True / False
1. A nonlinear optimization problem is any optimization problem in which at least one term in the objective function or a constraint is nonlinear.
a. True
b. False
: True
POINTS: 1
DIFFICUL
...
True / False
1. A nonlinear optimization problem is any optimization problem in which at least one term in the objective function or a constraint is nonlinear.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Remember
2. A function is considered a quadratic function if its nonlinear terms have a power of 2.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Remember
3. Nonlinear programming algorithms are more complex than linear programming algorithms.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Remember
4. Many linear programming algorithms such as the simplex method optimize by examining only the extreme points and selecting the extreme point that gives the best solution value.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
5. Nonlinear optimization problems can have only one local optimal solution.
a. True
b. False
: False
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Remember
6. A feasible solution is a global optimum if no other feasible solutions with a better objective function value are found in the immediate neighborhood.
a. True
b. False
: False
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Remember
7. A feasible solution is a global optimum if no other feasible points with a better objective function value are found in the feasible region.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Remember
8. For a typical nonlinear problem, if you change the right-hand side by even a small amount, the dual value changes.
a. True
b. False
: False
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
9. The interpretation of the dual price for nonlinear models is different than the interpretation of the dual price for linear models.
a. True
b. False
: False
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Remember
10. In the case of functions with multiple local optima, most nonlinear optimization software methods can get stuck and terminate at a local optimum.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Remember
11. For a minimization problem, a point is a global minimum if there are no other feasible points with a smaller objective function value.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Remember
12. It is possible that a nonlinear application in which there is a single local optimal solution also shows that solution as the global optimal solution.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
13. Functions that are convex have a single local maximum that is also the global maximum.
a. True
b. False
: False
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
14. The function f (X, Y) = X 2 + Y 2 has a single global minimum and is relatively easy to minimize.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Moderate
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
15. The problem of maximizing a concave quadratic function over a linear constraint set is relatively difficult to solve.
a. True
b. False
: False
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
16. Each point on the efficient frontier is the maximum possible risk, measured by portfolio variance, for the given return.
a. True
b. False
: False
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.03 - 8.3
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.3 Markowitz Portfolio Model
KEYWORDS: Bloom's: Understand
17. Any feasible solution to a blending problem with pooled components is feasible to the problem with no pooling.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.04 - 8.4
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.4 Blending: The Pooling Problem
KEYWORDS: Bloom's: Understand
18. Any feasible solution to a blending problem without pooled components is feasible to the problem with pooled components.
a. True
b. False
: False
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.04 - 8.4
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.4 Blending: The Pooling Problem
KEYWORDS: Bloom's: Understand
19. When components (or ingredients) in a blending problem must be pooled, the number of feasible solutions is reduced.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.04 - 8.4
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.4 Blending: The Pooling Problem
KEYWORDS: Bloom's: Understand
20. The value of the coefficient of imitation, q, in the Bass model for forecasting adoption of a new product cannot be negative.
a. True
b. False
: False
POINTS: 1
DIFFICULTY: Moderate
LEARNING OBJECTIVES: IMS.ASWC.19.08.05 - 8.5
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.5 Forecasting Adoption of a New Product
KEYWORDS: Bloom's: Understand
21. The Markowitz mean-variance portfolio model presented in the text is a convex optimization problem.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.03 - 8.3
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.3 Markowitz Portfolio Model
KEYWORDS: Bloom's: Understand
22. Because most nonlinear optimization codes will terminate with a local optimum, the solution returned by the codes will be the best solution.
a. True
b. False
: False
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
23. It is possible for the optimal solution to a nonlinear optimization problem to lie in the interior of the feasible region.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
24. The minimum value for a convex function is 0, and the point (0, 0) gives the minimum value of 0.
a. True
b. False
: True
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
Multiple Choice
25. Which of the following statements is incorrect?
a. A global optimum is a local optimum in a nonlinear optimization problem.
b. A local maximum is a global maximum in a concave nonlinear optimization problem.
c. A global minimum is a local minimum in a convex nonlinear optimization problem.
d. A local optimum is a global optimum in a nonlinear optimization problem.
: d
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
26. The measure of risk most often associated with the Markowitz portfolio model is the portfolio
a. average return.
b. minimum return.
c. variance.
d. standard deviation.
: c
POINTS: 1
DIFFICULTY: Moderate
LEARNING OBJECTIVES: IMS.ASWC.19.08.03 - 8.3
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.3 Markowitz Portfolio Model
KEYWORDS: Bloom's: Understand
27. An investor can pick the mean-variance tradeoff that he or she is most comfortable with by looking at a graph of the
a. feasible region.
b. pooled components.
c. rolling horizon.
d. efficient frontier.
