms/.

St. Louis is a major metropolitan area with a population of almost 3 million, which features a large variety of cultural and recreational activities and moderate living costs. Many significant companies are based in St. Louis, providing numerous opportunities for applied research and interactions with business. The Department’s Advisory Board consists of leading global and local firms, including Anheuser-Busch InBev, BJC HealthCare, Graybar, Unyson Logistics, Ameren Corporation, Unigroup Logistics, Nidec Motor Corporation and World Wide Technology Inc. Interested individuals should apply online at www.UMSL.jobs (job opening ID#20705). Applicants should include a letter of interest, curriculum vita, one research paper (i.e. publication, presentation or working paper), three references (names and contact information), and teaching evaluations. The application should address the courses and research activities that define the candidate’s area(s) of expertise and teaching interests. Review of applications will begin on September 1, 2016 and continue until the position is filled. Initial interviews with candidates will be scheduled for the CSCMP and INFORMS Annual Meetings in Fall 2016, or via Skype.

The University of Missouri is an affirmative action, equal employment opportunity employer committed to excellence through diversity. Women and minorities are encouraged to apply. This position requires commitment to working with diverse student and community populations. A background check and permission to work in the US are required for employment.

An equal opportunity institution

College of Business: Tenure Track Professor and Head of Department of Business Administration (F1600059) THE UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN College of Business

HEAD OF THE DEPARTMENT OF BUSINESS ADMINISTRATION Nominations and applications are invited for a full-time tenure track position for the Headship of the Department of Business Administration in the College of Business at the University of Illinois at Urbana-Champaign. The candidate must possess an earned doctorate or equivalent and should give evidence of demonstrated excellence in research, teaching, and service sufficient to merit the rank of full professor in the Department. Preference will be given to a person who shows promise to provide strong and effective academic leadership for the Department. The candidate should be able to lead a diverse, multi-disciplinary group of faculty and students. The candidate should also be capable of constructive and successful interaction with business organizations and other external groups to generate resources for the Department. As Department Head, he or she is responsible for academic, administrative and budgetary matters as well as effective liaison within the College and University.

The Department of Business Administration at UIUC is a major teaching and research unit located within the College of Business, which also contains the Departments of Accountancy and Finance. The Department of Business Administration has approximately 50 full-time faculty and offers undergraduate, professional, and doctoral programs. It includes the areas of marketing, operations management, organizational behavior, strategic management and entrepreneurship, international business and business law, and information systems.

Salary is competitive. The position is available August 16, 2017 or negotiable after close date. To receive full consideration, applications and supplemental materials must be submitted online at https://jobs.illinois.edu/ by December 31, 2016. Applicants may be interviewed before the closing date; however, no hiring decision will be made until after that date. Application materials must include a letter of intent, curriculum vitae, and list of three references. For further information regarding application procedures, contact Rebecca Heid heid@illinois.edu or (217) 333-9396.

For further information in regard to the Department of Business Administration, please visit the department website at https://business.illinois.edu/ba/.

The University of Illinois conducts criminal background checks and other required pre-employment assessments on all job candidates upon acceptance of a contingent offer.

Illinois is an equal opportunity employer which includes statuses of protected veterans and qualified individuals with disabilities (www.diversity.illinois.edu/chancellorscstmt.html). Illinois welcomes individuals with diverse backgrounds, experience, and ideas who embrace and value diversity and inclusivity. (www.inclusiveillinois.illinois.edu).

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UNIVERSITY OF WASHINGTON FOSTER SCHOOL OF BUSINESS FACULTY POSITION IN INFORMATION SYSTEMS The Information Systems and Operations Management (ISOM) Department in the University of Washington Foster School of Business invites applications for a full-time (100% FTE) tenure eligible faculty position at the Assistant (0116) Professor level in the Information Systems area. This is a 9 month appointment of indefinite length.

The Information Systems area is part of the ISO M Department, which offers courses in Information Systems, Operations Management, and Quantitative Methods in the School's undergraduate, MBA (including Executive MBA), MSIS, MSCM and Ph.D. programs. University of Washington faculty engage in teaching, research and service. Duties include teaching at all levels and research leading to publication in leading academic journals. Our faculty enjoy close ties with the local business community as well as other departments at the University of Washington, one of the leading public universities in the nation.

