Management Science
Exam Solutions
Course Introduction
Management Science is a multidisciplinary field that applies quantitative, analytical, and systematic approaches to decision-making and problem-solving within organizations. This course introduces students to fundamental concepts and tools such as linear programming, simulation, decision analysis, forecasting, and optimization techniques. By focusing on real-world business scenarios, it equips students with the skills to analyze complex situations, allocate resources efficiently, and develop strategies that improve organizational performance. Throughout the course, students learn to integrate mathematical models with managerial insights, fostering a holistic approach to tackling contemporary management challenges.
Recommended Textbook
Practical Management Science 5th Edition by
Wayne L. Winston
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14 Chapters
421 Verified Questions
421 Flashcards
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Page 2
Chapter 1: Introduction to Modeling
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Sample Questions
Q1) The most frequent cause of a failed implementation of a model is:
A)the model is incorrect
B)the analyst fails to communicate how to use the model
C)the data for the model is unavailable
D)the model is too complex
Answer: B
Q2) Which of the following is not necessarily a property of a good model?
A)The model represents the client's real problem accurately
B)The model is as simple as possible
C)The model is based on a well-known algorithm
D)The model is one the client can understand
Answer: C
Q3) The overall modeling process typically done in practice always requires seven steps: define the problem, collect and summarize data, develop a model, verify the model, select one or more suitable decisions, present the results to the organization, and finally implement the model and update it through time.
A)True
B)False
Answer: False
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Page 3
Chapter 2: Introduction to Spreadsheet Modeling
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Sample Questions
Q1) Goal Seek is a means for answering a large number of what-if questions quickly and easily.
A)True
B)False
Answer: False
Q2) Many models are built for the purpose of permitting experimentation with various scenarios.
A)True
B)False
Answer: True
Q3) Which of the following is not one of the required arguments for a VLOOKUP function?
A)The lookup table range
B)The value you want to compare to the values in the left column of the table
C)The index of the column you want the returned value to come from
D)TRUE (for an approximate match) or FALSE (for an exact match)
Answer: D
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Chapter 3: Introduction to Optimization Modeling
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Sample Questions
Q1) The condition of nonnegativity requires that:
A)the objective function cannot be less that zero
B)the decision variables cannot be less than zero
C)the right hand side of the constraints cannot be greater then zero
D)the reduced cost cannot be less than zero
Answer: B
Q2) If the objective function has the equation {4x + 2y}, then the slope of the objective function line is 2.
A)True
B)False
Answer: True
Q3) The feasible region in a graphical solution of a linear programming problem will appear as some type of polygon, with lines forming all sides.
A)True
B)False
Answer: True
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Chapter 4: Linear Programming Models
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31 Verified Questions
31 Flashcards
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Sample Questions
Q1) In aggregate planning models, which of the following statements are correct?
A)The number of workers available influences the possible production levels
B)We allow the workforce level to be modified each month through the hiring and firing of workers
C)We eventually allow demand to be backlogged; that is, demand need not be met on time
D)All of these options
Q2) The constraints in a blending problem can be specified in a valid way and still lead to which of the following problems?
A)Unboundedness
B)Infeasibility
C)Nonlinearity
D)None of these options
Q3) Refer to Exhibit 4-2. Determine the optimal staffing plan for the project.
Q4) When a workforce scheduling problems is formulated as an integer programming model, it has:
A)an integer objective function
B)integer decision variables
C)integer constraints
D)all of these options
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Chapter 5: Network Models
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Sample Questions
Q1) In transportation problems, shipments between supply points or between demand points are possible.
A)True
B)False
Q2) The graphical representation of a network in an optimization problem can be an aid in the development of a spreadsheet model.
A)True
B)False
Q3) In an assignment model of machines to jobs, the machines are analogous to which of the following in a transportation problem?
A)Suppliers
B)Customers
C)Flows
D)Unit capacities
Q4) In an optimized shipping plan, most of the shipments occur on the low-cost routes, but this is not always the case.
A)True
B)False
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Page 7
Chapter 6: Optimization Models With Integer Variables
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Sample Questions
Q1) Many inherently nonlinear problems can be transformed into linear models with the use of:
A)integer variables
B)integer constraints
C)binary variables
D)binary constraints
Q2) 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
Q3) Refer to Exhibit 6-1. Suppose she can save $400 by renting a smaller truck, which has only 800 cubic feed of capacity. Would she be better off with the smaller truck?
Q4) If Solver fails to find an optimal solution to an integer programming problem, we might be able to find a near optimal solution by specifying a smaller number for the integer optimality setting.
A)True
B)False
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8
Chapter 7: Nonlinear Optimization Models
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Sample Questions
Q1) [Part 2] Refer to Exhibit 7-3. Formulate a nonlinear optimization model to find the parameters of a function of the form: f(x) = a(1 e bx) to model demand for its product as a function of ad exposures (x). In terms of fit, is this model better or worse than the model in Part 1? Explain your answer
Q2) 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
Q3) If a convex function is multiplied by a negative constant, the result:
A)is convex
B)is concave
C)could be either convex or concave, depending on the value of the constant D)is linear
Q4) Refer to Exhibit 7-1. Suppose the company is required by regulation to charge the same price for both products. How many units of each product should the company produce in that case? What prices should it charge, to maximize profit?
