Simulation Modeling Test Questions
Course Introduction
Simulation Modeling introduces students to the fundamental principles and techniques of constructing and analyzing computer-based models that imitate real-world processes or systems. The course covers the development of conceptual models, the use of discrete-event and agent-based simulation methods, input data collection and analysis, model validation and verification, and interpretation of simulation results. Emphasis is placed on hands-on experience with simulation software, enabling students to apply simulation modeling to solve complex problems in fields such as engineering, healthcare, manufacturing, and business. Students will gain skills in designing simulation experiments, analyzing system performance, and making data-driven decisions based on simulated outcomes.
Recommended Textbook
Practical Management Science 6th Edition by Wayne L. Winston
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Chapter 1: Introduction to Modeling
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Sample Questions
Q1) Management science has often been taught as a collection of:
A) theories
B) problems
C) models
D) topics
Answer: C
Q2) 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
Q3) Which of the following is <u>not</u> one of advantages of mathematical models
A) Mathematical models enable managers to understand the problem better
B) Mathematical models allow analysts to employ a variety of mathematical solution procedures
C) The mathematical modeling process itself, if done correctly, often helps "sell" the solution
D) Mathematical models help reduce the cost of obtaining a solution
Answer: D
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Chapter 2: Introduction to Spreadsheet Modeling
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Q1) [Part 1] Refer to Exhibit 2-2.Use the graphing function in Excel to construct a scatterplot of forecasted price versus time,and fit a linear trendline to the data.What are the coefficients of the linear model,and what is the MAPE of a linear model forecast,compared to the company's forecast
Answer: The linear trend fit produces an intercept of 16.6 and a slope of 2.9.Forecasting with this model and comparing against the company forecast results in a MAPE of 1.5%.
Q2) Estimating the relationships between variables in a spreadsheet model can be done using:
A) data tables
B) Goal Seek
C) the VLOOKUP function
D) curve fitting
Answer: D
Q3) In Excel terminology,the unknown value used in Goal Seek is called the input cell.
A)True
B)False
Answer: False
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Chapter 3: Introduction to Optimization Modeling
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Sample Questions
Q1) In an optimization model,there can only be one:
A) decision variable
B) constraint
C) objective function
D) shadow price
Answer: C
Q2) Suppose the allowable increase and decrease for an objective coefficient of a decision variable that has a current value of $50 are $25 (increase)and $10 (decrease).If the coefficient were to change from $50 to $65,the optimal value of the objective function would not change.
A)True
B)False
Answer: False
Q3) When formulating a linear programming spreadsheet model,there is a set of designated cells that play the role of the decision variables.These are called the changing variable cells.
A)True
B)False
Answer: True
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Chapter 4: Linear Programming Models
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Sample Questions
Q1) When a workforce scheduling problem is formulated as an integer programming model,it has:
A) an integer objective function
B) integer technological coefficients
C) integer constraints
D) all of these options
Q2) Workforce scheduling problems in which the worker schedules continue week to week are:
A) continuous problems
B) transition problems
C) integrated problems
D) wraparound problems
Q3) One way to solve a dual-objective problem is to use one objective as the target cell and constrain the other.
A)True
B)False
Q4) Refer to Exhibit 4-4.Assuming that all fertilizer produced can be sold,determine the optimal blending plan for the company.What is the maximum profit
Q5) Refer to Exhibit 4-3.Determine the optimal processing plan for the meat market.
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Chapter 5: Network Models
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Q1) It is useful to model network problems by listing all of the arcs and their corresponding flows in one long,comprehensive list.
A)True
B)False
Q2) The objective in transportation problems is typically to:
A) maximize profits
B) maximize revenue
C) minimize costs
D) maximize feasibility
Q3) The cost of an arc in a shortest path problem is not necessarily equal to the distance of the arc.
A)True
B)False
Q4) Refer to Exhibit 5-1.Implement the LP model in Solver and obtain the optimal shipping plan.What is the optimized cost
Q5) A typical shortest path problem is a special case of the general network flow model.
A)True B)False
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Chapter 6: Optimization Models With Integer Variables
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Sample Questions
Q1) In a linear model,the target cell and constraints are ultimately:
A) a product of changing cells
B) a sum of products of changing cells
C) a product of constants and changing cells
D) a sum of products of constants and changing cells
Q2) Refer to Exhibit 6-2.What is Sinclair's optimal shipping plan What is the total cost in that case
Q3) Complete enumeration of all possible solutions in many integer programming problems is impractical.
A)True
B)False
Q4) During the solution of a maximization problem with the branch and bound algorithm,an incumbent solution represents an upper bound on the solution.
A)True
B)False
Q5) Refer to Exhibit 6-2.This problem is an example of what type of integer programming model
Q6) Refer to Exhibit 6-3.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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Q1) Which of the following is not one of the reasons an optimization model can become nonlinear
A) Nonconstant returns to scale.
B) The model objective is to minimize the sum of squared differences.
C) The model objective is a function of a variable times multiplied by a function of that same variable
D) The model objective is to minimize the sum of absolute errors.
Q2) Which of the following is not one of the useful options within Solver's Multistart box
A) Population size
B) Error distribution
C) Random seed
D) Upper or lower bound constraints on all changing cells
Q3) As an objective,minimizing the sum of squared errors is equivalent to minimizing the A) root mean square error
B) weighted sum of squared errors
C) sum of absolute errors
D) maximum absolute error
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Chapter 8: Evolutionary Solver: An Alternative Optimization
Procedure
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Sample Questions
Q1) With two-part tariff pricing,it is assumed that a customer buys the quantity that provides the largest difference between value and total price.
