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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 ASW8
3. An
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ANSWER: False
TOPIC: Local and global optimaQMB6
7. A feasible solution is a global optimum if there are no other feasible points with a better objective function value in the feasible region.
ANSWER: True
TOPIC: Local and global optima
8. For a typical nonlinear problem, duals price are relatively insensitive to small changes in right-hand side values.
ANSWER: False
TOPIC: Local and global optima QMB6
ASW8
9. The interpretation of the dual price for nonlinear models is different than the interpretation of the dual price for linear models.
ANSWER: False
TOPIC: Local and global optima ASW8
10. In the case of functions with multiple local optima, most nonlinear optimization software methods can get stuck and terminate at a local optimum.
ANSWER: True
TOPIC: Local and global optima
11. For a minimization problem, a point is a global minimum if there are no other feasible points with a smaller objective function value.
ANSWER: True
TOPIC: Local and global optima
12. There are nonlinear applications in which there is a single local optimal solution that is also the global optimal solution.
ANSWER: True
TOPIC: Local and global optima
13. Functions that are convex have a single local maximum that is also the global maximum.
ANSWER: False
TOPIC: Local and global optima
14. The function f (X, Y) = X 2 + Y 2 has a single global minimum and is relatively easy to minimize.
ANSWER: True
TOPIC: Local and global optima
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The feasible solutions property is necessary. It states that a minimum cost flow problem will have a feasible solution if and only if the sum of the supplies
What is the goal in optimization? Find the decision variable values that result in the best objective function and satisfy all constraints.
The shaded area represents the feasible region, and the dashed line in the middle is the slope of the objective function.
There is an difference between the slope of line on right and left of the optimum
We can view the optimal control problem as that of choosing the best path among all paths feasible for the system, with respect to the given cost function. In this sense, the problem is in nite- dimensional, because the space of paths is an in nite-dimensional function space. This problem is also a dynamic optimization problem, in the sense that it involves a dynamical system and time.
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A feasible solution point does not have to lie on the boundary of the feasible solution.
The reality is usually somewhere in between. In such cases the chosen price needs to be
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