Deck 3: Linear Programming: Sensitivity Analysis and Interpretation of Solution

ملء الشاشة (f)
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سؤال
Any change to the objective function coefficient of a variable that is positive in the optimal solution will change the optimal solution.
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سؤال
When the right-hand sides of two constraints are each increased by one unit, the objective function value will be adjusted by the sum of the constraints' dual prices.
سؤال
If the optimal value of a decision variable is zero and its reduced cost is zero, this indicates that alternative optimal solutions exist.
سؤال
In order to tell the impact of a change in a constraint coefficient, the change must be made and then the model resolved.
سؤال
Relevant costs should be reflected in the objective function, but sunk costs should not.
سؤال
The amount of a sunk cost will vary depending on the values of the decision variables.
سؤال
The dual price associated with a constraint is the change in the value of the solution per unit decrease in the right-hand side of the constraint.
سؤال
Decreasing the objective function coefficient of a variable to its lower limit will create a revised problem that is unbounded.
سؤال
Classical sensitivity analysis provides no information about changes resulting from a change in the coefficient of a variable in a constraint.
سؤال
The 100 percent rule can be applied to changes in both objective function coefficients and right-hand sides at the same time.
سؤال
If the range of feasibility for b1 is between 16 and 37, then if b1 = 22 the optimal solution will not change from the original optimal solution.
سؤال
If the range of feasibility indicates that the original amount of a resource, which was 20, can increase by 5, then the amount of the resource can increase to 25.
سؤال
For a minimization problem, a positive dual price indicates the value of the objective function will increase.
سؤال
If the dual price for the right-hand side of a ≤ constraint is zero, there is no upper limit on its range of feasibility.
سؤال
There is a dual price for every decision variable in a model.
سؤال
The 100% Rule does not imply that the optimal solution will necessarily change if the percentage exceeds 100%.
سؤال
A negative dual price indicates that increasing the right-hand side of the associated constraint would be detrimental to the objective.
سؤال
The dual price for a percentage constraint provides a direct answer to questions about the effect of increases or decreases in that percentage.
سؤال
For any constraint, either its slack/surplus value must be zero or its dual price must be zero.
سؤال
The reduced cost for a positive decision variable is 0.
سؤال
Sensitivity analysis information in computer output is based on the assumption of

A) no coefficient changes.
B) one coefficient changes.
C) two coefficients change.
D) all coefficients change.
سؤال
The range of feasibility measures

A) the right-hand-side values for which the objective function value will not change.
B) the right-hand-side values for which the values of the decision variables will not change.
C) the right-hand-side values for which the dual prices will not change.
D) each of these choices are true.
سؤال
A section of output from The Management Scientist is shown here. <strong>A section of output from The Management Scientist is shown here.   What will happen if the right-hand-side for constraint 2 increases by 200?</strong> A) Nothing. The values of the decision variables, the dual prices, and the objective function will all remain the same. B) The value of the objective function will change, but the values of the decision variables and the dual prices will remain the same. C) The same decision variables will be positive, but their values, the objective function value, and the dual prices will change. D) The problem will need to be resolved to find the new optimal solution and dual price. <div style=padding-top: 35px> What will happen if the right-hand-side for constraint 2 increases by 200?

A) Nothing. The values of the decision variables, the dual prices, and the objective function will all remain the same.
B) The value of the objective function will change, but the values of the decision variables and the dual prices will remain the same.
C) The same decision variables will be positive, but their values, the objective function value, and the dual prices will change.
D) The problem will need to be resolved to find the new optimal solution and dual price.
سؤال
To solve a linear programming problem with thousands of variables and constraints

A) a personal computer can be used.
B) a mainframe computer is required.
C) the problem must be partitioned into subparts.
D) unique software would need to be developed.
سؤال
​Sensitivity analysis is often referred to as

A) ​feasibility testing.
B) ​duality analysis.
C) ​alternative analysis.
D) ​postoptimality analysis.
سؤال
Which of the following is not a question answered by standard sensitivity analysis information?

A) If the right-hand side value of a constraint changes, will the objective function value change?
B) Over what range can a constraint's right-hand side value without the constraint's dual price possibly changing?
C) By how much will the objective function value change if the right-hand side value of a constraint changes beyond the range of feasibility?
D) By how much will the objective function value change if a decision variable's coefficient in the objective function changes within the range of optimality?
سؤال
A section of output from The Management Scientist is shown here. <strong>A section of output from The Management Scientist is shown here.   What will happen to the solution if the objective function coefficient for variable 1 decreases by 20?</strong> A) Nothing. The values of the decision variables, the dual prices, and the objective function will all remain the same. B) The value of the objective function will change, but the values of the decision variables and the dual prices will remain the same. C) The same decision variables will be positive, but their values, the objective function value, and the dual prices will change. D) The problem will need to be resolved to find the new optimal solution and dual price. <div style=padding-top: 35px> What will happen to the solution if the objective function coefficient for variable 1 decreases by 20?

