Question 1

What are the objective function coefficients for X1 and X2 based on the following Risk Solver Platform (RSP) sensitivity output?

Accepted Answer

Coefficien

Question 2

Consider the following linear programming model and Risk Solver Platform (RSP) sensitivity output. What is the optimal objective function value if the RHS of the first constraint increases to 18?

Accepted Answer

Shadow price of first constrai

Question 3

A change in the right hand side of a constraint changes

Accepted Answer

A) the slope of the objective function 
B) objective function coefficients 
C) other right hand sides 
D) the feasible region 
A) the slope of the objective function 
B) objective function coefficients 
C) other right hand sides 
D) the feasible region

Question 4

Is the optimal solution to this problem unique, or is there an alternate optimal solution? Explain your reasoning.

Accepted Answer

Alternate optimal solutions ex

Question 5

If the shadow price for a resource is 0 and 150 units of the resource are added what happens to the objective function value?

Accepted Answer

A) increase of 150 
B) increases more than 0 but less than 150 
C) no increase 
D) increases but by an unknown amount 
A) increase of 150 
B) increases more than 0 but less than 150 
C) no increase 
D) increases but by an unknown amount

Question 6

Use slack variables to rewrite this problem so that all its constraints are equality constraints.

Accepted Answer

The answer of Use slack variables to rewrite this problem...

Question 7

Solve this problem graphically. What is the optimal solution and what constraints are binding at the optimal solution?

Accepted Answer

Obj = 30 X₁ = 0 X₂ = 1

Question 8

The Simplex method works by first

Accepted Answer

A) identifying any basic feasible solution. 
B) choosing the largest value for X1. 
C) setting X1 at one-half of the its maximum value. 
D) going directly to the optimal solution. 
A) identifying any basic feasible solution. 
B) choosing the largest value for X1. 
C) setting X1 at one-half of the its maximum value. 
D) going directly to the optimal solution.

Question 9

The coefficients in an LP model (cj, aij, bj) represent

Accepted Answer

A) random variables. 
B) numeric constants. 
C) random constants. 
D) numeric variables. 
A) random variables. 
B) numeric constants. 
C) random constants. 
D) numeric variables.

Question 10

Solve this problem graphically. What is the optimal solution and what constraints are binding at the optimal solution?

Accepted Answer

Obj = 26 X₁ = 2.5 X₂ =

Question 11

If the shadow price for a resource is 0 and 150 units of the resource are added what happens to the optimal solution?

Accepted Answer

A) increases by an unknown amount 
B) increases more than 0 but less than 150 
C) no change 
D) decreases by an unknown amount 
A) increases by an unknown amount 
B) increases more than 0 but less than 150 
C) no change 
D) decreases by an unknown amount

Question 12

The solution to an LP problem is degenerate if

Accepted Answer

A) the right hand sides of any of the constraints have an allowable increase or allowable decrease of zero. 
B) the shadow prices of any of the constraints have an allowable increase or allowable decrease of infinity. 
C) the objective coefficients of any of the variables have an allowable increase or allowable decrease of zero. 
D) the shadow prices of any of the constraints have an allowable increase or allowable decrease of zero. 
A) the right hand sides of any of the constraints have an allowable increase or allowable decrease of zero. 
B) the shadow prices of any of the constraints have an allowable increase or allowable decrease of infinity. 
C) the objective coefficients of any of the variables have an allowable increase or allowable decrease of zero. 
D) the shadow prices of any of the constraints have an allowable increase or allowable decrease of zero.

Question 13

When a solution is degenerate the shadow prices and their ranges

Accepted Answer

A) may be interpreted in the usual way but they may not be unique. 
B) must be disregarded. 
C) are always valid and unique. 
D) are always understated 
A) may be interpreted in the usual way but they may not be unique. 
B) must be disregarded. 
C) are always valid and unique. 
D) are always understated

Question 14

Why might a decision maker prefer a solution in the interior of the feasible region of a linear programming problem?

Accepted Answer

A) Such a solution has a better objective function value than any other solution 
B) Such a solution is likely to remain feasible if some of the coefficients in the problem change 
C) The decision maker is not sure if he/she wants to maximize or minimize the objective 
D) Such a solution has more binding constraints 
A) Such a solution has a better objective function value than any other solution 
B) Such a solution is likely to remain feasible if some of the coefficients in the problem change 
C) The decision maker is not sure if he/she wants to maximize or minimize the objective 
D) Such a solution has more binding constraints

Question 15

The optimization technique that locates solutions in the interior of the feasible region is known as _____?

Accepted Answer

A) sub-optimal optimization 
B) sensitivity analysis 
C) robust optimization 
D) USET optimization 
A) sub-optimal optimization 
B) sensitivity analysis 
C) robust optimization 
D) USET optimization

Question 16

Which of the constraints are binding at the optimal solution for the following problem and Risk Solver Platform (RSP) sensitivity output?

Accepted Answer

The answer of Which of the constraints are binding at...

Question 17

What is the smallest value of the objective function coefficient X1 can assume without changing the optimal solution?

