Question 1

Consider the following linear programming problem: Maximize   Subject to       The above linear programming problem:

Accepted Answer

A) has only one optimal solution 
B) has more than one optimal solution 
C) exhibits infeasibility 
D) exhibits unboundedness 
A) has only one optimal solution 
B) has more than one optimal solution 
C) exhibits infeasibility 
D) exhibits unboundedness

Question 2

The most important solution method for linear programming problems is known as the:

Accepted Answer

A) spreadsheet method 
B) solution mix method 
C) complex method 
D) simplex method 
A) spreadsheet method 
B) solution mix method 
C) complex method 
D) simplex method

Question 3

The solution of a linear programming problem using Microsoft Excel typically involves the following three stages:

Accepted Answer

A) formulating the problem,invoking Solver,and sensitivity analysis 
B) formulating the problem,graphing the problem,and sensitivity analysis 
C) the changing cells,the target cells,and the constraints 
D) the inputs,the changing cells,and the outputs 
A) formulating the problem,invoking Solver,and sensitivity analysis 
B) formulating the problem,graphing the problem,and sensitivity analysis 
C) the changing cells,the target cells,and the constraints 
D) the inputs,the changing cells,and the outputs

Question 4

A linear programming problem with only decision variable(s)can be solved by a graphical solution method.

Accepted Answer

A) 1 
B) 2 
C) 3 
D) 4 
A) 1 
B) 2 
C) 3 
D) 4

Question 5

What are the decision variables in this problem?

Accepted Answer

The decision variabl

Question 6

Nonbinding constraints will always have slack,which is the difference between the two sides of the inequality in the constraint equation.

Accepted Answer

A) True 
 B)False

Question 7

If a constraint has the equation   ,then the slope of the constraint line is function line is -2:

Accepted Answer

A) True 
 B)False

Question 8

Every linear programming problem involves optimizing a:

Accepted Answer

A) linear regression model subject to several linear constraints 
B) linear function subject to several linear constraints 
C) linear function subject to several non-linear constraints 
D) non-linear function subject to several linear constraints 
A) linear regression model subject to several linear constraints 
B) linear function subject to several linear constraints 
C) linear function subject to several non-linear constraints 
D) non-linear function subject to several linear constraints

Question 9

(A)Determine how the company can meet its goal.Assume that Adam will not produce any units in either month that it cannot sell in that month.
(B)Referring to (A),suppose Adam wants to see what will happen if customer demands for each product in each month simultaneously change by a factor 1 + k.Revise the model so that you can use the SolverTable add-in to investigate the effect of this change on total revenue as k varies from -0.3 to 0.3 in increments of 0.1.Does revenue change in a linear manner over this range? Can you explain intuitively why it changes in the way it does?

Accepted Answer

The answer of (A)Determine how the company can meet its...

Question 10

When the proportionality property of LP models is violated,then we generally must use non-linear optimization.

Accepted Answer

A) True 
 B)False

Question 11

All optimization problems include decision variables,an objective function,and constraints.

Accepted Answer

A) True 
 B)False

Consider the following linear programming problem: Maximize Subject to The above linear programming problem:

The most important solution method for linear programming problems is known as the:

The solution of a linear programming problem using Microsoft Excel typically involves the following three stages:

A linear programming problem with only decision variable(s)can be solved by a graphical solution method.

What are the decision variables in this problem?

Nonbinding constraints will always have slack,which is the difference between the two sides of the inequality in the constraint equation.

If a constraint has the equation ,then the slope of the constraint line is function line is -2:

Every linear programming problem involves optimizing a:

When the proportionality property of LP models is violated,then we generally must use non-linear optimization.

All optimization problems include decision variables,an objective function,and constraints.

Introduction to Data Analysis and Decision Making

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, binomial, poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Optimization Modeling: Applications

Introduction to Simulation Modeling

Simulation Models

Filters

Exam 13: Introduction to Optimization Modeling

Consider the following linear programming problem: Maximize Subject to The above linear programming problem:

The most important solution method for linear programming problems is known as the:

The solution of a linear programming problem using Microsoft Excel typically involves the following three stages:

A linear programming problem with only decision variable(s)can be solved by a graphical solution method.

What are the decision variables in this problem?

Nonbinding constraints will always have slack,which is the difference between the two sides of the inequality in the constraint equation.

If a constraint has the equation ,then the slope of the constraint line is function line is -2:

Every linear programming problem involves optimizing a:

When the proportionality property of LP models is violated,then we generally must use non-linear optimization.

All optimization problems include decision variables,an objective function,and constraints.

Introduction to Data Analysis and Decision Making

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, binomial, poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Optimization Modeling: Applications

Introduction to Simulation Modeling

Simulation Models

Filters