A) Nothing. The values of the decision variables, the dual prices, and the objective function will all remain the same.
B) The value of the objective function will change, but the values of the decision variables and the dual prices will remain the same.
C) The same decision variables will be positive, but their values, the objective function value, and the dual prices will change.
D) The problem will need to be resolved to find the new optimal solution and dual price.
سؤال
​The cost that varies depending on the values of the decision variables is a

A) ​reduced cost.
B) ​relevant cost.
C) ​sunk cost.
D) ​dual cost.
سؤال
An objective function reflects the relevant cost of labor hours used in production rather than treating them as a sunk cost. The correct interpretation of the dual price associated with the labor hours constraint is

A) the maximum premium (say for overtime) over the normal price that the company would be willing to pay.
B) the upper limit on the total hourly wage the company would pay.
C) the reduction in hours that could be sustained before the solution would change.
D) the number of hours by which the right-hand side can change before there is a change in the solution point.
سؤال
A negative dual price for a constraint in a minimization problem means

A) as the right-hand side increases, the objective function value will increase.
B) as the right-hand side decreases, the objective function value will increase.
C) as the right-hand side increases, the objective function value will decrease.
D) as the right-hand side decreases, the objective function value will decrease.
سؤال
A constraint with a positive slack value

A) will have a positive dual price.
B) will have a negative dual price.
C) will have a dual price of zero.
D) has no restrictions for its dual price.
سؤال
When the cost of a resource is sunk, then the dual price can be interpreted as the

A) minimum amount the firm should be willing to pay for one additional unit of the resource.
B) maximum amount the firm should be willing to pay for one additional unit of the resource.
C) minimum amount the firm should be willing to pay for multiple additional units of the resource.
D) maximum amount the firm should be willing to pay for multiple additional units of the resource.
سؤال
​Sensitivity analysis is concerned with how certain changes affect

A) ​the feasible solution.
B) ​the unconstrained solution.
C) ​the optimal solution.
D) ​the degenerative solution.
سؤال
​The dual price for a < constraint

A) ​will always be < 0.
B) ​will always be > 0.
C) ​will be < 0 in a minimization problem and > 0 in a maximization problem.
D) ​will always equal 0.
سؤال
If a decision variable is not positive in the optimal solution, its reduced cost is

A) what its objective function value would need to be before it could become positive.
B) the amount its objective function value would need to improve before it could become positive.
C) zero.
D) its dual price.
سؤال
The dual price measures, per unit increase in the right hand side of the constraint,

A) the increase in the value of the optimal solution.
B) the decrease in the value of the optimal solution.
C) the improvement in the value of the optimal solution.
D) the change in the value of the optimal solution.
سؤال
​A cost that is incurred no matter what values the decision variables assume is

A) ​a reduced cost.
B) ​an optimal cost.
C) ​a sunk cost.
D) ​a dual cost.
سؤال
The 100% Rule compares

A) proposed changes to allowed changes.
B) new values to original values.
C) objective function changes to right-hand side changes.
D) dual prices to reduced costs.
سؤال
The amount the objective function coefficient of a decision variable would have to improve before that variable would have a positive value in the solution is the

A) dual price.
B) surplus variable.
C) reduced cost.
D) upper limit.
سؤال
The amount by which an objective function coefficient can change before a different set of values for the decision variables becomes optimal is the