: d
POINTS: 1
DIFFICULTY: Moderate
LEARNING OBJECTIVES: IMS.ASWC.19.08.03 - 8.3
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.3 Markowitz Portfolio Model
KEYWORDS: Bloom's: Understand
28. The Bass model is used to forecast the adoption of a new product. Which of the following is NOT a parameter of this Bass model?
a. coefficient of innovation
b. coefficient of interaction
c. coefficient of imitation
d. estimated pool of current adopters
: b
POINTS: 1
DIFFICULTY: Moderate
LEARNING OBJECTIVES: IMS.ASWC.19.08.05 - 8.5
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.5 Forecasting Adoption of a New Product
KEYWORDS: Bloom's: Understand
29. When the number of blending components exceeds the number of storage facilities, the number of feasible solutions to the blending problem is
a. reduced.
b. increased.
c. unchanged.
d. zero.
: a
POINTS: 1
DIFFICULTY: Moderate
LEARNING OBJECTIVES: IMS.ASWC.19.08.04 - 8.4
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.4 Blending: The Pooling Problem
KEYWORDS: Bloom's: Understand
30. In the Bass model for forecasting the adoption of a new product, the objective function
a. minimizes the sum of forecast errors.
b. minimizes the sum of squared forecast errors.
c. maximizes the number of adoptions.
d. maximizes the number of adoptions and imitations.
: b
POINTS: 1
DIFFICULTY: Moderate
LEARNING OBJECTIVES: IMS.ASWC.19.08.05 - 8.5
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.5 Forecasting Adoption of a New Product
KEYWORDS: Bloom's: Understand
31. Which of the following is NOT true regarding a concave function?
a. It is bowl-shaped down.
b. It is relatively easy to maximize.
c. It has multiple local maxima.
d. It has a single global maximum.
: c
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
32. A convex function is
a. bowl-shaped up.
b. bowl-shaped down.
c. elliptical in shape.
d. sinusoidal in shape.
: a
POINTS: 1
DIFFICULTY: Easy
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Remember
33. If the coefficient of each squared term in a quadratic function is positive, the function is
a. concave.
b. convex.
c. elliptical.
d. sinusoidal.
: b
POINTS: 1
DIFFICULTY: Moderate
LEARNING OBJECTIVES: IMS.ASWC.19.08.01 - 8.1
NATIONAL STANDARDS: United States - BUSPROG: Reflective Thinking
TOPICS: 8.1 A Production Application—Par, Inc., Revisited
KEYWORDS: Bloom's: Understand
34. When components share a storage facility, they are called
a. constrained components.
b. correlated components.
c. blended components.
d. None of these are correct.
35. The key idea behind constructing an index fund is to choose a portfolio of securities that
a. is a mix of growth- and income-oriented stocks.
b. minimizes risk without sacrificing liquidity.
c. mimics the performance of a broad market index.
d. balances short- and long-term investments.
36. It is common that components that are referred to as pooled
a. are shared by two or more customers.
b. have common ingredients.
c. share a storage facility or storage tank.
d. are interchangeable.
Subjective Short
37. Investment manager Max Gaines has several clients who wish to own a mutual fund portfolio that matches, as a whole, the performance of the S&P 500 stock index. His task is to determine what proportion of the portfolio should be invested in each of the five mutual funds listed below so that the portfolio most closely mimics the performance of the S&P 500 index. Formulate the appropriate nonlinear program.
Annual Returns (Planning Scenarios)
Mutual Fund Year 1 Year 2 Year 3 Year 4
International Stock 26.73 22.37 6.46 3.19
Large-Cap Blend 18.61 14.88 10.52 5.25
Mid-Cap Blend 18.04 19.45 15.91 1.94
Small-Cap Blend 11.33 13.79 2.07 6.85
Intermediate Bond 8.05 7.29 9.18 3.92
S&P 500 Index 21.00 19.00 12.00 4.00
38. Financial planner Minnie Margin has a substantial number of clients who wish to own a mutual fund portfolio that matches, as a whole, the performance of the Russell 2000 index. Her task is to determine what proportion of the portfolio should be invested in each of the five mutual funds listed below so that the portfolio most closely mimics the performance of the Russell 2000 index. Formulate the appropriate nonlinear program.
Annual Returns (Planning Scenarios)
Mutual Fund Year 1 Year 2 Year 3 Year 4
International Stock 22.37 26.73 4.86 2.17
Large-Cap Value 15.48 19.64 11.50 5.25
Mid-Cap Value 17.42 20.07 4.97 1.69
Small-Cap Growth 23.18 12.36 3.25 3.81
Short-Term Bond 9.26 8.81 6.15 4.04
Russell 2000 Index 20.00 22.00 8.00 2.00
39. Investment manager Max Gaines wishes to develop a mutual fund portfolio based on the Markowitz portfolio model. He needs to determine the proportion of the portfolio to invest in each of the five mutual funds listed below so that the variance of the portfolio is minimized subject to the constraint that the expected return of the portfolio be at least 4%. Formulate the appropriate nonlinear program.
