Question 1

A local optimum is a point in the feasible region with a better value than any other feasible point in the small neighborhood around it.

Accepted Answer

A) True 
 B)False  True

Question 2

Solutions of nonlinear programming models with Microsoft Excel will often generate "division by zero" errors. To avoid these errors, the decision maker should:

Accepted Answer

A)  Ignore them and read the solution as provided by Excel. 
B)  Accept the errors as part of the solution (i.e., there is no solution to the given problem). 
C)  Add a non-negativity constraint for decision variables instead of checking the non-negativity box in Solver. 
D)  All of the above 
A)  Ignore them and read the solution as provided by Excel. 
B)  Accept the errors as part of the solution (i.e., there is no solution to the given problem). 
C)  Add a non-negativity constraint for decision variables instead of checking the non-negativity box in Solver. 
D)  All of the above C

Question 3

A global optimum is a point in the feasible region with a better value than any other feasible point in the entire area of feasible solutions.

Accepted Answer

A) True 
 B)False  True

Question 4

Relationships in nonlinear programming models with two decision variables can be represented by straight lines.

Accepted Answer

A) True 
 B)False

Question 5

A nonlinear model has at least one nonlinear equation in either the constraint or the objective function.

Accepted Answer

A) True 
 B)False

Question 6

Nonlinear relationships in nonlinear programming models can be represented by:

Accepted Answer

A)  Curved lines when the model has two decision variables. 
B)  Planes when the model has three decision variables. 
C)  Both a and b are true. 
D)  None of the above 
A)  Curved lines when the model has two decision variables. 
B)  Planes when the model has three decision variables. 
C)  Both a and b are true. 
D)  None of the above

Question 7

Which of the following is a step for solving nonlinear programming models?

Accepted Answer

A)  Creating an Microsoft Excel template 
B)  Applying Solver 
C)  Interpreting the solution results 
D)  All of the above 
A)  Creating an Microsoft Excel template 
B)  Applying Solver 
C)  Interpreting the solution results 
D)  All of the above

Question 8

Relationships in linear programming models can be represented by:

Accepted Answer

A)  Straight lines when the model has two decision variables. 
B)  Planes when the model has three decision variables. 
C)  Both a and b are true. 
D)  None of the above 
A)  Straight lines when the model has two decision variables. 
B)  Planes when the model has three decision variables. 
C)  Both a and b are true. 
D)  None of the above

Question 9

In the era of Big Data, advanced software programs such as Solver can be used to navigate large number variables and constraints.

Accepted Answer

A) True 
 B)False

Question 10

The final value in the variable cells of the sensitivity report of nonlinear programming models can indicate:

Accepted Answer

A)  The initial solution for the decision variables. 
B)  The optimal solution for the decision variables. 
C)  A range of optimal solutions for the decision variables. 
D)  Any of the above 
A)  The initial solution for the decision variables. 
B)  The optimal solution for the decision variables. 
C)  A range of optimal solutions for the decision variables. 
D)  Any of the above

Question 11

The availability of more data allows organizations to explore, formulate, and solve previously unsolvable problems.

Accepted Answer

A) True 
 B)False

Question 12

Which of the following is a step for formulating nonlinear programming models?

Accepted Answer

A)  Defining decision variables 
B)  Formulating an objective function 
C)  Identifying a set of constraints 
D)  Identifying a set of non-negativity constraints 
E)  All of the above 
A)  Defining decision variables 
B)  Formulating an objective function 
C)  Identifying a set of constraints 
D)  Identifying a set of non-negativity constraints 
E)  All of the above

Question 13

Solving nonlinear programming models may be more difficult than solving linear programming models because:

Accepted Answer

A)  Nonlinear constraints may create discontinuous areas that satisfy all constraints. 
B)  Nonlinear constraints are difficult to translate into mathematical functions. 
C)  Nonlinear constraints are associated with a quantity discount. 
D)  All of the above 
A)  Nonlinear constraints may create discontinuous areas that satisfy all constraints. 
B)  Nonlinear constraints are difficult to translate into mathematical functions. 
C)  Nonlinear constraints are associated with a quantity discount. 
D)  All of the above

Question 14

The Lagrange multiplier 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 15

Mathematical modeling of real-world business situations involves:

Accepted Answer

A)  Linear relationships in the objective functions. 
B)  Linear relationships of resource constraints. 
C)  Nonlinear relationships in the objective functions. 
D)  Nonlinear relationships of resource constraints. 
E)  All of the above 
A)  Linear relationships in the objective functions. 
B)  Linear relationships of resource constraints. 
C)  Nonlinear relationships in the objective functions. 
D)  Nonlinear relationships of resource constraints. 
E)  All of the above

Question 16

Which of the following distinguishes the sensitivity reports of nonlinear programming models from the sensitivity reports of regular linear programming models?