A) optimal solution.
B) dual solution.
C) range of optimality.
D) range of feasibility.
سؤال
Use the following Management Scientist output to answer the questions.
LINEAR PROGRAMMING PROBLEM
MAX 31X1+35X2+32X3
S.T.
1) 3X1+5X2+2X3>90
2) 6X1+7X2+8X3<150
3) 5X1+3X2+3X3<120
OPTIMAL SOLUTION
Objective Function Value = 763.333 Use the following Management Scientist output to answer the questions. LINEAR PROGRAMMING PROBLEM MAX 31X1+35X2+32X3 S.T. 1) 3X1+5X2+2X3>90 2) 6X1+7X2+8X3<150 3) 5X1+3X2+3X3<120 OPTIMAL SOLUTION Objective Function Value = 763.333     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.Give the solution to the problem. b.Which constraints are binding? c.What would happen if the coefficient of x<sub>1</sub> increased by 3? d.What would happen if the right-hand side of constraint 1 increased by 10?<div style=padding-top: 35px> Use the following Management Scientist output to answer the questions. LINEAR PROGRAMMING PROBLEM MAX 31X1+35X2+32X3 S.T. 1) 3X1+5X2+2X3>90 2) 6X1+7X2+8X3<150 3) 5X1+3X2+3X3<120 OPTIMAL SOLUTION Objective Function Value = 763.333     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.Give the solution to the problem. b.Which constraints are binding? c.What would happen if the coefficient of x<sub>1</sub> increased by 3? d.What would happen if the right-hand side of constraint 1 increased by 10?<div style=padding-top: 35px> OBJECTIVE COEFFICIENT RANGES Use the following Management Scientist output to answer the questions. LINEAR PROGRAMMING PROBLEM MAX 31X1+35X2+32X3 S.T. 1) 3X1+5X2+2X3>90 2) 6X1+7X2+8X3<150 3) 5X1+3X2+3X3<120 OPTIMAL SOLUTION Objective Function Value = 763.333     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.Give the solution to the problem. b.Which constraints are binding? c.What would happen if the coefficient of x<sub>1</sub> increased by 3? d.What would happen if the right-hand side of constraint 1 increased by 10?<div style=padding-top: 35px> RIGHT HAND SIDE RANGES Use the following Management Scientist output to answer the questions. LINEAR PROGRAMMING PROBLEM MAX 31X1+35X2+32X3 S.T. 1) 3X1+5X2+2X3>90 2) 6X1+7X2+8X3<150 3) 5X1+3X2+3X3<120 OPTIMAL SOLUTION Objective Function Value = 763.333     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.Give the solution to the problem. b.Which constraints are binding? c.What would happen if the coefficient of x<sub>1</sub> increased by 3? d.What would happen if the right-hand side of constraint 1 increased by 10?<div style=padding-top: 35px>
a.Give the solution to the problem.
b.Which constraints are binding?
c.What would happen if the coefficient of x1 increased by 3?
d.What would happen if the right-hand side of constraint 1 increased by 10?
سؤال
Excel's Solver tool has been used in the spreadsheet below to solve a linear programming problem with a minimization objective function and all ≥ constraints. Excel's Solver tool has been used in the spreadsheet below to solve a linear programming problem with a minimization objective function and all ≥ constraints.   ​ a.Give the original linear programming problem. b.Give the complete optimal solution.<div style=padding-top: 35px>
a.Give the original linear programming problem.
b.Give the complete optimal solution.
سؤال
​How can the interpretation of dual prices help provide an economic justification for new technology?
سؤال
Eight of the entries have been deleted from the LINDO output that follows. Use what you know about linear programming to find values for the blanks.
MIN 6 X1 + 7.5 X2 + 10 X3
SUBJECT TO
2) 25 X1 + 35 X2 + 30 X3 >= 2400
3) 2 X1 + 4 X2 + 8 X3 >= 400
END
LP OPTIMUM FOUND AT STEP 2
OBJECTIVE FUNCTION VALUE
