Question 1

The reduced gradient values in sensitivity analysis for nonlinear programming models are valid only at the point of the optimal solution.

Accepted Answer

A) True 
 B)False

Question 2

By definition, any linear equation must be:

Accepted Answer

A)  Proportional and additive. 
B)  Proportional or additive. 
C)  Neither proportional nor additive. 
D)  Either non-proportional or non-additive. 
A)  Proportional and additive. 
B)  Proportional or additive. 
C)  Neither proportional nor additive. 
D)  Either non-proportional or non-additive.

Question 3

Nonlinear programming models are usually:

Accepted Answer

A)  More challenging to solve than linear programming models. 
B)  Less representative of real-world problems. 
C)  Less accurate in the results of the final solution. 
D)  All of the above distinguish nonlinear programming from linear programming counterparts. 
A)  More challenging to solve than linear programming models. 
B)  Less representative of real-world problems. 
C)  Less accurate in the results of the final solution. 
D)  All of the above distinguish nonlinear programming from linear programming counterparts.

Question 4

If the objective function or any of the constraints do not follow the proportionality or additivity requirement, then the decision maker may choose to represent business relationships with a:

Accepted Answer

A)  Regression model. 
B)  Nonlinear programming model. 
C)  Linear programming model. 
D)  None of the above 
A)  Regression model. 
B)  Nonlinear programming model. 
C)  Linear programming model. 
D)  None of the above

Question 5

Nonlinear programming models are based on the assumptions that the objective function and constraints are nonlinear equations.

Accepted Answer

A) True 
 B)False

Question 6

Business situations often have relationships that are often not proportional or additive.

Accepted Answer

A) True 
 B)False

Question 7

When an objective function is nonlinear, any local optimum is also a global optimum.

Accepted Answer

A) True 
 B)False

Question 8

The additivity assumption may fail under certain conditions such as:

Accepted Answer

A)  Economies of scale 
B)  Buy one, get a second item of an equal or lower price for free. 
C)  Both a and b 
D)  Neither a nor b 
A)  Economies of scale 
B)  Buy one, get a second item of an equal or lower price for free. 
C)  Both a and b 
D)  Neither a nor b

Question 9

When constraints are nonlinear, any local optimum is also a global optimum.

Accepted Answer

A) True 
 B)False

Question 10

The dual values in sensitivity analysis for nonlinear programming models:

Accepted Answer

A)  Change when these values move away from the optimal solution. 
B)  Remain constant within the range between the upper and lower limits. 
C)  Become invalid at the point of the optimal solution. 
D)  None of the above statements are true about the dual values for nonlinear programming models. 
A)  Change when these values move away from the optimal solution. 
B)  Remain constant within the range between the upper and lower limits. 
C)  Become invalid at the point of the optimal solution. 
D)  None of the above statements are true about the dual values for nonlinear programming models.

Question 11

Which of the following is a good option for the decision maker when formulating and solving complex nonlinear programming models?

Accepted Answer

A)  Formulating the problem as a linear model and considering the trade-off between a less rigorous formulation and an efficient solution 
B)  Formulating the problem as a nonlinear model and solving it using linear modeling approaches 
C)  Not using an optimization technique and saving on model building and solution costs 
D)  All of the above 
A)  Formulating the problem as a linear model and considering the trade-off between a less rigorous formulation and an efficient solution 
B)  Formulating the problem as a nonlinear model and solving it using linear modeling approaches 
C)  Not using an optimization technique and saving on model building and solution costs 
D)  All of the above

Question 12

When using nonlinear programming models, there is always a risk that the algorithm will result in a local optimum.

Accepted Answer

A) True 
 B)False

Question 13

A modeler may check the "Use Multistart" box under "Options" to allow Solver to avoid the local optimum as much as possible.

Accepted Answer

A) True 
 B)False

Question 14

Which of the following is not a part of the nonlinear programming formulation?

Accepted Answer

A)  An objective function to be optimized 
B)  A set of constraints to be satisfied 
C)  A set of nonlinear objectives to be sought 
D)  All of the above are components of nonlinear programming formulations. 
A)  An objective function to be optimized 
B)  A set of constraints to be satisfied 
C)  A set of nonlinear objectives to be sought 
D)  All of the above are components of nonlinear programming formulations.

Question 15

Formulation steps for nonlinear programming models are identical to those of linear programming models.

Accepted Answer

A) True 
 B)False

Question 16

Solver's GRG algorithm is best suited for linear programming models.

Accepted Answer

A) True 
 B)False

Question 17

Nonlinear programming models have the same structure as the linear programming models. Both models consist of the objective function, a set of constraints, and a set of non-negativity constraints.

Accepted Answer

A) True 
 B)False

Question 18

Which of the following dimensions of Big Data offers increased opportunities for optimization models in general and nonlinear programming models in particular?

