Decision Modeling Final Exam
Course Introduction
Decision Modeling explores quantitative methods and analytical frameworks used to support decision-making in complex, uncertain environments. The course covers fundamental concepts such as optimization, simulation, risk analysis, and spreadsheet modeling, equipping students with practical tools to structure and solve real-world business problems. Through hands-on exercises and case studies, students learn to construct models that facilitate data-driven reasoning, evaluate alternatives, and optimize outcomes based on organizational objectives. Emphasis is placed on interpreting model results and communicating insights effectively to stakeholders.
Recommended Textbook
Managerial Decision Modeling 6th International Edition by Cliff T. Ragsdale
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15 Chapters
1113 Verified Questions
1113 Flashcards
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Chapter 1: Introduction to Modeling and Decision Analysis
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Sample Questions
Q1) A mathematical model is considered to be "valid" when
A)it accurately represents the relevant characteristics of the object or decision.
B)it has passed a validation test.
C)it replicates all aspects of the object or decision.
D)the left-hand and right-hand sides of expressions are equal.
Answer: A
Q2) The goal of the modeling approach to problem solving is to
A)Help individuals make good decisions.
B)Ensure optimality of decisions.
C)Determine a set of optimal decisions.
D)Determine feasibility of decisions.
Answer: A
Q3) A purely rational decision maker should
A)Consistently select the same alternative, regardless of how the problem is framed.
B)Disregard the consequences of his/her choices.
C)Always select optimal action.
D)Allow emotions influence the decision.
Answer: A
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3
Chapter 2: Introduction to Optimization and Linear Programming
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Sample Questions
Q1) 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
Q2) A diet is being developed which must contain at least 100 mg of vitamin C. Two fruits are used in this diet. Bananas contain 30 mg of vitamin C and Apples contain 20 mg of vitamin C. The diet must contain at least 100 mg of vitamin C. Which of the following constraints reflects the relationship between Bananas, Apples and vitamin C?
A)20 A + 30 B \(\ge\) 100
B)20 A + 30 B \(\le\) 100
C)20 A + 30 B = 100
D)20 A = 100
Answer: A
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Chapter 3: Modeling and Solving Lp Problems in a Spreadsheet
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Sample Questions
Q1) Refer to Exhibit 3.3. What formula should be entered in cell D11 in the accompanying Excel spreadsheet to compute the total liters of alcohol supplied?
A)=B4*B5+C4*C5
B)=SUMPRODUCT(B11:C11,$B$4:$C$4)
C)=SUM(B5:C5)
D)=SUM(E8:E10)
Answer: B
Q2) Scaling problems
A)can cause Risk Solver Platform (RSP) to consider a linear problem as nonlinear.
B)can cause problems in accuracy of solutions returned.
C)are caused by small numbers and large numbers used in the same problem.
D)all of these.
Answer: D
Q3) Which type of spreadsheet cell represents the objective function in an LP model?
A)Objective cell
B)Changing variable cell
C)Constraint cell
D)Constant cell
Answer: A
Page 5
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Chapter 4: Sensitivity Analysis and the Simplex Method
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Sample Questions
Q1) A change in the right hand side of a binding constraint may change all of the following except
A)optimal value of the decision variables
B)slack values
C)other right hand sides
D)objective function value
Q2) The solution to an LP problem is degenerate if
A)the right hand sides of any of the constraints have an allowable increase or allowable decrease of zero.
B)the shadow prices of any of the constraints have an allowable increase or allowable decrease of infinity.
C)the objective coefficients of any of the variables have an allowable increase or allowable decrease of zero.
D)the shadow prices of any of the constraints have an allowable increase or allowable decrease of zero.
Q3) Refer to Exhibit 4.2. Constraint cell F9 corresponds to the constraint, W<sub>1</sub> + W<sub>2</sub> + W<sub>3</sub> + W<sub>4</sub> = 1, and has a shadow price of 75.
Armed with this information, what can Robert request of his instructor regarding this constraint?
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Page 6
Chapter 5: Network Modeling
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Sample Questions
Q1) When might a network flow model for a transportation/assignment problem be preferable to a matrix form for the problem?
A)When an integer solution is required.
B)When the problem is large and not fully connected.
C)When the problem is large and fully connected.
D)When supply exceeds demand.
Q2) Decision variables in network flow problems are represented by A)nodes.
B)arcs.
C)demands.
D)supplies.
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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Chapter 6: Integer Linear Programming
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Sample Questions
Q1) A company will be able to obtain a quantity discount on component parts for its three products, X<sub>1</sub>, X<sub>2</sub> and X<sub>3</sub> if it produces beyond certain limits. To get the X<sub>1</sub> discount it must produce more than 50 X<sub>1</sub>'s. It must produce more than 60 X<sub>2</sub>'s for the X<sub>2</sub> discount and 70 X<sub>3</sub>'s for the X<sub>3</sub> discount. Which of the following pair of constraints enforces the quantity discount relationship on X<sub>3</sub>?