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 8-4.Formulate and solve a shortest-path model using Evolutionary Solver.What is the shortest distance Steve can travel and visit all cities What is the route
Q4) The initial set of chromosomes generated by a genetic algorithm is called the population.
A)True B)False
Q5) Refer to Exhibit 8-1.This is an example of what type of optimization problem
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Chapter 9: Decision Making Under Uncertainty
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Q1) Bayes' rule is used for updating the probability of an uncertain outcome after observing the results of a test or study.
A)True
B)False
Q2) The certainty equivalent is the certain dollar amount a risk-averse decision maker would accept in order to avoid a gamble altogether.
A)True
B)False
Q3) Refer to Exhibit 9-2.The bank can thoroughly investigate the customer's credit record and obtain a favorable or unfavorable recommendation.If the credit report is perfectly reliable,what is the most the credit union should be willing to pay for the report
Q4) Refer to Exhibit 9-1.Find the highest cost of insulating the grapefruits for which the farmer prefers to insulate his crop.
Q5) Which of the following statements is true concerning decision tree conventions
A) Time proceeds from right to left.
B) The trees are composed of circles, triangles and ovals.
C) The nodes represent points in time.
D) Probabilities of outcomes are shown to the right of the end nodes.
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Chapter 10: Introduction to Simulation Modeling
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Q1) One of the primary advantages of simulation models that they enable managers to answer what-if questions about changes in systems without actually changing the systems themselves.
A)True
B)False
Q2) Refer to Exhibit 10-2.What is the probability that the apparel company will exceed a profit at least $0.5M from the jacket line
Q3) A correlation matrix must always be symmetric,so that the correlations above the diagonal are a mirror image of those below it.
A)True
B)False
Q4) A correlation matrix must always have 1's along its diagonal (because a variable is always perfectly correlated with itself)and numbers between 1 and +1 elsewhere.
A)True
B)False
Q5) Refer to Exhibit 10-2.Use @RISK distributions to generate the three random variables for regional sales and derive a distribution for the total sales.What is the expected total sales
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Chapter 11: Simulation Models
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Q1) [Part 2] Refer to Exhibit 11-2.Use a RISKSIMTABLE to with the following values for capacity: 20,000,25,000,30,000,35,000,40,000.Which of these capacities produces the largest expected NPV
Q2) Value at risk (VAR)is an indicator of:
A) how much to bid for a project
B) the expected amount of loss for a project
C) what is nearly the worst possible outcome for a project
D) the required amount of investment required for a project
Q3) [Part 5] Refer to Exhibit 11-1.What are the chances the firm could lose money on this project,given the price uncertainty
Q4) [Part 4] Refer to Exhibit 11-2.Are there any simulations which indicated there was a chance of getting negative NPV Briefly explain in one sentence.
Q5) The main issue in marketing and sales models is:
A) the amount invested in marketing
B) the timing of marketing
C) the profit from sales
D) the timing of sales
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Chapter 12: Queueing Models
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Q1) Refer to Exhibit 12-4.What percentage of customers do not wait in the queue
Q2) In an Erlang loss model,customers who arrive when all servers are busy are lost to the system.
A)True
B)False
Q3) Exponentially distributed service times are often more realistic than exponentially distributed interarrival times.
A)True
B)False
Q4) Refer to Exhibit 12-3.What is the average length of time (in hours)spent waiting in line
Q5) The two basic modeling approaches for queuing systems are optimization and simulation.
A)True
B)False
Q6) The exponential distribution is:
A) flat
B) bell-shaped
C) heavily right-skewed
D) heavily left-skewed
Page 14
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Chapter 13: Regression and Forecasting Models
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Q1) Refer to Exhibit 13-1.How does the R<sup>2</sup> value for this multiple regression model compare to that of the simple regression model estimated above Interpret the adjusted R<sup>2</sup> values for the two models.
Q2) The adjusted R<sup>2</sup> adjusts R<sup>2</sup> for:
A) non-linearity
B) outliers
C) low correlation
D) the number of explanatory variables in a multiple regression model
Q3) In reference to the equation \[\hat { Y } = - 0.70 + 0.10 X\] ,the value 0.10 is the expected change in Y per unit change in X.
A)True
B)False
Q4) Refer to Exhibit 13-1.Estimate a simple linear regression model involving shipping cost and package weight.Interpret the slope coefficient of the least squares line as well as R<sup>2</sup>.
Q5) The least squares line is the line that minimizes the sum of the residuals.
A)True
B)False
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Chapter 14: Data Mining
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Q1) The primary advantage of neural networks is that they provide more accurate predictions,especially when the relationships are linear.
A)True
B)False
Q2) See Exhibit 14-2 Using Palisade's NeuralTools and the results from the prior problem,use the prediction data in this table to classify these 25 people as having been diagnosed with an illness or not.
Q3) The K-Means clustering algorithm :
A) becomes an optimization model for choosing the best cluster centers.
B) determines the best value of K.
C) has an objective that maximizes the sum of the dissimilarity measures.
D) cannot be directly implemented in Excel.
Q4) If the probability of a restaurant being successful is 10% then the odds of it failing are 10 to 1.
A)True
B)False
Q5) See Exhibit 14.1 - How well can logistic regression classify the people as having the illness or not
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