Course Introduction
Management Science
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Management Science is an interdisciplinary course that focuses on the application of quantitative and analytical methods to decision-making in organizations. Students will learn to utilize mathematical modeling, statistics, and optimization techniques to solve complex business problems and improve operational efficiency. The course covers topics such as linear programming, simulation, decision analysis, forecasting, inventory management, and project scheduling. By integrating real-world case studies and computer-based tools, Management Science prepares students to make informed managerial decisions and supports data-driven strategies in diverse organizational settings.
Recommended Textbook
Practical Management Science 5th Edition by Wayne
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14 Chapters
421 Verified Questions
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Page 2
L. Winston
Chapter 1: Introduction to Modeling
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Sample Questions
Q1) Which of the following is a possible cause if a model's outputs for certain inputs are not as expected?
A)The certain inputs may not be correct
B)The model could be too detailed of an approximation of the actual situation
C)The mathematics in the model are inadequate
D)The analyst's expectations are not correct
Answer: D
Q2) In some applications, an analyst might present several alternative solutions from a model, and let the organization choose the best one.
A)True
B)False
Answer: True
Q3) Optimization models are useful for determining:
A)sensitivity to inputs
B)whether the inputs are valid or not
C)what the manager should do
D)the value of the output under the current conditions
Answer: C
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3
Chapter 2: Introduction to Spreadsheet Modeling
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Sample Questions
Q1) Which of the following is not one of the components of a mathematical model?
A)Inputs
B)Outputs
C)Decision variables
D)None of these options
Answer: D
Q2) Which of the following is a useful tool for understanding and troubleshooting a spreadsheet model?
A)Data tables
B)VLOOKUP function
C)Formula auditing
D)SUMPRODUCT function
Answer: C
Q3) Which of the following is not one of the types of curve fitting models available in Excel's Trendline tool?
A)Exponential
B)Linear
C)Interpolation
D)Power
Answer: C
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Chapter 3: Introduction to Optimization Modeling
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Sample Questions
Q1) The feasible region in all linear programming problems is bounded by:
A)corner points
B)hyperplanes
C)an objective line
D)all of these options
Answer: B
Q2) In an optimization model, there can only be one:
A)decision variable
B)constraint
C)objective function
D)shadow price
Answer: C
Q3) The proportionality property of LP models implies that the sum of the contributions from the various activities to a particular constraint equals the total contribution to that constraint.
A)True
B)False
Answer: True
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5
Chapter 4: Linear Programming Models
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Sample Questions
Q1) [Part 2] Refer to Exhibit 4-3. What happens to the revenue when the optimal plan changes to the one given in Part 1?
Q2) If we round the optimal values in the changing cells of a linear programming model, this is a good approximation of the integer programming solution.
A)True
B)False
Q3) [Part 1] Refer to Exhibit 4-3. Suppose that later in the year, venison will be out of season, but the market will be able to obtain an additional 300 pounds of pork for the same costs. Develop a processing plan in that case. How does the solution change?
Q4) Refer to Exhibit 4-2. Suppose the bonus for completing the project three months early is $250,000. What would be the net bonus to the company, after adjusting for any difference in personnel costs under the accelerated schedule?
Q5) In blending problems, if a quality constraint involves a quotient, then the problem will be nonlinear.
A)True
B)False
Q6) Refer to Exhibit 4-3. Determine the optimal processing plan for the meat market.
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Page 6
Chapter 5: Network Models
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Sample Questions
Q1) The objective in transportation problems is typically to:
A)maximize profits
B)maximize revenue
C)minimize costs
D)maximize feasibility
Q2) Transshipment points are locations where goods neither originate nor end up, but goods are allowed to enter such points to be shipped out to their eventual destinations.
A)True
B)False
Q3) The cost of an arc in a shortest path problem is equal to the distance of the arc.
A)True
B)False
Q4) In transportation problems, the three sets of input numbers that are required are capacities, demands and flows.
A)True
B)False
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Chapter 6: Optimization Models With Integer Variables
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Sample Questions
Q1) The default integer optimality setting in Solver is:
A)0.1%
B)0.5%
C)1%
D)5%
Q2) Any integer program involving 0 1 variables with ____ constraint(s) is called a knapsack problem.
A)three
B)two
C)one
D)zero
Q3) Refer to Exhibit 6-2. This problem is an example of what type of integer programming model?
Q4) Optimization software, including Solver, typically has more difficulty solving an integer programming problem, relative to a linear programming problem.
A)True
B)False
Q5) Refer to Exhibit 6-1. This problem is an example of what type of integer programming model?
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Chapter 7: Nonlinear Optimization Models
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Sample Questions
Q1) In advertising response models, a typical source of nonlinearity is a decreasing marginal effect, where each extra ad gains fewer exposures than the previous ad.
A)True
B)False
Q2) In pricing models, elasticity of demand is an input with specifies the:
A)range of demand
B)level of demand
C)sensitivity of price to changes in demand
D)sensitivity of demand to changes in price
Q3) A function is convex if a line drawn connecting two points on the curve never lies below the curve.
A)True
B)False
Q4) Refer to Exhibit 7-1. How many units of each product should the company produce? What prices should it charge, to maximize profit?
Q5) [Part 1] Refer to Exhibit 7-4. Determine the minimum variance portfolio that yields an expected annual return of at least 0.10
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9
Chapter 8: Evolutionary Solver: An Alternative Optimization
Procedure
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Sample Questions
Q1) The initial set of chromosomes generated by a genetic algorithm is called the population.
