Question 1

Nonlinear optimization problems can have only one local optimal solution.

Accepted Answer

A) True 
 B)False

Question 2

A nonlinear optimization problem is any optimization problem in which at least one term in the objective function or a constraint is nonlinear.

Accepted Answer

A) True 
 B)False

Question 3

Which of the following is not true regarding a concave function?

Accepted Answer

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.

Question 4

Which of the following is incorrect?

Accepted Answer

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.

Question 5

Which of the following is not a parameter of the Bass model for forecasting adoption of a new product?

Accepted Answer

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 B

Question 6

A feasible solution is a global optimum if there are no other feasible solutions with a better objective function value in the immediate neighborhood.

Accepted Answer

A) True 
 B)False

Question 7

A convex function is

Accepted Answer

A)  bowl-shaped up.
B)  bowl-shaped down.
C)  elliptical in shape.
D)  sinusoidal in shape.

Question 8

The function f (X, Y) = X 2 + Y 2 has a single global minimum and is relatively easy to minimize.

Accepted Answer

A) True 
 B)False

Question 9

An investor can pick the mean-variance tradeoff that he or she is most comfortable with by looking at a graph of the

Accepted Answer

A)  feasible region.
B)  pooled components.
C)  rolling horizon.
D)  efficient frontier.

Question 10

Because most nonlinear optimization codes will terminate with a local optimum, the solution returned by the codes will be the best solution.

Accepted Answer

A) True 
 B)False

Question 11

Any feasible solution to a blending problem with pooled components is feasible to the problem with no pooling.

Accepted Answer

A) True 
 B)False

Question 12

A function is quadratic if its nonlinear terms have a power of 4.

Accepted Answer

A) True 
 B)False

Question 13

If the coefficient of each squared term in a quadratic function is positive, the function is

Accepted Answer

A)  concave.
B)  convex.
C)  elliptical.
D)  sinusoidal.

Question 14

When components (or ingredients) in a blending problem must be pooled, the number of feasible solutions is reduced.

Accepted Answer

A) True 
 B)False

Question 15

When the number of blending components exceeds the number of storage facilities, the number of feasible solutions to the blending problem

Accepted Answer

A)  is reduced.
B)  is increased.
C)  is unchanged.
D)  is zero. A

Question 16

Components that share a storage facility are called

Accepted Answer

A)  constrained components.
B)  indexed components.
C)  blended components.
D)  pooled components.

Question 17

The problem of maximizing a concave quadratic function over a linear constraint set is relatively difficult to solve.

Accepted Answer

A) True 
 B)False

Question 18

Any feasible solution to a blending problem without pooled components is feasible to the problem with pooled components.

Accepted Answer

A) True 
 B)False  False

Question 19

Many linear programming algorithms such as the simplex method optimize by examining only the extreme points of the feasible region.

Accepted Answer

A) True 
 B)False

Question 20

The key idea behind constructing an index fund is to choose a portfolio of securities that

Accepted Answer

A)  is a mix of growth-oriented and income-oriented stocks.
B)  minimizes risk without sacrificing liquidity.
C)  mimics the performance of a broad market index.
D)  balances short-term and long-term investments.

Exam 8: Nonlinear Optimization Models

Nonlinear optimization problems can have only one local optimal solution.

Correct AnswerverifiedShow Answer

A nonlinear optimization problem is any optimization problem in which at least one term in the objective function or a constraint is nonlinear.

Correct AnswerverifiedShow Answer

Which of the following is not true regarding a concave function?

Correct AnswerverifiedShow Answer

Which of the following is incorrect?

Correct AnswerverifiedShow Answer

Which of the following is not a parameter of the Bass model for forecasting adoption of a new product?

Correct AnswerverifiedB

A feasible solution is a global optimum if there are no other feasible solutions with a better objective function value in the immediate neighborhood.

Correct AnswerverifiedShow Answer

A convex function is

Correct AnswerverifiedShow Answer

The function f (X, Y) = X 2 + Y 2 has a single global minimum and is relatively easy to minimize.

Correct AnswerverifiedShow Answer

An investor can pick the mean-variance tradeoff that he or she is most comfortable with by looking at a graph of the

Correct AnswerverifiedShow Answer

Because most nonlinear optimization codes will terminate with a local optimum, the solution returned by the codes will be the best solution.

Correct AnswerverifiedShow Answer

Any feasible solution to a blending problem with pooled components is feasible to the problem with no pooling.

Correct AnswerverifiedShow Answer

A function is quadratic if its nonlinear terms have a power of 4.

Correct AnswerverifiedShow Answer

If the coefficient of each squared term in a quadratic function is positive, the function is

Correct AnswerverifiedShow Answer

When components (or ingredients) in a blending problem must be pooled, the number of feasible solutions is reduced.

Correct AnswerverifiedShow Answer

When the number of blending components exceeds the number of storage facilities, the number of feasible solutions to the blending problem

Correct AnswerverifiedA

Components that share a storage facility are called

Correct AnswerverifiedShow Answer

The problem of maximizing a concave quadratic function over a linear constraint set is relatively difficult to solve.

Correct AnswerverifiedShow Answer

Any feasible solution to a blending problem without pooled components is feasible to the problem with pooled components.

Correct AnswerverifiedFalse

Many linear programming algorithms such as the simplex method optimize by examining only the extreme points of the feasible region.

Correct AnswerverifiedShow Answer

The key idea behind constructing an index fund is to choose a portfolio of securities that

Correct AnswerverifiedShow Answer

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified
B

Correct Answer
verified

Correct Answer
verified

The function f (X, Y) = X ² + Y ² has a single global minimum and is relatively easy to minimize.

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified
A

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified
False

Correct Answer
verified

Correct Answer
verified