Question 1

Nonlinear integer programming models offer additional challenges for solution algorithms because the values of reduced gradients are valid only at the point of the optimal solution.

Accepted Answer

A) True 
 B)False

Question 2

In order to strictly enforce integer values for the final solution, the decision maker must set the tolerance level for integer constraints to zero.

Accepted Answer

A) True 
 B)False

Question 3

In the assignment method, the decision maker seeks to assign each available resource to a specific task.

Accepted Answer

A) True 
 B)False

Question 4

The objective function of the assignment method always seeks to minimize cost.

Accepted Answer

A) True 
 B)False

Question 5

When determining the number of pounds of lumber to be produced, decision variables must be enforced as integer values.

Accepted Answer

A) True 
 B)False

Question 6

The finite nature of integer programming models leads to simpler solution algorithms.

Accepted Answer

A) True 
 B)False

Question 7

While a regular linear programming model has an infinite number of possible solutions, the integer counterpart has an infinite but different set of possible solutions.

Accepted Answer

A) True 
 B)False

Question 8

Which of the following is a result that the decision maker should anticipate when solving an integer linear programming model with a maximization objective?

Accepted Answer

A)  The value of the objective function will not be less than the objective function of the non-integer model. 
B)  The value of the objective function will be greater than the objective function of the non-integer model. 
C)  The value of the objective function will not be greater than the objective function of the non-integer model. 
D)  All of the above

Question 9

The objective function of the assignment method in business settings always seeks to maximize revenue, profit, or another organizational metric.

Accepted Answer

A) True 
 B)False

Question 10

The knapsack problem is a special case of the binary linear programming model.

Accepted Answer

A) True 
 B)False

Question 11

In the assignment method, the decision maker seeks to assign:

Accepted Answer

A)  Each available resource to a specific set of tasks. 
B)  One resource to only one task. 
C)  Several available resources to one set of tasks. 
D)  Several available resources to only one task.

Question 12

Which of the following is a result that the decision maker should anticipate when solving an integer nonlinear programming model with a maximization objective?

Accepted Answer

A)  The value of the objective function will not be less than the objective function of the non-integer model. 
B)  The value of the objective function will be greater than the objective function of the non-integer model. 
C)  The value of the objective function will not be greater than the objective function of the non-integer model. 
D)  All of the above

Question 13

Which of the following is a result that the decision maker should anticipate when solving an integer nonlinear programming model with a minimization objective?

Accepted Answer

A)  The value of the objective function will not be less than the objective function of the non-integer model. 
B)  The value of the objective function will be greater than the objective function of the non-integer model. 
C)  The value of the objective function will not be greater than the objective function of the non-integer model. 
D)  All of the above

Question 14

In a mathematical programming model, the divisibility assumption allows decision variables to take:

Accepted Answer

A)  Integer values. 
B)  Fractional values. 
C)  Negative values. 
D)  All of the above

Question 15

The impact of rounding a fractional solution into an integer solution on the objective function is always minimal.

Accepted Answer

A) True 
 B)False

Question 16

Nonlinear integer programming models offer additional challenges for solution algorithms because:

Accepted Answer

A)  The values of reduced gradients are valid only at the point of the optimal solution. 
B)  The values of Lagrange multipliers are valid only at the point of the optimal solution. 
C)  The generalized reduced gradient algorithm cannot differentiate local and global optima. 
D)  All of the above

Question 17

Nonlinear integer programming models offer additional challenges for solution algorithms because the values of Lagrange multipliers are valid only at the point of the optimal solution.

Accepted Answer

A) True 
 B)False

Question 18

Which of the following is a context that may require the use of the assignment method?

Accepted Answer

A)  There are m machines and n workers to be assigned at the beginning of production period (m ? n). 
B)  There are m machines and n workers to be assigned at the beginning of production period (m = n). 
C)  Both a and b 
D)  Neither a nor b

Question 19

Linear integer programming models offer additional challenges for solution algorithms because the dual values are valid only at the point of the optimal solution.

Accepted Answer

A) True 
 B)False

Question 20

Which of the following is a result that the decision maker should anticipate when solving an integer linear programming model with a minimization objective?

Accepted Answer

A)  The value of the objective function will not be less than the objective function of the non-integer model. 
B)  The value of the objective function will be greater than the objective function of the non-integer model. 
C)  The value of the objective function will not be greater than the objective function of the non-integer model. 
D)  All of the above

Exam 6: Business Analytics With Integer Programming

Nonlinear integer programming models offer additional challenges for solution algorithms because the values of reduced gradients are valid only at the point of the optimal solution.

In order to strictly enforce integer values for the final solution, the decision maker must set the tolerance level for integer constraints to zero.

In the assignment method, the decision maker seeks to assign each available resource to a specific task.

The objective function of the assignment method always seeks to minimize cost.

When determining the number of pounds of lumber to be produced, decision variables must be enforced as integer values.

The finite nature of integer programming models leads to simpler solution algorithms.

While a regular linear programming model has an infinite number of possible solutions, the integer counterpart has an infinite but different set of possible solutions.

Which of the following is a result that the decision maker should anticipate when solving an integer linear programming model with a maximization objective?

The objective function of the assignment method in business settings always seeks to maximize revenue, profit, or another organizational metric.

The knapsack problem is a special case of the binary linear programming model.

In the assignment method, the decision maker seeks to assign:

Which of the following is a result that the decision maker should anticipate when solving an integer nonlinear programming model with a maximization objective?

Which of the following is a result that the decision maker should anticipate when solving an integer nonlinear programming model with a minimization objective?

In a mathematical programming model, the divisibility assumption allows decision variables to take:

The impact of rounding a fractional solution into an integer solution on the objective function is always minimal.

Nonlinear integer programming models offer additional challenges for solution algorithms because:

Nonlinear integer programming models offer additional challenges for solution algorithms because the values of Lagrange multipliers are valid only at the point of the optimal solution.

Which of the following is a context that may require the use of the assignment method?

Linear integer programming models offer additional challenges for solution algorithms because the dual values are valid only at the point of the optimal solution.

Which of the following is a result that the decision maker should anticipate when solving an integer linear programming model with a minimization objective?