A)X<sub>31</sub> \(\le\) M<sub>3</sub>Y<sub>3</sub>, X<sub>32</sub> \(\ge\)50Y<sub>3</sub>
B)X<sub>31</sub> \(\le\)M<sub>3</sub>Y<sub>3</sub>, X<sub>31</sub> \(\ge\) 50
C)X<sub>32</sub>\(\ge\) (1/50)X<sub>31</sub>, X<sub>31</sub> \(\le\)50
D)X<sub>32</sub> \(\le\) M<sub>3</sub>Y<sub>3</sub>, X<sub>31</sub> \(\ge\)50Y<sub>3</sub>
Q2) The optimal relaxed solution for an ILP has X<sub>1</sub> = 3.6 and X<sub>2</sub> = 2.9. If we branch on X<sub>1</sub>, what constraints must be added to the two resulting LP problems?
A)X<sub>1</sub>\(\ge\) 3, X<sub>1</sub> \(\ge\) 4
B)X<sub>1</sub> = 4
C)3\(\le\) X<sub>1</sub>, X<sub>1</sub> \(\le\) 4
D)X<sub>1</sub> \(\le\)3, X<sub>1</sub> \(\ge\) 4
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Page 8
Chapter 7: Goal Programming and Multiple Objective
Optimization
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Sample Questions
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) Goal programming solution feedback indicates that the d<sub>4</sub><sup>+</sup> level of 50 should not be exceeded in future solution iterations. How should you modify your goal constraint 40 X<sub>1 </sub>+ 20 X<sub>2</sub> + d<sub>4</sub><sup>-</sup>+ d<sub>4</sub><sup>+</sup> = 300
To accommodate this requirement?
A)Increase the RHS value from 300 to 350.
B)Replace the constraint with 40 X<sub>1 </sub>+ 20 X<sub>2</sub> \(\le\) 350.
C)Do not modify the constraint, add a constraint d<sub>4</sub><sup>+</sup> \(\le\)50.
D)Do not modify the constraint, add a constraint d<sub>4</sub><sup>+</sup> = 50.
Q3) Refer to Exhibit 7.2. Which cells are the changing cells in this model?
A)$B$6:$C$6, $B$10:$B$11
B)$B$6:$C$6
C)$B$6:$D$6
D)$B$10:$B$11
Q4) Refer to Exhibit 7.4. What formulas should go in cell E26 of the spreadsheet?
Page 9
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Chapter 8: Nonlinear Programming and Evolutionary Optimization
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Sample Questions
Q1) The Lagrange Multiplier is similar to which of these terms from linear programming?
A)Shadow Price
B)Allowable Increase
C)Allowable Decrease
D)Reduced Cost
Q2) Refer to Exhibit 8.1. What formula is used in cell D12 of the spreadsheet for this problem?
A)=SUMPRODUCT(B3:C3, B12:C12)
B)=SUMPRODUCT(B4:C4, B12:C12)
C)=SUMPRODUCT(B5:C5, B12:C12)
D)=SUMPRODUCT(B7:C7, B12:C12)
Q3) An office supply company is attempting to determine the order quantity for Mt. White fountain pens which are sold to local executives. Annual demand is 5,000 units and each pen costs the store $50. It costs $75 to place an order and the inventory carrying cost rate is 30% of the value of the item.
Formulate the objective function for this problem. Let Q indicate the order quantity.
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Page 10
Chapter 9: Regression Analysis
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Sample Questions
Q1) Refer to Exhibit 9.2. What is the estimated regression function for this problem? Explain what the terms in your equation mean.
Q2) Refer to Exhibit 9.2. Interpret the meaning of the "Lower 95%" and "Upper 95%" terms in cells F16:G16 of the spreadsheet.
Q3) The terms b<sub>0</sub> and b<sub>1</sub> are referred to as
A)population variables.
B)population parameters.
C)estimated population variables.
D)estimated population parameters.
Q4) The actual value of a dependent variable will generally differ from the regression equation estimate due to A)unaccounted for random variation.
B)the inability of the nonlinear Solver to find optimal values.
C)not building the regression model with enough data.
D)the model R<sup>2</sup> not equal to 1.
Q5) Refer to Exhibit 9.3. Interpret the meaning of R square in cell B3 of the spreadsheet.
Q6) Refer to Exhibit 9.1. Predict the mean number of labor hours for a batch of 5 parts.
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Page 11
Chapter 10: Discriminant Analysis
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Sample Questions
Q1) 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
Q2) Refer to Exhibit 10.1. Suppose that for a given observation, the difference between Mahalanobis distances between group 1 and 2 (G1-G2) is small. This means that
A)The observation is likely to be classified incorrectly
B)The observation is likely to be classified correctly
C)The observation is unlikely to be classified
D)The observation should be deleted from the data set
Q3) Discriminant analysis (DA) differs from most other predictive statistical methods because the dependent variable is
A)continuous
B)random
C)stochastic
D)discrete
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Chapter 11: Time Series Forecasting
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Sample Questions
Q1) Refer to Exhibit 11.9. Which column in the spreadsheet represents the independent variable for a regression model?