1) 612.50000 Eight of the entries have been deleted from the LINDO output that follows. Use what you know about linear programming to find values for the blanks. MIN 6 X1 + 7.5 X2 + 10 X3 SUBJECT TO 2) 25 X1 + 35 X2 + 30 X3 >= 2400 3) 2 X1 + 4 X2 + 8 X3 >= 400 END LP OPTIMUM FOUND AT STEP 2 OBJECTIVE FUNCTION VALUE 1) 612.50000     NO. ITERATIONS= 2 RANGES IN WHICH THE BASIS IS UNCHANGED:    <div style=padding-top: 35px> Eight of the entries have been deleted from the LINDO output that follows. Use what you know about linear programming to find values for the blanks. MIN 6 X1 + 7.5 X2 + 10 X3 SUBJECT TO 2) 25 X1 + 35 X2 + 30 X3 >= 2400 3) 2 X1 + 4 X2 + 8 X3 >= 400 END LP OPTIMUM FOUND AT STEP 2 OBJECTIVE FUNCTION VALUE 1) 612.50000     NO. ITERATIONS= 2 RANGES IN WHICH THE BASIS IS UNCHANGED:    <div style=padding-top: 35px> NO. ITERATIONS= 2
RANGES IN WHICH THE BASIS IS UNCHANGED: Eight of the entries have been deleted from the LINDO output that follows. Use what you know about linear programming to find values for the blanks. MIN 6 X1 + 7.5 X2 + 10 X3 SUBJECT TO 2) 25 X1 + 35 X2 + 30 X3 >= 2400 3) 2 X1 + 4 X2 + 8 X3 >= 400 END LP OPTIMUM FOUND AT STEP 2 OBJECTIVE FUNCTION VALUE 1) 612.50000     NO. ITERATIONS= 2 RANGES IN WHICH THE BASIS IS UNCHANGED:    <div style=padding-top: 35px> Eight of the entries have been deleted from the LINDO output that follows. Use what you know about linear programming to find values for the blanks. MIN 6 X1 + 7.5 X2 + 10 X3 SUBJECT TO 2) 25 X1 + 35 X2 + 30 X3 >= 2400 3) 2 X1 + 4 X2 + 8 X3 >= 400 END LP OPTIMUM FOUND AT STEP 2 OBJECTIVE FUNCTION VALUE 1) 612.50000     NO. ITERATIONS= 2 RANGES IN WHICH THE BASIS IS UNCHANGED:    <div style=padding-top: 35px>
سؤال
In a linear programming problem, the binding constraints for the optimal solution are
5X + 3Y ≤ 30
2X + 5Y ≤ 20
a.Fill in the blanks in the following sentence:As long as the slope of the objective function stays between _______ and _______, the current optimal solution point will remain optimal.
b.Which of these objective functions will lead to the same optimal solution?1) 2X + 1Y 2) 7X + 8Y 3) 80X + 60Y 4) 25X + 35Y
سؤال
​Describe each of the sections of output that come from The Management Scientist and how you would use each.
سؤال
LINDO output is given for the following linear programming problem.
MIN 12 X1 + 10 X2 + 9 X3
SUBJECT TO
2) 5 X1 + 8 X2 + 5 X3 >= 60
3) 8 X1 + 10 X2 + 5 X3 >= 80
END
LP OPTIMUM FOUND AT STEP 1
OBJECTIVE FUNCTION VALUE
1) 80.000000 LINDO output is given for the following linear programming problem. MIN 12 X1 + 10 X2 + 9 X3 SUBJECT TO 2) 5 X1 + 8 X2 + 5 X3 >= 60 3) 8 X1 + 10 X2 + 5 X3 >= 80 END LP OPTIMUM FOUND AT STEP 1 OBJECTIVE FUNCTION VALUE 1) 80.000000     NO. ITERATIONS= 1 RANGES IN WHICH THE BASIS IS UNCHANGED:     a.What is the solution to the problem? b.Which constraints are binding? c.Interpret the reduced cost for x<sub>1</sub>. d.Interpret the dual price for constraint 2. e.What would happen if the cost of x<sub>1</sub> dropped to 10 and the cost of x<sub>2</sub> increased to 12?<div style=padding-top: 35px> LINDO output is given for the following linear programming problem. MIN 12 X1 + 10 X2 + 9 X3 SUBJECT TO 2) 5 X1 + 8 X2 + 5 X3 >= 60 3) 8 X1 + 10 X2 + 5 X3 >= 80 END LP OPTIMUM FOUND AT STEP 1 OBJECTIVE FUNCTION VALUE 1) 80.000000     NO. ITERATIONS= 1 RANGES IN WHICH THE BASIS IS UNCHANGED:     a.What is the solution to the problem? b.Which constraints are binding? c.Interpret the reduced cost for x<sub>1</sub>. d.Interpret the dual price for constraint 2. e.What would happen if the cost of x<sub>1</sub> dropped to 10 and the cost of x<sub>2</sub> increased to 12?<div style=padding-top: 35px> NO. ITERATIONS= 1