Applicants must either possess a doctorate in Information Systems or a related field by the date of appointment or will be hired in an acting title for up to one year. Applicants interested in applying should submit a detailed curriculum vita, research papers and publications, information about teaching experience and performance, and the names and contact information of at least 3 references at https://academicjobsonline.org/ajo/jobs/7593. Applications must be received by November 1, 2016.

For further inquiries, contact the committee chair, Professor Yong Tan (ytan@uw.edu).

The University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to, race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, protected veterans or disable status, or genetic information.

CASE WESTERN RESERVE UNIVERSITY

Weatherhead School of Management Non-tenure Track or Visiting Faculty Position in Operations The Department of Operations invites applicants for a non-tenure-track position of Assistant Professor of Operations or a one year Visiting Faculty position to begin August 2017. We seek candidates with potential for excellence in teaching in graduate and undergraduate programs. We particularly prefer an individual who has prior teaching and/or professional experience in Operations Management, Operations Research, or Statistics. We desire candidates who can help us to design and deliver courses in our undergraduate program in management, the M.B.A. program, and in our master’s degree program in supply chain management and operations research. The potential to take a leadership position in the management of these programs and to participate in executive education is also desirable. The candidate should have a graduate degree in Operations Management, Operations Research, Statistics, or a related area. A doctoral degree would be a plus.

The Department has a long and distinguished history and granted the first Ph.D. in operations research. The Weatherhead School’s MBA and Undergraduate programs (in which the successful candidate would teach) are well ranked. The University is ten minutes from downtown Cleveland with world-class cultural venues within walking distance and excellent residential areas close by.

Applicants should e-mail a resume, any evidence of teaching effectiveness (course evaluations, for example) and should also arrange for at least three letters of reference to be sent electronically to Ms. Tedda Nathan at oprerecruit@case.edu.

“In employment as in education, Case Western Reserve University is committed to Equal Opportunity and Diversity. Women, veterans, members of underrepresented minority groups, and individuals with disabilities are encouraged to apply.”

Case Western Reserve University provides reasonable accommodations to applicants with disabilities. Applicants requiring a reasonable accommodation for any part of the application and hiring process should contact the Office of Inclusion, Diversity and Equal Opportunity at 216-368-8877 to request a reasonable accommodation. Determinations as to granting reasonable accommodations for any applicant will be made on a case-by-case basis.

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The Decision, Risk and Operations Division at Columbia Business School is seeking to hire qualified faculty members for tenure-track appointments at the assistant or associate professor level, depending on the qualifications of the applicant.

The Division has teaching responsibilities for management science, statistics, and operations management courses at the MBA and Ph.D. levels. Applicants for an associate professor level appointment should have a Ph.D. from an accredited institution, a record of scholastic achievement in both research and teaching, and should combine exceptional disciplinary training with a strong interest in the professional mission of the school. Applicants for an assistant professor level appointment should have, or be close to completing, a Ph.D. from an accredited institution, demonstrate promise of becoming an outstanding scholar in every respect, including research and teaching, and should combine exceptional disciplinary training with a strong interest in the professional mission of the school.

Columbia Business School is particularly interested in candidates who, through their research, teaching and/or service will contribute to the diversity and excellence of the academic community.

Applicants should apply online at

CLASSIFIEDS

JORDAN LOUVIERE FELLOWSHIP IN CHOICE MODELLING • Institute for Choice, located in Sydney, NSW, Australia • Three (3) year full-time, fixed term contract • Salary range: AUD$111,681 - $148,142 per annum The University of South Australia is an enterprising and dynamic, outward-looking institution established in 1991, but built on more than 150 years of teaching, learning and research excellence of our antecedent institutions. We are South Australia’s largest university, and continue to enjoy a strong upward trajectory across a number of key indicators and global rankings - we are ranked amongst the top 3% of universities worldwide and in the top 50 international universities under 50 years of age.

https://academicjobs.columbia.edu/applicants/Central?quickFind=63185

Candidates are encouraged to apply by November 1 to be considered before the annual INFORMS conference.

School of Industrial Engineering and Management College of Engineering, Architecture and Technology Oklahoma State University The School of Industrial Engineering and Management at Oklahoma State University seeks talented and motivated candidates for one faculty position starting in Fall 2017. Rank, tenure, and salary will be determined based on candidate qualifications and accomplishments. The candidates are expected to have completed their PhD or satisfied requirements for a PhD by August 2017.