A)A
B)B
C)C
D)D
Q2) Refer to Exhibit 11.12. What is the Input Y Range in the Regression command settings dialog box?
A)$C$3:$C$14
B)$H$3:$H$14
C)$C$3:$G$14
D)$H$3:$I$14
Q3) Refer to Exhibit 11.6. What formula should be entered in cell F9 to compute the second average when using the double moving average method with k = 4?
A)=Average($E$3:$E$9)
B)=Average($D$3:$D$9)
C)=Average(D3:D9)
D)=Average(D6:D9)
Q4) Refer to Exhibit 11.21. What formulas should go in cells E3:H16?
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Chapter 12: Introduction to Simulation Using Risk Solver
Platform
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65 Flashcards
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Sample Questions
Q1) Using the information in Exhibit 12.1, what Risk Solver Platform (RSP) function should go in cell C8 and copied to cells C9:C19 to compute the average damage per car in the month?
A)=PsiNormal($C$3*$F$3^$A$8, $H$3)
B)=PsiNormal($C$3*$F$3^A8, $H$3)
C)=PsiNormal($C$3, $D$3*(1+$F$3)^A8)
D)=PsiNormal($C$3*(1+$F$3)^A8, $H$3)
Q2) Using the information in Exhibit 12.3, what formula should go in cell J8 to determine the arrival date for an order?
A)=IF(I8=0,0,A8+I8)
B)=IF(I8=0,0,A8+1+I8)
C)=IF(I8=1,0,A8+1+I8)
D)=IF(I8=0,A8+1+I8,0)
Q3) Using the information in Exhibit 12.4, what Risk Solver Platform (RSP) function should be used in cell C10 to determine the number of Passengers to Board?
A)=PsiBinomial($C$8, 1-$C$6)
B)=PsiBinomial(1-$C$6, $C$8)
C)=PsiBinomial($C$8, $C$6)
D)=PsiBinomial($C$6, $C$8)
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Chapter 13: Queuing Theory
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Sample Questions
Q1) Which type of queuing system are you likely to encounter at a grocery store?
A)Single waiting line, single service station.
B)Multiple waiting lines, single service station.
C)Single waiting line, multiple service stations.
D)Multiple waiting lines, multiple service stations.
Q2) Refer to Exhibit 13.2. Based on this report what is the average total time spent waiting for a haircut and getting a haircut?
Q3) Refer to Exhibit 13.4. What is the Kendall notation for this system?
Q4) Customers arrive at a store randomly, following a Poisson distribution at an average rate of 90 per hour. How many customers arrive per minute, on average?
Q5) The M in M/G/1 stands for
A)Markovian inter-arrival times.
B)Mendelian inter-arrival times.
C)Mean inter-arrival times.
D)Mathematical inter-arrival times.
Q6) Refer to Exhibit 13.7. Based on this report what is the probability that a customer does not have to wait for assistance with his or her taxes?
Q7) Refer to Exhibit 13.7. What is the Kendall notation for this system?
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Chapter 14: Decision Analysis
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Sample Questions
Q1) The ____ correspond to future events that are not under the control of the decision maker.
A)payoffs
B)states of nature
C)criteria
D)alternatives
Q2) Refer to Exhibit 14.4. What formula should go in cell D14 of the spreadsheet to compute the EVPI?
A)MAX(D5:D8)-D12
B)D12-MIN(D5:D8)
C)SUMPRODUCT(B12:C12,B10:C10)-MAX(D5:D8)
D)D12-MAX(D5:D8)
Q3) Refer to Exhibit 14.9. What formula should go in cell D5 and get copied to D6:D8 to implement the maximax decision rule?
Q4) The ____ in a decision problem represent factors that are important to the decision maker.
A)payoffs
B)states of nature
C)criteria
D)alternatives
Page 16
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Chapter 15: Project Management Online
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Sample Questions
Q1) 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.
Q2) A weakness of Gantt charts is that they do not explicitly
A)indicate activity times.
B)show precedence relationships.
C)show activity start times.
D)show activity finish times.
Q3) Which of the following definitions correctly defines the acronym, PERT?
A)Program Evaluation and Review Technique.
B)Process Evaluation and Review Technique.
C)Program Evaluation and Reduction Technique.
D)Program Explanation and Reduction Technique.
Q4) Refer to Exhibit 15.4. Draw the CPM network for this problem. Use AON notation.
Q5) Refer to Exhibit 15.6. Is it necessary to draw an arc from the node for activity A to the node for activity C?
Q6) Refer to Exhibit 15.3. Draw the CPM network for this problem. Use AON notation.
Page 17
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