RANGES IN WHICH THE BASIS IS UNCHANGED: LINDO output is given for the following linear programming problem. MIN 12 X1 + 10 X2 + 9 X3 SUBJECT TO 2) 5 X1 + 8 X2 + 5 X3 >= 60 3) 8 X1 + 10 X2 + 5 X3 >= 80 END LP OPTIMUM FOUND AT STEP 1 OBJECTIVE FUNCTION VALUE 1) 80.000000     NO. ITERATIONS= 1 RANGES IN WHICH THE BASIS IS UNCHANGED:     a.What is the solution to the problem? b.Which constraints are binding? c.Interpret the reduced cost for x<sub>1</sub>. d.Interpret the dual price for constraint 2. e.What would happen if the cost of x<sub>1</sub> dropped to 10 and the cost of x<sub>2</sub> increased to 12?<div style=padding-top: 35px> LINDO output is given for the following linear programming problem. MIN 12 X1 + 10 X2 + 9 X3 SUBJECT TO 2) 5 X1 + 8 X2 + 5 X3 >= 60 3) 8 X1 + 10 X2 + 5 X3 >= 80 END LP OPTIMUM FOUND AT STEP 1 OBJECTIVE FUNCTION VALUE 1) 80.000000     NO. ITERATIONS= 1 RANGES IN WHICH THE BASIS IS UNCHANGED:     a.What is the solution to the problem? b.Which constraints are binding? c.Interpret the reduced cost for x<sub>1</sub>. d.Interpret the dual price for constraint 2. e.What would happen if the cost of x<sub>1</sub> dropped to 10 and the cost of x<sub>2</sub> increased to 12?<div style=padding-top: 35px>
a.What is the solution to the problem?
b.Which constraints are binding?
c.Interpret the reduced cost for x1.
d.Interpret the dual price for constraint 2.
e.What would happen if the cost of x1 dropped to 10 and the cost of x2 increased to 12?
سؤال
Portions of a Management Scientist output are shown below. Use what you know about the solution of linear programs to fill in the ten blanks.
LINEAR PROGRAMMING PROBLEM
MAX 12X1+9X2+7X3
S.T.
1) 3X1+5X2+4X3<150
2) 2X1+1X2+1X3<64
3) 1X1+2X2+1X3<80
4) 2X1+4X2+3X3>116
OPTIMAL SOLUTION
Objective Function Value = 336.000 Portions of a Management Scientist output are shown below. Use what you know about the solution of linear programs to fill in the ten blanks. LINEAR PROGRAMMING PROBLEM MAX 12X1+9X2+7X3 S.T. 1) 3X1+5X2+4X3<150 2) 2X1+1X2+1X3<64 3) 1X1+2X2+1X3<80 4) 2X1+4X2+3X3>116 OPTIMAL SOLUTION Objective Function Value = 336.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES  <div style=padding-top: 35px> Portions of a Management Scientist output are shown below. Use what you know about the solution of linear programs to fill in the ten blanks. LINEAR PROGRAMMING PROBLEM MAX 12X1+9X2+7X3 S.T. 1) 3X1+5X2+4X3<150 2) 2X1+1X2+1X3<64 3) 1X1+2X2+1X3<80 4) 2X1+4X2+3X3>116 OPTIMAL SOLUTION Objective Function Value = 336.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES  <div style=padding-top: 35px> OBJECTIVE COEFFICIENT RANGES Portions of a Management Scientist output are shown below. Use what you know about the solution of linear programs to fill in the ten blanks. LINEAR PROGRAMMING PROBLEM MAX 12X1+9X2+7X3 S.T. 1) 3X1+5X2+4X3<150 2) 2X1+1X2+1X3<64 3) 1X1+2X2+1X3<80 4) 2X1+4X2+3X3>116 OPTIMAL SOLUTION Objective Function Value = 336.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES  <div style=padding-top: 35px> RIGHT HAND SIDE RANGES Portions of a Management Scientist output are shown below. Use what you know about the solution of linear programs to fill in the ten blanks. LINEAR PROGRAMMING PROBLEM MAX 12X1+9X2+7X3 S.T. 1) 3X1+5X2+4X3<150 2) 2X1+1X2+1X3<64 3) 1X1+2X2+1X3<80 4) 2X1+4X2+3X3>116 OPTIMAL SOLUTION Objective Function Value = 336.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES  <div style=padding-top: 35px>
سؤال
​How would sensitivity analysis of a linear program be undertaken if one wishes to consider simultaneous changes for
both the right-hand-side values and objective function.
سؤال
Excel's Solver tool has been used in the spreadsheet below to solve a linear programming problem with a maximization objective function and all ≤ constraints. Excel's Solver tool has been used in the spreadsheet below to solve a linear programming problem with a maximization objective function and all ≤ constraints.   ​ a.Give the original linear programming problem. b.Give the complete optimal solution.<div style=padding-top: 35px>
a.Give the original linear programming problem.
b.Give the complete optimal solution.
سؤال
​Explain the two interpretations of dual prices based on the accounting assumptions made in calculating the objective
function coefficients.
سؤال
The optimal solution of the linear programming problem is at the intersection of constraints 1 and 2.
Max
2x1 + x2
s.t.
4x1 + 1x2 ≤ 400
4x1 + 3x2 ≤ 600
1x1 + 2x2 ≤ 300
x1 , x2 ≥ 0