A)True
B)False
Q2) The Evolutionary Solver setting that helps the algorithm explore a completely different area of the feasible region is:
A)convergence
B)mutation rate
C)population size
D)random seed
Q3) Refer to Exhibit 8-2. Explain why this problem typically requires Evolutionary Solver to obtain a solution.
Q4) The data used to classify members in a discriminant analysis is called a:
A)group
B)cluster
C)training sample
D)population
Q5) Refer to Exhibit 8-3. Use a discriminant analysis to develop a classification model. What is the best percentage correctly classified obtained with your model?
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Chapter 9: Decision Making Under Uncertainty
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Sample Questions
Q1) The strategy region graph is a type of sensitivity analysis chart that:
A)is useful in determining whether the optimal decision changes over the range of the input variable.
B)ranks the sensitivity of the EMV to the input variables.
C)reflects how the value of information changes over a range of probabilities.
D)None of these
Q2) Refer to Exhibit 9-2. Should the credit union purchase the report if it costs $150?
Q3) Refer to Exhibit 9-2. Suppose that an actual (not perfectly reliable) credit report has the following characteristics based on historical data; in cases where the customer did not default on the approved loan, the probability of receiving a favorable recommendation on the basis of the credit investigation was 80%, while in cases where the customer defaulted on the approved loan, the probability of receiving a favorable recommendation on the basis of the credit investigation was 25%. Given this information, what are the posterior probabilities that default will and will not occur, given the credit report?
Q4) Refer to Exhibit 9-2. Construct a decision tree to help the credit union decide whether or not to make the loan. Make sure to label all decision and chance nodes and include appropriate costs, payoffs and probabilities.
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Chapter 10: Introduction to Simulation Modeling
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Sample Questions
Q1) Correlation between two random input variables may change the mean of an output, but it will not affect the variability and shape of an output distribution.
A)True
B)False
Q2) A distribution for modeling the time it takes to serve a customer at a bank is probably:
A)symmetric
B)left skewed
C)right skewed
D)uniform
Q3) It is usually fairly straightforward to predict the shape of the output distribution from the shape(s) of the input distribution(s).
A)True
B)False
Q4) Refer to Exhibit 10-1. A little later on, management still believes the upper and lower bounds for the costs are $5M and $8M, but now they can also state that "we believe the most likely value is about $6.5M."
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Chapter 11: Simulation Models
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Sample Questions
Q1) Which of the following is the most likely characteristic of a distribution that is to be used to develop a simulation model for estimating the time until failure of a product in a simulation model?
A)Unbounded
B)Left skewed
C)Normal
D)Uniform
Q2) A key input variable in many marketing models of customer loyalty is the:
A)Mean profit per customer
B)Number of customers
C)Churn rate
D)Time horizon
Q3) In marketing and sales models, the primary issue is the uncertain amount of sales that can be obtained, given an assumed timing.
A)True
B)False
Q4) [Part 4] Refer to Exhibit 11-1. What does the distribution of the project NPV look like?
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13
Chapter 12: Inventory and Supply Chain Models
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Sample Questions
Q1) The time it takes for an order to arrive at facility is called the stockout time.
A)True
B)False
Q2) Refer to Exhibit 12-1. Suppose there is a storage cost of $10 per unit. Make the appropriate change to your Solver model or EOQ formula, and find the optimal order quantity in that case.
Q3) Refer to Exhibit 12-3. Suppose the annual demand for the sweaters is not known with certainty, but rather is estimated to be normally distributed with mean 26,000 and standard deviation 2,000. Formulate a Solver model to find the optimal (R,Q) policy by minimizing the North Slope's expected annual cost. What is the policy, and what is the total annual cost?
Q4) An order cycle begins each time an order arrives and ends just before the next order arrives.
A)True
B)False
Q5) Refer to Exhibit 12-3. Formulate a Solver model and find the optimal order quantity for the cotton sweaters. What is the optimal order? How much, if any, is the maximum backlog?
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Page 14
Chapter 13: Queuing Models
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Sample Questions
Q1) Refer to Exhibit 13-4. Use the M/M/s template to find the expected number of busy servers, and the expected fraction of time each server is busy
Q2) The decision to balk at entering a queuing system can be made by the customer or the system.
A)True
B)False
Q3) Refer to Exhibit 13-4. What percentage of customers do not wait in the queue?
Q4) Refer to Exhibit 13-2. How many of the servers are busy on average?
Q5) Refer to Exhibit 13-3. What percentage of all customers have to spend at least some small amount of time waiting in line?
Q6) When a customer already in line in a queuing system becomes impatient and leaves the system before starting service, this is called:
A)balking
B)limited waiting
C)quitting
D)reneging
Q7) Refer to Exhibit 13-3. What is the average length of time (in hours) spent waiting in line?
Page 15
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Chapter 14: Regression and Forecasting Models
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Sample Questions
Q1) In reference to the equation , the value 0.10 is the expected change in Y per unit change in X.
\[\hat { Y } = - 0.70 + 0.10 X\]
A)True
B)False
Q2) Forecasting models can be divided into three groups. They are:
A)time series, optimization, and simulation methods
B)judgmental, regression, and extrapolation methods
C)judgmental, random, and linear methods
D)linear, non-linear, and extrapolation methods
Q3) A "fan" shape in a scatterplot indicates:
A)nonconstant error variance
B)a nonlinear relationship
C)the absence of outliers
D)sampling error
Q4) Refer to Exhibit 14-1. How does the R2 value for this multiple regression model compare to that of the simple regression model estimated above? Interpret the adjusted R2 values for the two models.
Q5) Refer to Exhibit 14-2. Identify and interpret the percentage of variation explained (R2) for the model.
Page 16
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