Accepted Answer

A)  The "reduced cost" in linear programming models is called the "Lagrange multiplier" in nonlinear programming models. 
B)  The "shadow price" in linear programming models is called the "reduced gradient" in nonlinear programming models. 
C)  The "reduced cost" in linear programming models is called the "reduced gradient" in nonlinear programming models. 
D)  All of the above 
A)  The "reduced cost" in linear programming models is called the "Lagrange multiplier" in nonlinear programming models. 
B)  The "shadow price" in linear programming models is called the "reduced gradient" in nonlinear programming models. 
C)  The "reduced cost" in linear programming models is called the "reduced gradient" in nonlinear programming models. 
D)  All of the above

Question 17

Which of the following must be satisfied in a nonlinear programming model?

Accepted Answer

A)  The objective function must be nonlinear. 
B)  The constraints must be nonlinear equations. 
C)  Either a or b 
D)  Neither a nor b 
A)  The objective function must be nonlinear. 
B)  The constraints must be nonlinear equations. 
C)  Either a or b 
D)  Neither a nor b

Question 18

In certain situations, a decision maker may choose nonlinear programming models in exchange for:

Accepted Answer

A)  More accurate results of the solution. 
B)  A simpler formulation process. 
C)  A simpler solution process. 
D)  All of the above 
A)  More accurate results of the solution. 
B)  A simpler formulation process. 
C)  A simpler solution process. 
D)  All of the above

Question 19

When solving linear or nonlinear programming models, a constraint with a zero slack variable is a binding constraint.

Accepted Answer

A) True 
 B)False

Question 20

Nonlinear relationships in nonlinear programming models can be represented by:

Accepted Answer

A)  Straight lines when the model has two decision variables. 
B)  Planes when the model has three decision variables. 
C)  Both a and b are true. 
D)  None of the above 
A)  Straight lines when the model has two decision variables. 
B)  Planes when the model has three decision variables. 
C)  Both a and b are true. 
D)  None of the above

A local optimum is a point in the feasible region with a better value than any other feasible point in the small neighborhood around it.

Solutions of nonlinear programming models with Microsoft Excel will often generate "division by zero" errors. To avoid these errors, the decision maker should:

A global optimum is a point in the feasible region with a better value than any other feasible point in the entire area of feasible solutions.

Relationships in nonlinear programming models with two decision variables can be represented by straight lines.

A nonlinear model has at least one nonlinear equation in either the constraint or the objective function.

Nonlinear relationships in nonlinear programming models can be represented by:

Which of the following is a step for solving nonlinear programming models?

Relationships in linear programming models can be represented by:

In the era of Big Data, advanced software programs such as Solver can be used to navigate large number variables and constraints.

The final value in the variable cells of the sensitivity report of nonlinear programming models can indicate:

The availability of more data allows organizations to explore, formulate, and solve previously unsolvable problems.

Which of the following is a step for formulating nonlinear programming models?

Solving nonlinear programming models may be more difficult than solving linear programming models because:

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

Mathematical modeling of real-world business situations involves:

Which of the following distinguishes the sensitivity reports of nonlinear programming models from the sensitivity reports of regular linear programming models?

Which of the following must be satisfied in a nonlinear programming model?

In certain situations, a decision maker may choose nonlinear programming models in exchange for:

When solving linear or nonlinear programming models, a constraint with a zero slack variable is a binding constraint.

Nonlinear relationships in nonlinear programming models can be represented by:

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

A local optimum is a point in the feasible region with a better value than any other feasible point in the small neighborhood around it.

Solutions of nonlinear programming models with Microsoft Excel will often generate "division by zero" errors. To avoid these errors, the decision maker should:

A global optimum is a point in the feasible region with a better value than any other feasible point in the entire area of feasible solutions.

Relationships in nonlinear programming models with two decision variables can be represented by straight lines.

A nonlinear model has at least one nonlinear equation in either the constraint or the objective function.

Nonlinear relationships in nonlinear programming models can be represented by:

Which of the following is a step for solving nonlinear programming models?

Relationships in linear programming models can be represented by:

In the era of Big Data, advanced software programs such as Solver can be used to navigate large number variables and constraints.

The final value in the variable cells of the sensitivity report of nonlinear programming models can indicate:

The availability of more data allows organizations to explore, formulate, and solve previously unsolvable problems.

Which of the following is a step for formulating nonlinear programming models?

Solving nonlinear programming models may be more difficult than solving linear programming models because:

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

Mathematical modeling of real-world business situations involves:

Which of the following distinguishes the sensitivity reports of nonlinear programming models from the sensitivity reports of regular linear programming models?

Which of the following must be satisfied in a nonlinear programming model?

In certain situations, a decision maker may choose nonlinear programming models in exchange for:

When solving linear or nonlinear programming models, a constraint with a zero slack variable is a binding constraint.

Nonlinear relationships in nonlinear programming models can be represented by:

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