a.​Over what range can the coefficient of x1 vary before the current solution is no longer optimal?
b.​Over what range can the coefficient of x2 vary before the current solution is no longer optimal?
c.Compute the dual prices for the three constraints.
سؤال
The binding constraints for this problem are the first and second.
Min
x1 + 2x2
s.t.
x1 + x2 ≥ 300
2x1 + x2 ≥ 400
2x1 + 5x2 ≤ 750
x1 , x2 ≥ 0
a.Keeping c2 fixed at 2, over what range can c1 vary before there is a change in the optimal solution point?
b.Keeping c1 fixed at 1, over what range can c2 vary before there is a change in the optimal solution point?
c.If the objective function becomes Min 1.5x1 + 2x2, what will be the optimal values of x1, x2, and the objective function?
d.If the objective function becomes Min 7x1 + 6x2, what constraints will be binding?
e.Find the dual price for each constraint in the original problem.
سؤال
​How is sensitivity analysis used in linear programming? Given an example of what type of questions that can be
answered.
سؤال
Use the following Management Scientist output to answer the questions.
MIN 4X1+5X2+6X3
S.T.
1) X1+X2+X3<85
2) 3X1+4X2+2X3>280
3) 2X1+4X2+4X3>320
Objective Function Value = 400.000 Use the following Management Scientist output to answer the questions. MIN 4X1+5X2+6X3 S.T. 1) X1+X2+X3<85 2) 3X1+4X2+2X3>280 3) 2X1+4X2+4X3>320 Objective Function Value = 400.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution, and what is the value of the profit contribution? b.Which constraints are binding? c.What are the dual prices for each resource? Interpret. d.Compute and interpret the ranges of optimality. e.Compute and interpret the ranges of feasibility.<div style=padding-top: 35px> Use the following Management Scientist output to answer the questions. MIN 4X1+5X2+6X3 S.T. 1) X1+X2+X3<85 2) 3X1+4X2+2X3>280 3) 2X1+4X2+4X3>320 Objective Function Value = 400.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution, and what is the value of the profit contribution? b.Which constraints are binding? c.What are the dual prices for each resource? Interpret. d.Compute and interpret the ranges of optimality. e.Compute and interpret the ranges of feasibility.<div style=padding-top: 35px> OBJECTIVE COEFFICIENT RANGES Use the following Management Scientist output to answer the questions. MIN 4X1+5X2+6X3 S.T. 1) X1+X2+X3<85 2) 3X1+4X2+2X3>280 3) 2X1+4X2+4X3>320 Objective Function Value = 400.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution, and what is the value of the profit contribution? b.Which constraints are binding? c.What are the dual prices for each resource? Interpret. d.Compute and interpret the ranges of optimality. e.Compute and interpret the ranges of feasibility.<div style=padding-top: 35px> RIGHT HAND SIDE RANGES Use the following Management Scientist output to answer the questions. MIN 4X1+5X2+6X3 S.T. 1) X1+X2+X3<85 2) 3X1+4X2+2X3>280 3) 2X1+4X2+4X3>320 Objective Function Value = 400.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution, and what is the value of the profit contribution? b.Which constraints are binding? c.What are the dual prices for each resource? Interpret. d.Compute and interpret the ranges of optimality. e.Compute and interpret the ranges of feasibility.<div style=padding-top: 35px>
a.What is the optimal solution, and what is the value of the profit contribution?
b.Which constraints are binding?
c.What are the dual prices for each resource? Interpret.
d.Compute and interpret the ranges of optimality.
e.Compute and interpret the ranges of feasibility.
سؤال
​Explain the connection between reduced costs and the range of optimality, and between dual prices and the range of
feasibility.
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Deck 3: Linear Programming: Sensitivity Analysis and Interpretation of Solution
1
Any change to the objective function coefficient of a variable that is positive in the optimal solution will change the optimal solution.
False
2
When the right-hand sides of two constraints are each increased by one unit, the objective function value will be adjusted by the sum of the constraints' dual prices.
False
3
If the optimal value of a decision variable is zero and its reduced cost is zero, this indicates that alternative optimal solutions exist.
True
4
In order to tell the impact of a change in a constraint coefficient, the change must be made and then the model resolved.
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5
Relevant costs should be reflected in the objective function, but sunk costs should not.
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6
The amount of a sunk cost will vary depending on the values of the decision variables.
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7
The dual price associated with a constraint is the change in the value of the solution per unit decrease in the right-hand side of the constraint.
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8
Decreasing the objective function coefficient of a variable to its lower limit will create a revised problem that is unbounded.
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9
Classical sensitivity analysis provides no information about changes resulting from a change in the coefficient of a variable in a constraint.
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10
The 100 percent rule can be applied to changes in both objective function coefficients and right-hand sides at the same time.
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11
If the range of feasibility for b1 is between 16 and 37, then if b1 = 22 the optimal solution will not change from the original optimal solution.
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12
If the range of feasibility indicates that the original amount of a resource, which was 20, can increase by 5, then the amount of the resource can increase to 25.
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13
For a minimization problem, a positive dual price indicates the value of the objective function will increase.
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14
If the dual price for the right-hand side of a ≤ constraint is zero, there is no upper limit on its range of feasibility.
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15
There is a dual price for every decision variable in a model.
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16
The 100% Rule does not imply that the optimal solution will necessarily change if the percentage exceeds 100%.
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17
A negative dual price indicates that increasing the right-hand side of the associated constraint would be detrimental to the objective.
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18
The dual price for a percentage constraint provides a direct answer to questions about the effect of increases or decreases in that percentage.
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19
For any constraint, either its slack/surplus value must be zero or its dual price must be zero.
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20
The reduced cost for a positive decision variable is 0.
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21
Sensitivity analysis information in computer output is based on the assumption of