Although candidates with at least one degree in industrial engineering are preferred, those with degrees in a closely related discipline will be considered. Candidates must have a strong methodological background, potential to attract funded research and complement as well as enhance the School’s current research and educational thrusts. Performance expectations include leadership and creativity in undergraduate and graduate education, funded research, scholarship, and professional service. The School has an ambitious plan for growth, recognition and visibility in the industrial engineering and management field.

Candidates with a strong methodological background in optimization, stochastic modeling or simulation and research/curricular interests in one or more of the following industrial engineering and management areas are sought.

• Data Analytics • Energy and Climate Science • Engineering Management • Ergonomics and Human Factors • Food, Energy, and Water Systems • Healthcare Systems

• Life Science • Logistics and Transportation • Supply Chain Management • Manufacturing Processes and Systems • Quality Management and Engineering • Service Systems

Interested applicants should apply online at http://jobs.okstate.edu. Applicants should submit a cover letter, curriculum vitae a list of three to five references, and a statement of teaching, research and service interests. Any inquiries may be sent to Sunderesh Heragu, Regents Professor and Head, School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK 74078 (sunderesh.heragu@okstate.edu). More information about the School can be found at iem.okstate.edu.

Applications received before December 1, 2016 will receive full consideration. However, applications will be accepted and considered until the positions are filled.

Oklahoma State University is an Affirmative Action/Equal Opportunity/E-verify employer committed to diversity and all qualified applicants will receive consideration for employment and will not be discriminated against based on age, race, color, religion, sex, sexual orientation, genetic information, gender identity, national origin, disability or protected veteran states.OSU is a VEVRAA Federal Contractor and desires priority referrals of protected veterans for its opening. For more information go to eeo.okstate.edu.

The Institute for Choice is a world-leading research facility that focuses on understanding and modelling human decision-making and choice behaviour. The Jordan Louviere Fellow will develop, engage and lead high quality research projects in the area of choice modelling. You will make independent and original research contributions of both a theoretical and empirical nature in the area of discrete choice modelling, with an expected significant impact in your area of specialisation. You will also be acknowledged at an international level as being influential in expanding the knowledge of your relevant discipline.

Your expertise in choice modelling will apply to transport, energy, utility/networks, environment/resources or labour.

You will have a quantitative PhD in applied economics, econometrics, or other relevant field (appointment as Senior Research Fellow), or a doctorate in an area of applied economics together with research experience preferentially aligned with Australian research priorities (appointment as Associate Research Professor). The level of appointment will depend on the skills and experience of the successful applicant.

For a copy of the position description and to apply, please visit Working at UniSA. For further information in the first instance, please contact Katrina Gillespie, Senior Human Resources Consultant, on + 61 8 8302 1193 or via email at katrina.gillespie@unisa.edu.au.

This position will remain open until a suitable candidate has been identified. www.unisa.edu.au/workingatunisa The University is an Equal Opportunity Employer.

CRICOS PROVIDER NO 00121B

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FACULTY POSITIONS Business – Information Systems NYU SHANGHAI Carnegie Mellon University: Tepper School of Business JUNIOR FACULTY TENURE-TRACK POSITION IN OPERATIONS RESEARCH The Tepper School of Business at Carnegie Mellon University seeks candidates for a tenure-track faculty position in Operations Research at the Assistant Professor level, beginning in September 2017. Applicants are expected to have a Ph.D. in Operations Research or a related field at the time of appointment, a demonstrated potential for outstanding research, and strong teaching skills.

The specialty of the candidate may be in the broad area of Optimization with connections to Business Analytics and Machine Learning. The ideal candidate will be able to contribute to the school’s analytical approach to business education, and engage in cross-disciplinary research activities within the Tepper School and Carnegie Mellon University.

Carnegie Mellon University seeks to meet the needs of dual-career couples and is a member of the Higher Education Recruitment Consortium (HERC) that assists with dual-career searches.

Applicants should submit an application letter, curriculum vitae, up to three publications or working papers, research and teaching statements, and three recommendation letters. Questions about the application can be addressed to Mr. Philip Conley at orgroup@andrew.cmu.edu or 412-268-6212.