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Page 9
Chapter 8: Evolutionary Solver: An Alternative Optimization
Procedure
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Sample Questions
Q1) In Evolutionary Solver, the initial population is chosen randomly, so the starting solution you enter in the changing cells is irrelevant.
A)True
B)False
Q2) Refer to Exhibit 8-3. Write out your model and interpret your results. Do the results make sense?
Q3) A traveling salesman problem with a starting city and 10 other cities that must be visited has 1,826,800 possible solutions.
A)True
B)False
Q4) Refer to Exhibit 8-4. Suppose Steve moves to Los Angeles. What is the shortest distance in this case?
Q5) Crossovers are rare as a genetic algorithm is generating chromosomes for the next generations.
A)True
B)False
Q6) 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) 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?
Q2) Refer to Exhibit 9-1. Suppose the farmer is uncertain about the reliability of the National Weather Service forecast. If he thinks the probability of a freeze occurring could be anywhere between 40% and 80%, would that change his decision?
Q3) Bayes' rule is used to:
A)update the prior probabilities once new information is observed.
B)turn the given conditional probabilities (i.e. likelihoods) around.
C)update the posterior probabilities once new information is observed.
D)All of the above are uses for Bayes' rule.
Q4) Refer to Exhibit 9-1. Construct a risk profile and from that determine the probability that no additional cost is incurred if the decision to insulate at a cost of $20,000 is made.
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Chapter 10: Introduction to Simulation Modeling
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Sample Questions
Q1) Refer to Exhibit 10-2. Suppose the jacket sales price also varies, depending on the individual retailers and their pricing strategies. Assume that sales price is normally distributed with a mean of $65 per unit and a standard deviation of $10. How much revenue will the jacket line produce (ignore discounting)?
Q2) The RAND() function in excel models which of the following probability distributions?
A)Normal(0,1)
B)Uniform(0,1)
C)Normal( 1,1)
D)Uniform( 1,1).
Q3) Refer to Exhibit 10-2. Finally, suppose the apparel company receives an uncertain fraction of the total retail revenue from its retailers, modeled as a Triangular(0.70,0.75,0.80) distribution, and then must subtract production and operations costs, which are modeled as a Lognormal distribution with mean of $1,000,000 and standard deviation of $300,000. In that case, what is the expected net profit from the jacket line?
Q4) 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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Sample Questions
Q1) A tornado chart lets us see which random input has the most effect on a specified output in a financial model.
A)True
B)False
Q2) In warranty cost models, the key input random variable is product lifetime.
A)True
B)False
Q3) A common distribution for modeling product lifetimes is the normal distribution
A)True
B)False
Q4) 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
Q5) [Part 6] Refer to Exhibit 11-1. Given your answers to Parts 1 through 5, would you invest in this project?
Q6) [Part 3] Refer to Exhibit 11-2. Briefly explain why designing the plant for the expected capacity is clearly not the optimal solution.
Page 13
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Chapter 12: Inventory and Supply Chain Models
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Sample Questions
Q1) Refer to Exhibit 12-3. Suppose again that 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. However, this time, formulate a Solver model to find the optimal (R,Q) policy to ensure that at least 99% of customer demands are met with existing inventory. What is the policy, and what is the total annual cost in that case?
Q2) Which of the following is not one of the important issues in inventory models?
A)Whether demand is generated internally or externally
B)Whether the company orders the products it needs from a supplier or produces them internally
C)Whether the inventory is stored onsite or offsite
D)Whether inventory is reviewed continuously or periodically
Q3) Refer to Exhibit 12-2. Assuming there are no storage costs, formulate a Solver model and find the optimal order quantity.
Q4) The time it takes for an order to arrive at facility is called the stockout time.
A)True B)False
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Page 14
Chapter 13: Queuing Models
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Sample Questions
Q1) As the traffic intensity approaches 1:
A)there is no waiting
B)waiting lines stabilize
C)waiting lines grow extremely rapidly
D)at least one server will be idle
Q2) Refer to Exhibit 13-3. What percentage of all customers have to spend at least some small amount of time waiting in line?
Q3) Refer to Exhibit 13-3. What is the average length of the waiting line?
Q4) The server utilization U in an M/M/s system is always the same as the traffic intensity. A)True
B)False
Q5) Refer to Exhibit 13-4. What percentage of customers do not wait in the queue?
Q6) [Part 3] Refer to Exhibit 13-1. Again assuming an exponential distribution with the parameter you obtained in Part 2, what is the probability that a customer interarrival time will be more than 2 minutes, but less than 5 minutes?
Q7) [Part 1] Refer to Exhibit 13-1. Is it reasonable to assume exponentially distributed interarrival times for the grocery store customers? If so, what is ?
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Chapter 14: Regression and Forecasting Models
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Sample Questions
Q1) A time series can consist of four different components: trend, seasonal, cyclical, and random (or noise).
A)True
B)False
Q2) When using the moving average method, you must select ____ which represent(s) the number of terms in the moving average.
A)a smoothing constant
B)the explanatory variables
C)an alpha value
D)a span
Q3) The least squares line is the line that minimizes the sum of the residuals.
A)True
B)False
Q4) Refer to Exhibit 14-3. Use a moving average model to forecast these data, requesting 4 quarters of future forecasts. Use a span of 4 quarters.
Q5) Refer to Exhibit 14-2. Interpret each of the estimated regression coefficients of the regression model above.
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Page 16