A) no coefficient changes.
B) one coefficient changes.
C) two coefficients change.
D) all coefficients change.
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22
The range of feasibility measures

A) the right-hand-side values for which the objective function value will not change.
B) the right-hand-side values for which the values of the decision variables will not change.
C) the right-hand-side values for which the dual prices will not change.
D) each of these choices are true.
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23
A section of output from The Management Scientist is shown here. <strong>A section of output from The Management Scientist is shown here.   What will happen if the right-hand-side for constraint 2 increases by 200?</strong> A) Nothing. The values of the decision variables, the dual prices, and the objective function will all remain the same. B) The value of the objective function will change, but the values of the decision variables and the dual prices will remain the same. C) The same decision variables will be positive, but their values, the objective function value, and the dual prices will change. D) The problem will need to be resolved to find the new optimal solution and dual price. What will happen if the right-hand-side for constraint 2 increases by 200?

A) Nothing. The values of the decision variables, the dual prices, and the objective function will all remain the same.
B) The value of the objective function will change, but the values of the decision variables and the dual prices will remain the same.
C) The same decision variables will be positive, but their values, the objective function value, and the dual prices will change.
D) The problem will need to be resolved to find the new optimal solution and dual price.
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24
To solve a linear programming problem with thousands of variables and constraints

A) a personal computer can be used.
B) a mainframe computer is required.
C) the problem must be partitioned into subparts.
D) unique software would need to be developed.
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25
​Sensitivity analysis is often referred to as

A) ​feasibility testing.
B) ​duality analysis.
C) ​alternative analysis.
D) ​postoptimality analysis.
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26
Which of the following is not a question answered by standard sensitivity analysis information?

A) If the right-hand side value of a constraint changes, will the objective function value change?
B) Over what range can a constraint's right-hand side value without the constraint's dual price possibly changing?
C) By how much will the objective function value change if the right-hand side value of a constraint changes beyond the range of feasibility?
D) By how much will the objective function value change if a decision variable's coefficient in the objective function changes within the range of optimality?
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27
A section of output from The Management Scientist is shown here. <strong>A section of output from The Management Scientist is shown here.   What will happen to the solution if the objective function coefficient for variable 1 decreases by 20?</strong> A) Nothing. The values of the decision variables, the dual prices, and the objective function will all remain the same. B) The value of the objective function will change, but the values of the decision variables and the dual prices will remain the same. C) The same decision variables will be positive, but their values, the objective function value, and the dual prices will change. D) The problem will need to be resolved to find the new optimal solution and dual price. What will happen to the solution if the objective function coefficient for variable 1 decreases by 20?

A) Nothing. The values of the decision variables, the dual prices, and the objective function will all remain the same.
B) The value of the objective function will change, but the values of the decision variables and the dual prices will remain the same.
C) The same decision variables will be positive, but their values, the objective function value, and the dual prices will change.
D) The problem will need to be resolved to find the new optimal solution and dual price.
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28
​The cost that varies depending on the values of the decision variables is a

A) ​reduced cost.
B) ​relevant cost.
C) ​sunk cost.
D) ​dual cost.
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29
An objective function reflects the relevant cost of labor hours used in production rather than treating them as a sunk cost. The correct interpretation of the dual price associated with the labor hours constraint is

A) the maximum premium (say for overtime) over the normal price that the company would be willing to pay.
B) the upper limit on the total hourly wage the company would pay.
C) the reduction in hours that could be sustained before the solution would change.
D) the number of hours by which the right-hand side can change before there is a change in the solution point.
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30
A negative dual price for a constraint in a minimization problem means

A) as the right-hand side increases, the objective function value will increase.
B) as the right-hand side decreases, the objective function value will increase.
C) as the right-hand side increases, the objective function value will decrease.
D) as the right-hand side decreases, the objective function value will decrease.
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31
A constraint with a positive slack value

A) will have a positive dual price.
B) will have a negative dual price.
C) will have a dual price of zero.
D) has no restrictions for its dual price.
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32
When the cost of a resource is sunk, then the dual price can be interpreted as the

A) minimum amount the firm should be willing to pay for one additional unit of the resource.
B) maximum amount the firm should be willing to pay for one additional unit of the resource.
C) minimum amount the firm should be willing to pay for multiple additional units of the resource.
D) maximum amount the firm should be willing to pay for multiple additional units of the resource.
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33
​Sensitivity analysis is concerned with how certain changes affect

A) ​the feasible solution.
B) ​the unconstrained solution.
C) ​the optimal solution.
D) ​the degenerative solution.
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34
​The dual price for a < constraint

A) ​will always be < 0.
B) ​will always be > 0.
C) ​will be < 0 in a minimization problem and > 0 in a maximization problem.
D) ​will always equal 0.
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35
If a decision variable is not positive in the optimal solution, its reduced cost is