To receive full consideration, applications must be submitted by January 1, 2017.

Application Procedure: Faculty applications and all supporting documents must be submitted to: https://apply.interfolio.com/37613 Carnegie Mellon University is an equal opportunity employer and is committed to increasing the diversity of its community on a range of intellectual and cultural dimensions. Carnegie Mellon welcomes faculty applicants who will contribute to this diversity through their research, teaching and service, including women, members of minority groups, protected veterans, individuals with disabilities, and others who would contribute in different ways.

NYU Shanghai is seeking to fill tenure-track or tenure positions in the field of Information Systems, beginning in the Fall Semester of 2017. Positions are available at all ranks: Assistant Professor, Associate Professor and Full Professor.

The terms of employment for tenure-track or tenure Business faculty positions in NYU Shanghai are comparable to NYU Stern in terms of compensation and research funds, and include housing subsidies and educational subsidies for children. Faculty may also spend time at NYU New York and other sites of the NYU global network, engaging in both research and teaching.

Applications are due no later than January 20, 2017. The review of applications will begin immediately, and will continue until the positions are filled. To be considered, applicants should submit a curriculum vitae, separate statements of research and teaching interests (no more than three pages each), and electronic copies of representative publications. To complete the online process, applicants will be prompted to enter the names and email addresses of three referees. Each referee will be contacted to upload their reference letter. Please visit our website at http://shanghai.nyu.edu/en/about/workhere/open-positions-faculty for instructions and other information on how to apply. If you have any questions, please e-mail shanghai.faculty.recruitment@nyu.edu.

About NYU Shanghai: NYU Shanghai is the newest degree-granting campus within New York University’s global network. It is the first higher education joint venture in China authorized to grant degrees that are accredited in the U.S. as well as in China. All teaching is conducted in English. A research university with liberal arts and science at its core, it resides in one of the world’s great cities with a vibrant intellectual community. NYU Shanghai recruits scholars of the highest caliber who are committed to NYU’s global vision of transformative teaching and innovative research and who embody the global society in which we live.

NYU’s global network includes degree-granting campuses in New York, Shanghai, and Abu Dhabi, complemented by eleven additional academic centers across five continents. Faculty and students circulate within the network in pursuit of common research interests and cross-cultural, interdisciplinary endeavors, both local and global.

NYU Shanghai is an equal opportunity employer committed to equity, diversity and social inclusion. We strongly encourage applications from individuals who are underrepresented in the profession, across color, creed, race, ethnic and national origin, physical ability, and gender and sexual identity. NYU Shanghai affirms the value of differing perspectives on the world as we strive to build the strongest possible university with the widest reach.

EOE/AA/Minorities/Females/Vet/Disabled/Sexual Orientation/Gender Identity Employer

FACULTY POSITION IN MATHEMATICS: Mathematical Optimization and Data Analytics University of California, Davis The Department of Mathematics at the University of California, Davis invites applications for an Assistant Professor (tenure-track) faculty position in the areas of Mathematical Optimization and Data Analytics starting July 1, 2017.

Minimum qualifications for the position include a Ph.D. degree or its equivalent in the Mathematical Sciences or a related field and excellent potential for performance in teaching and research.

Duties include mathematical research, undergraduate and graduate teaching, and departmental, university and professional service.

Candidates are expected to engage in interdisciplinary research within the UC Davis Data Science Initiative.

Additional information about the Department may be found at https://www.math.ucdavis.edu/.

Applications will be accepted until the position is filled. For full consideration, completed applications should be received by December 15, 2016. To apply: submit the AMS Cover Sheet and supporting documentation electronically through http://www.mathjobs.org/.

The University of California, Davis, is an affirmative action/equal opportunity employer with a strong institutional commitment to the achievement of diversity among its faculty and staff.

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Faculty, Researcher, Postdoctoral Positions MIT Global SCALE Network The Massachusetts Institute of Technology’s Global Supply Chain and Logistics Excellence (MIT SCALE) Network is growing rapidly and we are seeking talented and energetic professionals for Faculty, Researcher, and Postdoctoral positions across the network. Candidates will help our centers become world leaders in education and research in supply chain management, freight transportation, global trade, and logistics.

