MS12-TB08 - 8 Nonlinear Optimization Models MULTIPLE CHOICE...

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Unformatted text preview: 8 Nonlinear Optimization Models MULTIPLE CHOICE 1. Which of the following 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. ANSWER: d TOPIC: Local and global optima 2. The measure of risk most often associated with the Markowitz portfolio model is the a. portfolio average return. b. portfolio minimum return. c. portfolio variance. d. portfolio standard deviation. ANSWER: c TOPIC: Markowitz portfolio model 3. 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. ANSWER: d TOPIC: Markowitz portfolio model 4. Which of the following is not a parameter of the Bass model for forecasting adoption of a new product? a. the coefficient of innovation b. the coefficient of interaction c. the coefficient of imitation d. the estimated number of people to eventually adopt the new product ANSWER: b TOPIC: Forecasting adoption of a new product 1 2 Chapter 8 Nonlinear Optimization Models 5. When the number of blending components exceeds the number of storage facilities, the number of feasible solutions to the blending problem a. is reduced. b. is increased. c. is unchanged. d. is zero. ANSWER: a TOPIC: Blending the pooling problem 6. 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. ANSWER: b TOPIC: Forecasting adoption of a new product 7. 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. ANSWER: c TOPIC: Local and global optima 8. A convex function is a. bowl-shaped up. b. bowl-shaped down. c. elliptical in shape. d. sinusoidal in shape. ANSWER: a TOPIC: Local and global optima 9. If the coefficient of each squared term in a quadratic function is positive, the function is a. concave. b. convex. c. elliptical. d. sinusoidal. ANSWER: b TOPIC: Local and global optima 10. Components that share a storage facility are called a. constrained components. b. indexed components. c. blended components. d. pooled components. ANSWER: d TOPIC: Blending the pooling problem 11. The key idea behind constructing an index fund is to choose a portfolio of securities that a. is a mix of growth-oriented and income-oriented stocks....
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MS12-TB08 - 8 Nonlinear Optimization Models MULTIPLE CHOICE...

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