Accepted Answer

Coefficien

Question 18

A change in the right hand side of a binding constraint may change all of the following except

Accepted Answer

A) optimal value of the decision variables 
B) slack values 
C) other right hand sides 
D) objective function value 
A) optimal value of the decision variables 
B) slack values 
C) other right hand sides 
D) objective function value

Question 19

The following questions are based on the problem below and accompanying Risk Solver Platform (RSP) sensitivity report.
Carlton construction is supplying building materials for a new mall construction project in Kansas. Their contract calls for a total of 250,000 tons of material to be delivered over a three-week period. Carlton's supply depot has access to three modes of transportation: a trucking fleet, railway delivery, and air cargo transport. Their contract calls for 120,000 tons delivered by the end of week one, 80% of the total delivered by the end of week two, and the entire amount delivered by the end of week three. Contracts in place with the transportation companies call for at least 45% of the total delivered be delivered by trucking, at least 40% of the total delivered be delivered by railway, and up to 15% of the total delivered be delivered by air cargo. Unfortunately, competing demands limit the availability of each mode of transportation each of the three weeks to the following levels (all in thousands of tons):
   The following is the LP model for this logistics problem.
    
-Refer to Exhibit 4.1. Should the company negotiate for additional air delivery capacity?

Accepted Answer

No. The shadow price

Question 20

Constraint 3 is a non-binding constraint in the final solution to a maximization problem. Complete the following entry for the Risk Solver Platform (RSP) sensitivity report. Cell labels are included to ease of reference.

Accepted Answer

The answer of Constraint 3 is a non-binding constraint in...

What are the objective function coefficients for X₁ and X₂ based on the following Risk Solver Platform (RSP) sensitivity output?

Consider the following linear programming model and Risk Solver Platform (RSP) sensitivity output. What is the optimal objective function value if the RHS of the first constraint increases to 18?

A change in the right hand side of a constraint changes

Is the optimal solution to this problem unique, or is there an alternate optimal solution? Explain your reasoning.

If the shadow price for a resource is 0 and 150 units of the resource are added what happens to the objective function value?

Use slack variables to rewrite this problem so that all its constraints are equality constraints.

Solve this problem graphically. What is the optimal solution and what constraints are binding at the optimal solution?

The Simplex method works by first

The coefficients in an LP model (c_j, a_ij, b_j) represent

Solve this problem graphically. What is the optimal solution and what constraints are binding at the optimal solution?

If the shadow price for a resource is 0 and 150 units of the resource are added what happens to the optimal solution?

The solution to an LP problem is degenerate if

When a solution is degenerate the shadow prices and their ranges

Why might a decision maker prefer a solution in the interior of the feasible region of a linear programming problem?

The optimization technique that locates solutions in the interior of the feasible region is known as _____?

Which of the constraints are binding at the optimal solution for the following problem and Risk Solver Platform (RSP) sensitivity output?

What is the smallest value of the objective function coefficient X₁ can assume without changing the optimal solution?

A change in the right hand side of a binding constraint may change all of the following except

Constraint 3 is a non-binding constraint in the final solution to a maximization problem. Complete the following entry for the Risk Solver Platform (RSP) sensitivity report. Cell labels are included to ease of reference.

Introduction to Modeling and Decision Analysis

Introduction to Optimization and Linear Programming

Modeling and Solving Lp Problems in a Spreadsheet

Network Modeling

Integer Linear Programming

Goal Programming and Multiple Objective Optimization

Nonlinear Programming and Evolutionary Optimization

Regression Analysis

Discriminant Analysis

Time Series Forecasting

Introduction to Simulation Using Risk Solver Platform

Queuing Theory

Decision Analysis

Project Management Online

Filters

Exam 4: Sensitivity Analysis and the Simplex Method

What are the objective function coefficients for X1 and X2 based on the following Risk Solver Platform (RSP) sensitivity output?

Consider the following linear programming model and Risk Solver Platform (RSP) sensitivity output. What is the optimal objective function value if the RHS of the first constraint increases to 18?

A change in the right hand side of a constraint changes

Is the optimal solution to this problem unique, or is there an alternate optimal solution? Explain your reasoning.

If the shadow price for a resource is 0 and 150 units of the resource are added what happens to the objective function value?

Use slack variables to rewrite this problem so that all its constraints are equality constraints.

Solve this problem graphically. What is the optimal solution and what constraints are binding at the optimal solution?

The Simplex method works by first

The coefficients in an LP model (cj, aij, bj) represent

Solve this problem graphically. What is the optimal solution and what constraints are binding at the optimal solution?

If the shadow price for a resource is 0 and 150 units of the resource are added what happens to the optimal solution?

The solution to an LP problem is degenerate if

When a solution is degenerate the shadow prices and their ranges

Why might a decision maker prefer a solution in the interior of the feasible region of a linear programming problem?

The optimization technique that locates solutions in the interior of the feasible region is known as _____?

Which of the constraints are binding at the optimal solution for the following problem and Risk Solver Platform (RSP) sensitivity output?

What is the smallest value of the objective function coefficient X1 can assume without changing the optimal solution?

A change in the right hand side of a binding constraint may change all of the following except

Constraint 3 is a non-binding constraint in the final solution to a maximization problem. Complete the following entry for the Risk Solver Platform (RSP) sensitivity report. Cell labels are included to ease of reference.

Introduction to Modeling and Decision Analysis

Introduction to Optimization and Linear Programming

Modeling and Solving Lp Problems in a Spreadsheet

Network Modeling

Integer Linear Programming

Goal Programming and Multiple Objective Optimization

Nonlinear Programming and Evolutionary Optimization

Regression Analysis

Discriminant Analysis

Time Series Forecasting

Introduction to Simulation Using Risk Solver Platform

Queuing Theory

Decision Analysis

Project Management Online

Filters

What are the objective function coefficients for X₁ and X₂ based on the following Risk Solver Platform (RSP) sensitivity output?

The coefficients in an LP model (c_j, a_ij, b_j) represent

What is the smallest value of the objective function coefficient X₁ can assume without changing the optimal solution?