The MIT SCALE Network consists of six education and research centers of excellence focused in supply chain management and logistics. Currently there are centers in Cambridge, MA, USA; Zaragoza, Spain; Bogota, Colombia; Kuala Lumpur, Malaysia; University of Luxembourg, Luxembourg; and Ningbo, China.

For more information and directions on submitting an application for any of these positions, please visit: https://academicjobsonline.org/ajo/SCM

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advertiser index Page #

Columbia Business School is seeking to hire one or more lecturers in discipline or senior lecturers in discipline in the field of Decision, Risk, and Operations. The Division has teaching responsibilities for management science, statistics, and operations management courses at the MBA and Ph.D. levels.

All applicants must have a doctoral degree from an accredited institution. Applicants for an appointment as lecturer in discipline should have a record (at least 2 years) of EITHER successful teaching OR significant industry experience relevant to the division's needs. Applicants for a senior lecturer in discipline appointment should have an established record (5 of more years) of EITHER successful teaching OR significant industry experience that would warrant appointment at the senior rank.

Columbia Business School is particularly interested in candidates who, through their research, teaching and/or service will contribute to the diversity and excellence of the academic community.

Applicants should apply online at https://academicjobs.columbia.edu/applicants/Central?quickFind=63459.

Candidates are encouraged to apply by November 1 to be considered before the annual INFORMS conference.

ADVERTISER E-mail & Web Page

C2

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AIMMS info@aimms.com www.aimms.com

AMPL Optimization

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American Society for Engineering Education

smart@asee.org https://smart.asee.org

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Banxia® Software Ltd.

info@banxia.com www.banxia.com

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Dynamic Ideas, LLC

orders@altlog.net www.dynamic-ideas.com

17 FICO FICOAmericas@fico.com www.fico.com/shell

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GAMS Development Corp. sales@gams.com www.gams.com

Geer Mountain

The Department of Industrial Engineering at the University of Arkansas invites applications for a tenure track Assistant Professor position with an anticipated start date of August 2017.

We seek individuals whose research and graduate teaching interests in Analytics and other related areas that align with the department’s emphasis in the application of quantitative modeling and analysis in the areas of quality and reliability engineering, logistics and distribution, and healthcare systems.

More importantly, we seek individuals who can make contributions to the university’s new cross-college, interdisciplinary Institute for Advanced Data Analytics. The new institute was established as a new industry research partnership for developing practical, implementable solutions to industry issues and problems as well as a source of continuing education in data analytics.

Applicants should have a PhD in industrial engineering, operations research, statistics, computer science, or other closely related field and have excellent communication skills.

Applicants should demonstrate potential for high-quality research, for securing competitive research funding and scholarly publications, provide evidence of teaching excellence (undergraduate and graduate courses), experience advising PhD students, and ability to provide appropriate service to the department, university, and the profession.

Applicants are asked to provide a letter of interest, curriculum vita, research and teaching statements, and the names of three references.

To ensure full consideration, application materials should be submitted online

by December 1st, 2016 at http://jobs.uark.edu/postings/16265. Applications submitted after that date will be reviewed until the position is filled. http://industrial-engineering.uark.edu The University of Arkansas is an equal opportunity, affirmative action institution. The university welcomes applications without regard to age, race, gender (including pregnancy), national origin, disability, religion, marital or parental status, protected veteran status, military service, genetic information, sexual orientation or gender identity. Persons must have proof of legal authority to work in the United States on the first day of employment. All applicant information is subject to public disclosure under the Arkansas Freedom of Information Act.

Software Corporation

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Gurobi Optimization

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14, 15, 27, INFORMS 29, 39, 46 informs@informs.org meetings@informs.org www.informs.org

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LINDO Systems, Inc. info@lindo.com www.lindo.com

Logical Decisions www.logicaldecisions.com

Optimization Direct, Inc.

alkis@industrialgorithms.com www.optimizationdirect.com

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Saitech, Inc.

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ORacle

Doug Samuelson

samuelsondoug@yahoo.com

The detective’s parable The group of OR/MS analysts had reconvened, dawdling over another nice lunch, shortly after the first presidential candidates’ debate of 2016. Brett asked Ben, “So what do you think now?” (Brett remembered Ben’s scathing comments about the Trump campaign from last issue’s ORacle column, and his more general critique of others’ public speaking from the ORacle column in the issue before that.)