Accepted Answer

A)  Volume 
B)  Variety 
C)  Velocity 
D)  All of the above 
A)  Volume 
B)  Variety 
C)  Velocity 
D)  All of the above

Question 19

In certain situations, a decision maker may decide to ignore the assumptions of nonlinearity when formulating a model in exchange for:

Accepted Answer

A)  More accurate results of the solution. 
B)  A simpler formulation and solution process. 
C)  A better representation of real-world relationships. 
D)  All of the above 
A)  More accurate results of the solution. 
B)  A simpler formulation and solution process. 
C)  A better representation of real-world relationships. 
D)  All of the above

Question 20

The proportionality assumption may fail under certain conditions such as:

Accepted Answer

A)  Economies of scale. 
B)  Buy one, get a second item of an equal or lower price for free. 
C)  Both a and b 
D)  Neither a nor b 
A)  Economies of scale. 
B)  Buy one, get a second item of an equal or lower price for free. 
C)  Both a and b 
D)  Neither a nor b

The reduced gradient values in sensitivity analysis for nonlinear programming models are valid only at the point of the optimal solution.

By definition, any linear equation must be:

Nonlinear programming models are usually:

If the objective function or any of the constraints do not follow the proportionality or additivity requirement, then the decision maker may choose to represent business relationships with a:

Nonlinear programming models are based on the assumptions that the objective function and constraints are nonlinear equations.

Business situations often have relationships that are often not proportional or additive.

When an objective function is nonlinear, any local optimum is also a global optimum.

The additivity assumption may fail under certain conditions such as:

When constraints are nonlinear, any local optimum is also a global optimum.

The dual values in sensitivity analysis for nonlinear programming models:

Which of the following is a good option for the decision maker when formulating and solving complex nonlinear programming models?

When using nonlinear programming models, there is always a risk that the algorithm will result in a local optimum.

A modeler may check the "Use Multistart" box under "Options" to allow Solver to avoid the local optimum as much as possible.

Which of the following is not a part of the nonlinear programming formulation?

Formulation steps for nonlinear programming models are identical to those of linear programming models.

Solver's GRG algorithm is best suited for linear programming models.

Nonlinear programming models have the same structure as the linear programming models. Both models consist of the objective function, a set of constraints, and a set of non-negativity constraints.

Which of the following dimensions of Big Data offers increased opportunities for optimization models in general and nonlinear programming models in particular?

In certain situations, a decision maker may decide to ignore the assumptions of nonlinearity when formulating a model in exchange for:

The proportionality assumption may fail under certain conditions such as:

Business Analytics With Management Science

Introduction to Linear Programming

Business Analytics With Linear Programming

Business Analytics With Goal Programming

Business Analytics With Integer Programming

Business Analytics With Shipment Models

Marketing Analytics With Linear Programming

Marketing Analytics With Multiple Goals

Business Analytics With Simulation

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Exam 4: Business Analytics With Nonlinear Programming

The reduced gradient values in sensitivity analysis for nonlinear programming models are valid only at the point of the optimal solution.

By definition, any linear equation must be:

Nonlinear programming models are usually:

If the objective function or any of the constraints do not follow the proportionality or additivity requirement, then the decision maker may choose to represent business relationships with a:

Nonlinear programming models are based on the assumptions that the objective function and constraints are nonlinear equations.

Business situations often have relationships that are often not proportional or additive.

When an objective function is nonlinear, any local optimum is also a global optimum.

The additivity assumption may fail under certain conditions such as:

When constraints are nonlinear, any local optimum is also a global optimum.

The dual values in sensitivity analysis for nonlinear programming models:

Which of the following is a good option for the decision maker when formulating and solving complex nonlinear programming models?

When using nonlinear programming models, there is always a risk that the algorithm will result in a local optimum.

A modeler may check the "Use Multistart" box under "Options" to allow Solver to avoid the local optimum as much as possible.

Which of the following is not a part of the nonlinear programming formulation?

Formulation steps for nonlinear programming models are identical to those of linear programming models.

Solver's GRG algorithm is best suited for linear programming models.

Nonlinear programming models have the same structure as the linear programming models. Both models consist of the objective function, a set of constraints, and a set of non-negativity constraints.

Which of the following dimensions of Big Data offers increased opportunities for optimization models in general and nonlinear programming models in particular?

In certain situations, a decision maker may decide to ignore the assumptions of nonlinearity when formulating a model in exchange for:

The proportionality assumption may fail under certain conditions such as:

Business Analytics With Management Science

Introduction to Linear Programming

Business Analytics With Linear Programming

Business Analytics With Goal Programming

Business Analytics With Integer Programming

Business Analytics With Shipment Models

Marketing Analytics With Linear Programming

Marketing Analytics With Multiple Goals

Business Analytics With Simulation

Filters