Course Introduction
Management Science
Chapter Exam Questions
Management Science is an interdisciplinary field that applies quantitative analysis, statistical methods, and mathematical modeling to solve complex organizational problems and support effective decision-making. By integrating techniques from operations research, economics, and information systems, the course equips students with tools to analyze data, optimize processes, allocate resources, and assess risks. Through case studies and practical applications, students learn to develop and implement systematic approaches for improving efficiency, productivity, and competitiveness in areas such as supply chain management, project planning, and strategic management.
Recommended Textbook
Managerial Decision Modeling 6th International Edition by Cliff T. Ragsdale
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Page 2
Chapter 1: Introduction to Modeling and Decision Analysis
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Q1) Identifying the real problems faced by the decision maker
A)is not important since the decision maker has already defined the problem.
B)requires insight, some imagination, time and a good bit of detective work.
C)first requires a well-defined problem statement.
D)will lead to developing the best model.
Answer: B
Q2) In which step of the problem-solving process is the main focus to generate and evaluate alternatives?
A)Identify problem
B)Formulate model
C)Use model to analyze problem
D)Test results
Answer: C
Q3) In a decision-making framework presented in Chapter One, the term "poetic justice" refers to a situation when the following occur:
A)Good decision quality and good outcome quality.
B)Good decision quality and bad outcome quality.
C)Bad decision quality and good outcome quality.
D)Bad decision quality and bad outcome quality.
Answer: D
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Chapter 2: Introduction to Optimization and Linear Programming
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Q1) Level curves are used when solving LP models using the graphical method. To what part of the model do level curves relate?
A)constraints
B)boundaries
C)right hand sides
D)objective function
Answer: D
Q2) Which of the following is the general format of an objective function?
A)f(X<sub>1</sub>, X<sub>2</sub>, ..., X<sub>n</sub>) \(\le\)b
B)f(X<sub>1</sub>, X<sub>2</sub>, ..., X<sub>n</sub>) \(\ge\) b
C)f(X<sub>1</sub>, X<sub>2</sub>, ..., X<sub>n</sub>) = b
D)f(X<sub>1</sub>, X<sub>2</sub>, ..., X<sub>n</sub>)
Answer: D
Q3) A mathematical programming application employed by a shipping company is most likely
A)a product mix problem.
B)a manufacturing problem.
C)a routing and logistics problem.
D)a financial planning problem.
Answer: C
Page 4
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Chapter 3: Modeling and Solving Lp Problems in a Spreadsheet
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Sample Questions
Q1) A company needs to purchase several new machines to meet its future production needs. It can purchase three different types of machines A, B, and C. Each machine A costs $80,000 and requires 2,000 square feet of floor space. Each machine B costs $50,000 and requires 3,000 square feet of floor space. Each machine C costs $40,000 and requires 5,000 square feet of floor space. The machines can produce 200, 250 and 350 units per day respectively. The plant can only afford $500,000 for all the machines and has at most 20,000 square feet of room for the machines. The company wants to buy as many machines as possible to maximize daily production.
Formulate the LP for this problem.
Answer: 11ea68ee_b833_5bc4_b0a4_63565ab91757_TB5443_00
Q2) The constraints X<sub>1</sub> \(\ge\) 0 and X<sub>2</sub> \(\ge\)0 are referred to as
A)positivity constraints.
B)optimality conditions.
C)left hand sides.
D)nonnegativity conditions.
Answer: D
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Page 5
Chapter 4: Sensitivity Analysis and the Simplex Method
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Q1) A change in the right hand side of a constraint changes
A)the slope of the objective function
B)objective function coefficients
C)other right hand sides
D)the feasible region
Q2) When the allowable increase or allowable decrease for the objective function coefficient of one or more variables is zero it indicates (in the absence of degeneracy) that
A)the problem is infeasible.
B)alternate optimal solutions exist.
C)there is only one optimal solution.
D)no optimal solution can be found.
Q3) The allowable increase for a constraint is
A)how many more units of resource to purchase to maximize profits.
B)the amount by which the resource can increase given shadow price.
C)how much resource to use to get the optimal solution.
D)the amount by which the constraint coefficient can increase without changing the final optimal value.
Q4) Refer to Exhibit 4.1. Should the company negotiate for additional air delivery capacity?
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Chapter 5: Network Modeling
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Q1) The right hand side value for the starting node in a shortest path problem has a value of A)-1
B)0
C)1
D)2
Q2) Supply quantities for supply nodes in a transshipment problem are customarily indicated by
A)positive numbers.
B)negative numbers.
C)imaginary numbers.
D)either positive or negative numbers.
Q3) Which method is preferred for solving fully connected transportation problems?