Annual Returns (Planning Scenarios)
Mutual Fund Year 1 Year 2 Year 3 Year 4
International Stock 26.73 22.37 6.46 3.19
Large-Cap Blend 18.61 14.88 10.52 5.25
Mid-Cap Blend 18.04 19.45 15.91 1.94
Small-Cap Blend 11.33 13.79 2.07 6.85
Intermediate Bond 8.05 7.29 9.18 3.92
40. Financial planner Minnie Margin wishes to develop a mutual fund portfolio based on the Markowitz portfolio model. She needs to determine the proportion of the portfolio to invest in each of the five mutual funds listed below so that the variance of the portfolio is minimized subject to the constraint that the expected return of the portfolio be at least 5%. Formulate the appropriate nonlinear program.
Annual Returns (Planning Scenarios)
Mutual Fund Year 1 Year 2 Year 3 Year 4
International Stock 22.37 26.73 4.86 2.17
Large-Cap Value 15.48 19.64 11.50 5.25
Mid-Cap Value 17.42 20.07 4.97 1.69
Small-Cap Growth 23.18 12.36 3.25 3.81
Short-Term Bond 9.26 8.81 6.15 4.04
41. Cutting Edge Yard Care is a residential and commercial lawn service company that has been in business in the Atlanta metropolitan area for almost one year. Cutting Edge would like to use its Atlanta service subscription data below to develop a model for forecasting service subscriptions in other metropolitan areas where it might expand. The first step is to estimate values for p (coefficient of innovation) and q (coefficient of imitation). Formulate the appropriate nonlinear program.
Month Subscribers St Cum. Subscribers Ct
1 0.53 0.53
2 2.04 2.57
3 3.37 5.94
4 4.85 10.79
5 5.14 15.93
6 3.90 19.83
7 2.26 22.09
8 1.43 23.52
9 0.98 24.50
10 0.42 24.92
42. MegaSports, Inc. produces two high-priced metal baseball bats, the Slugger and the Launcher, that are made from special aluminum and steel alloys. The cost to produce a Slugger bat is $100, and the cost to produce a Launcher bat is $120. We cannot assume that MegaSports will sell all the bats it can produce. As the selling price of each bat model—Slugger and Launcher—increases, the quantity demanded for each model goes down.
Assume that the demand, S, for Slugger bats is given by S = 640 − 4PS and the demand, L, for Launcher bats is given by L = 450 − 3PL where PS is the price of a Slugger bat and PL is the price of a Launcher bat. The profit contributions are PS S − 100S for Slugger bats and PL L − 120L for Launcher bats. Develop the total profit contribution function for this problem.
43. Pacific-Gulf Oil Company is faced with the problem of refining three petroleum components into regular and premium gasoline in order to maximize profit. Components 1 and 2 are pooled in a single storage tank, and component 3 has its own storage tank. Regular and premium gasolines are made from blending the pooled components and component 3. Prices per gallon for the two products and three components, as well as product specifications, are listed below.
Price per Gallon
Regular gasoline $2.80
Premium gasoline 3.10
Component 1 2.40
Component 2 2.50
Component 3 2.75
Product Specifications
Regular gasoline At most 25% component 1
At least 40% component 2
At most 30% component 3
Premium gasoline At least 30% component 1
At most 50% component 2
At least 25% component 3
The maximum number of gallons available for each of the three components is 4000, 8000, and 8000, respectively. Formulate a nonlinear program to determine: (1) what percentages of components 1 and 2 should be used in the pooled mixture and (2) how to make regular and premium gasoline by blending the mixture of components 1 and 2 from the pooling tank with component 3.
44. Skooter's Skateboards produces two models of skateboards, the FX and the ZX. Skateboard revenue (in $l000s) for the firm is nonlinear and is stated as (number of FXs)(5 − 0.2 number of FXs) + (number of ZXs)(7 − 0.3 number of ZXs). Skooter's has 80 labor-hours available per week in its paint shop. Each FX requires two labor-hours to paint, and each ZX requires three labor-hours. Formulate this nonlinear production planning problem to determine how many FX and ZX skateboards should be produced per week at Scooter's.
45. Native Customs sells two popular styles of hand-sewn footwear: a sandal and a moccasin. The cost to make a pair of sandals is $18, and the cost to make a pair of moccasins is $24. The demand for these two items is sensitive to the price, and historical data indicate that the monthly demands are given by S = 400 − 10P1 and M = 450 − 15P2, where S = demand for sandals (in pairs), M = demand for moccasins (in pairs), P1 = price for a pair of sandals, and P2 = price for a pair of moccasins. To remain competitive, Native Customs must limit the price (per pair) to no more than $60 and $75 for its sandals and moccasins, respectively. Formulate this nonlinear programming problem to find the optimal production quantities and prices for sandals and moccasins that maximize total monthly profit.
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