“Still holding my nose at both parties, although Trump is still doing worse than Hillary,” Ben grimaced, as the group joined in a rather hollow laugh. “At least she managed to stay focused and on message throughout the debate, which is why now she got a little bump in the polls,” he added.

“That’s what I thought. But what did she mess up?” Jim prompted.

“Let’s just say,” Ben responded, “the long-haul pressure of a campaign exposes the weaknesses of any candidate. In Trump’s case, it’s lack of discipline and focus, as you’ve seen. Hillary is almost the opposite, a control freak who has trouble with spontaneity, especially in front of a crowd. Remember how she helped kill her health plan, back in 1993, by playing everything way too close, with a handful of trusted advisors, and not communicating with potential allies, so there was no consensus? In the debate, her style was working for her, because she was able to keep baiting Trump and he kept giving the kinds of responses she had prepared for.

“But think about how she’s handled the charges about her email server,” Ben went on. “It should have been obvious to lots of people, certainly anyone in our line of work, that she got advised from the start of her time as secretary of state to keep as much of her email private as possible. Government systems are prime targets for hackers, and they’ve gotten hacked several times in the past 10 years. Her private server did not get hacked, as far as anyone knows. It’s a 64 | ORMS Today

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October 2016

a reprimand and a warning. If it got wider and more serious, maybe the employee would lose his or her security clearance and have to find another job. But it’s extremely unlikely there would be even a misdemeanor criminal charge, and maybe a

If they discover it piece by piece, they think you’re covering up, and they keep digging to see what more might be there.

basic principle of IT security: don’t trust any system you Don’t control.

“So what she did,” Ben explained, “was take that advice and push it further than she should have, following her natural tendencies to try to keep control over everything, and she missed the importance of keeping classified material within the system.That’s partly for better security, although that’s questionable. It also makes it possible for the security bureaucrats to go back and declare that something should have been classified and immediately make it harder to get and disclose – which drives everyone else crazy, and that’s another reason she resisted. But perhaps most important, it spreads the responsibility for keeping information secure, and that spreading can be very helpful to a prominent official later, when something sensitive leaks out.”

“So her real mistake was missing an opportunity to spread the blame?” Jim laughed.

Ben shook his head. “Her real mistake was not following the rules because she thought she knew better than everyone else. Sometimes that’s the right thing to do, but more often it has a way of coming back to bite you.”

Jim looked skeptical.

“And then there was the second mistake,” Ben resumed. “I learned this rule as a kid from my uncle, who was a detective. He said, ‘When you get caught doing anything that’s likely to be a problem, immediately admit everything that’s going to come out later.That way, the investigators are likely to decide that you messed up once but came clean about it. If they discover it piece by piece, they think you’re covering up, and they keep digging to see what more might be there.’ And that’s what happened to her with the email server. It’s the sort of thing that would get a mid-level employee

couple of years’ probation – and that’s the most it would be, worst case, as long as the security leak caused no major damage.

“But cover it up,” Ben concluded, “and they go after you for perjury and obstruction of justice – both felonies. Or, for a public official, still probably no felony charges, but a scandal that just won’t go away.Which is what Hillary has now.”

“Seems fair to me,” Jim responded, clearly skeptical about Hillary.

“And it is fair,” Ben asserted. “Public officials need to know how to gather input, involve other people and interests in decisions, build consensus and end up with shared responsibility – and, when they’re wrong,‘fess up quickly and contain the damage. Hillary learned some of that as a senator, but she’s not as good at it as the more successful presidents we’ve had, like Ronald Reagan.”

“Hey, Mr. Democrat, don’t tell me you miss Reagan!” Jim chided Ben. Ben smiled ruefully.“I hate to tell you,” he admitted,“I miss him, and George H.W. Bush and Jerry Ford. Even Dan Quayle is looking better and better – he had good advisors and listened to them. Pity we can’t trade both of our current nominees to the Brits for Tony Blair.”

“Agreed!” the group chorused. And they proceeded to order another round of adult beverages, as after this discussion they felt a strong need for anesthetics. ORMS Doug Samuelson is president and chief scientist of InfoLogix, Inc., in Annandale, Va. He is a veteran of a number of political campaigns in addition to his long career as a federal policy analyst and consultant. Contrary to rumors, he is not actively looking into longterm residence overseas – yet.

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