A)linear programming
B)network flow methods
C)trial and error
D)simulation
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Page 7
Chapter 6: Integer Linear Programming
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Sample Questions
Q1) How are general integrality requirements indicated in the Excel Risk Solver Platform (RSP)?
A)Specifying the INT option for the appropriate changing cells.
B)Specifying the INT option for the constraint rows.
C)Adding additional RHS values to constraints.
D)Choosing the BIN setting in the Value field in the Solver Parameters dialog box.
Q2) One approach to solving integer programming problems is to ignore the integrality conditions and solve the problem with continuous decision variables. This is referred to as
A)quickest solution method.
B)LP satisficing.
C)LP relaxation.
D)LP approximation.
Q3) Refer to Exhibit 6.2. What formula would go into cells B11:E11 and cells F8:F10?
Q4) What are binary integer variables?
A)Variables with any two values, a and b
B)Variables with values 0 and 1.
C)Variables whose sum of digits is 2.
D)Variables with values between 0 and 1.
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Chapter 7: Goal Programming and Multiple Objective Optimization
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Q1) Refer to Exhibit 7.4. The spreadsheet model has scaled all the weights from pounds into 100s pounds. How does this scaling effect the solution obtained using the Risk Solver Platform (RSP)?
Q2) If no other feasible solution to a multi-objective linear programming (MOLP) problem allows an increase in any objective without decreasing at least one other objective, the solution is said to be A)dually optimal.
B)Pareto optimal.
C)suboptimal.
D)maximally optimal.
Q3) Refer to Exhibit 7.1. If the company is very concerned about going over the $200,000 budget, which cell value should change and how should it change?
A)D13, increase
B)D13, decrease
C)D14, increase
D)D14, decrease
Q4) Refer to Exhibit 7.4. Given the solution indicated in the spreadsheet, which trucks, if any, are under an equal weight amount, and which trucks are over an equal weight amount?
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Chapter 8: Nonlinear Programming and Evolutionary Optimization
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Sample Questions
Q1) In the GRG algorithm the initial solution is called the
A)originating point.
B)insertion point.
C)zero point.
D)starting point.
Q2) The GRG algorithm operates by
A)moving in the direction of most rapid improvement in the objective function.
B)choosing a search direction at random.
C)searching directly for the optimum solution.
D)moving in a clockwise direction.
Q3) The Reduced Gradient is similar to which of these terms from linear programming?
A)Shadow Price
B)Allowable Decrease
C)Allowable Increase
D)Reduced Cost
Q4) The total annual cost for the economic order quantity model is
A)purchase cost + ordering cost + holding cost.
B)fixed ordering cost + holding cost.
C)purchase cost + fixed ordering cost.
D)unit cost + variable ordering cost + holding cost.
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Chapter 9: Regression Analysis
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Q1) The terms b<sub>0</sub> and b<sub>1</sub> are
A)estimated population parameters.
B)estimated intercept and slope values, respectively.
C)random variables.
D)all of these.
Q2) The terms \(\beta\)<sub>0</sub> and \(\beta\)<sub>1</sub> are referred to as
A)sample statistics
B)random variables
C)population variables
D)population parameters
Q3) Refer to Exhibit 9.1. Interpret the meaning of R Square in cell B3 of the spreadsheet.
Q4) Refer to Exhibit 9.1. What is the estimated regression function for this problem? Explain what the terms in your equation mean.
Q5) Refer to Exhibit 9.3. What is the estimated regression function for this problem? Explain what the terms in your equation mean
Q6) Refer to Exhibit 9.1. Test the significance of the model and explain which values you used to reach your conclusions.
Q7) Refer to Exhibit 9.7. What is the SS for Total?
Page 11
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Chapter 10: Discriminant Analysis
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Q1) Refer to Exhibit 10.1. What is the verbal test score value of the group centroid for group 2?
A)683.8
B)654.2
C)610.7
D)605.7
Q2) Refer to Exhibit 10.4. What is the percentage of observations:
a.Correctly classified to a Group?
b.Incorrectly classified to a Group?
c.Correctly classified to Group 1?
d.Correctly classified to Group 2?
Q3) Refer to Exhibit 10.1. What is the quantitative test score value of the group centroid for group 1?
A)683.8
B)654.2
C)610.7
D)605.7
Q4) Refer to Exhibit 10.7. What formulas should go in cells C22:D24 of the spreadsheet?
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Chapter 11: Time Series Forecasting
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Q1) Refer to Exhibit 11.15. What formulas should go in cells C5:C16 of the spreadsheet if Bill uses a 2 month weighted moving average forecasting model?
Q2) Refer to Exhibit 11.10. What are predicted sales for the fourth quarter of year 4?
A)1170 \(\le\) predicted sales < 1175
B)1310 \(\le\) predicted sales < 1315
C)1460 \(\le\) predicted sales < 1465
D)1615 \(\le\) predicted sales < 1620
Q3) Refer to Exhibit 11.8. What formula should be entered in cell H7 to compute the
Predicted Sales value for year 2 Quarter 1?
A)=SUM(E6:F6)*G3
B)=SUM(E6:F6)+G3
C)=SUM(E6:F6)
D)=SUM(E6:G3)
Q4) Refer to Exhibit 11.22. Based on the regression output, what formulas should go in cells E3:E14?
Q5) Refer to Exhibit 11.25. What is the forecast for time period 13?
Q6) Refer to Exhibit 11.15. What is the forecast for time period 13-15?
Q7) Refer to Exhibit 11.21. What is the forecast for time period 13?
Page 13
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Chapter 12: Introduction to Simulation Using Risk Solver Platform
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Q1) What function should be used for generating random integer numbers between 2 and 8?
Q2) Which of the following distributions can be generated by Risk Solver Platform (RSP)?
A)Poisson
B)Normal
C)Weibull
D)All of these
Q3) Using the information in Exhibit 12.3, what Risk Solver Platform (RSP) function should be used for generating a random shipping time based on the Data spreadsheet distribution for shipping time?
A)=PsiCumul($B$6:$C$8)
B)=PsiCustom($B$6:$B$8, $C$8:$C$8)
C)=PsiGeneral(Data!$B$6, probability $C$8)
D)=PsiDiscrete($B$6:$B$8, $C$8:$C$8)
Q4) Inventory position is defined as
A)ending inventory + outstanding orders
B)ending inventory - backorders
C)outstanding orders - on hand inventory
D)ending inventory
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Chapter 13: Queuing Theory
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Q1) To find steady-state values for the M/M/S queuing system, which of the following statements must be true about the arrival rate?
A)\(\lambda\) < s \(\mu\)
B)\(\lambda\)- s = \(\mu\)
C)\(\lambda\) > s \(\mu\)
D)\(\lambda\)= s \(\mu\)
Q2) Which of the following best describes queuing theory?
A)The study of arrival rates.
B)The study of service times.
C)The study of waiting lines.
D)The evaluation of service time costs.
Q3) The amount of time a customer spends with the server is referred to as
A)system time.
B)queue time.
C)service time.
D)served time.
Q4) Customers arrive at a store randomly, following a Poisson distribution at an average rate of 20 per hour. What is the probability of exactly 0, 1 2, and 3 arrivals in a 15 minute period?
Q5) Refer to Exhibit 13.7. What is the Kendall notation for this system?
Page 15
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Chapter 14: Decision Analysis
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Q1) Refer to Exhibit 14.8. What formula should go in cell F11 and get copied to F12:F13 of the Price worksheet to compute the Price Score?
A)=AVERAGE(C4:C6)
B)=AVERAGE(C11:E11)
C)=AVERAGE(G11:G13)
D)=AVERAGE(C7:E7)
Q2) Decision Analysis techniques provide modeling techniques to help decision makers make decisions. Which of the following is not typically a benefit of decision analysis?
A)Incorporating uncertainty via probabilities.
B)Incorporating risk via utility theory functions.
C)Incorporating uncertainty via exponential distributions.
D)Structuring decision strategies via decision trees.
Q3) What is the formula for the exponential utility function U(x)?
A)-e<sup>-</sup><sup>x/R</sup>
B)1 + e<sup>-</sup><sup>x/R</sup>
C)1 - e<sup>x/R</sup>
D)1 - e1<sup>-</sup><sup>x/R</sup>
Q4) Refer to Exhibit 14.11. What formula should go in cell C13 of the probability table?
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Chapter 15: Project Management Online
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Q1) Refer to Exhibit 15.2. Which of the following activities is not on the critical path for the network?
A)Activity A
B)Activity C
C)Activity D
D)Activity G
Q2) The purpose of the backward pass in the Critical Path Method (CPM) technique is to
A)review each of the precedence relationships in the activity network.
B)calculate the slack time within each node on the activity network.
C)determine the earliest time each activity can start and finish.
D)determine the latest time each activity can start and finish.
Q3) The critical path in PERT analysis is the path with the A)smallest variance.
B)longest expected completion time.
C)smallest number of tasks.
D)smallest variance and longest expected completion time.
Q4) Refer to Exhibit 15.6. Is it necessary to draw an arc from the node for activity F to the node for activity I?
Q5) Refer to Exhibit 15.3. Draw the CPM network for this problem. Use AON notation.
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