A) what its objective function value would need to be before it could become positive.
B) the amount its objective function value would need to improve before it could become positive.
C) zero.
D) its dual price.
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36
The dual price measures, per unit increase in the right hand side of the constraint,

A) the increase in the value of the optimal solution.
B) the decrease in the value of the optimal solution.
C) the improvement in the value of the optimal solution.
D) the change in the value of the optimal solution.
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37
​A cost that is incurred no matter what values the decision variables assume is

A) ​a reduced cost.
B) ​an optimal cost.
C) ​a sunk cost.
D) ​a dual cost.
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38
The 100% Rule compares

A) proposed changes to allowed changes.
B) new values to original values.
C) objective function changes to right-hand side changes.
D) dual prices to reduced costs.
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39
The amount the objective function coefficient of a decision variable would have to improve before that variable would have a positive value in the solution is the

A) dual price.
B) surplus variable.
C) reduced cost.
D) upper limit.
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40
The amount by which an objective function coefficient can change before a different set of values for the decision variables becomes optimal is the

A) optimal solution.
B) dual solution.
C) range of optimality.
D) range of feasibility.
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41
Use the following Management Scientist output to answer the questions.
LINEAR PROGRAMMING PROBLEM
MAX 31X1+35X2+32X3
S.T.
1) 3X1+5X2+2X3>90
2) 6X1+7X2+8X3<150
3) 5X1+3X2+3X3<120
OPTIMAL SOLUTION
Objective Function Value = 763.333 Use the following Management Scientist output to answer the questions. LINEAR PROGRAMMING PROBLEM MAX 31X1+35X2+32X3 S.T. 1) 3X1+5X2+2X3>90 2) 6X1+7X2+8X3<150 3) 5X1+3X2+3X3<120 OPTIMAL SOLUTION Objective Function Value = 763.333     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.Give the solution to the problem. b.Which constraints are binding? c.What would happen if the coefficient of x<sub>1</sub> increased by 3? d.What would happen if the right-hand side of constraint 1 increased by 10? Use the following Management Scientist output to answer the questions. LINEAR PROGRAMMING PROBLEM MAX 31X1+35X2+32X3 S.T. 1) 3X1+5X2+2X3>90 2) 6X1+7X2+8X3<150 3) 5X1+3X2+3X3<120 OPTIMAL SOLUTION Objective Function Value = 763.333     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.Give the solution to the problem. b.Which constraints are binding? c.What would happen if the coefficient of x<sub>1</sub> increased by 3? d.What would happen if the right-hand side of constraint 1 increased by 10? OBJECTIVE COEFFICIENT RANGES Use the following Management Scientist output to answer the questions. LINEAR PROGRAMMING PROBLEM MAX 31X1+35X2+32X3 S.T. 1) 3X1+5X2+2X3>90 2) 6X1+7X2+8X3<150 3) 5X1+3X2+3X3<120 OPTIMAL SOLUTION Objective Function Value = 763.333     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.Give the solution to the problem. b.Which constraints are binding? c.What would happen if the coefficient of x<sub>1</sub> increased by 3? d.What would happen if the right-hand side of constraint 1 increased by 10? RIGHT HAND SIDE RANGES Use the following Management Scientist output to answer the questions. LINEAR PROGRAMMING PROBLEM MAX 31X1+35X2+32X3 S.T. 1) 3X1+5X2+2X3>90 2) 6X1+7X2+8X3<150 3) 5X1+3X2+3X3<120 OPTIMAL SOLUTION Objective Function Value = 763.333     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.Give the solution to the problem. b.Which constraints are binding? c.What would happen if the coefficient of x<sub>1</sub> increased by 3? d.What would happen if the right-hand side of constraint 1 increased by 10?
a.Give the solution to the problem.
b.Which constraints are binding?
c.What would happen if the coefficient of x1 increased by 3?
d.What would happen if the right-hand side of constraint 1 increased by 10?
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42
Excel's Solver tool has been used in the spreadsheet below to solve a linear programming problem with a minimization objective function and all ≥ constraints. Excel's Solver tool has been used in the spreadsheet below to solve a linear programming problem with a minimization objective function and all ≥ constraints.   ​ a.Give the original linear programming problem. b.Give the complete optimal solution.
a.Give the original linear programming problem.
b.Give the complete optimal solution.
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43
​How can the interpretation of dual prices help provide an economic justification for new technology?
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44
Eight of the entries have been deleted from the LINDO output that follows. Use what you know about linear programming to find values for the blanks.
MIN 6 X1 + 7.5 X2 + 10 X3
SUBJECT TO
2) 25 X1 + 35 X2 + 30 X3 >= 2400
3) 2 X1 + 4 X2 + 8 X3 >= 400
END
LP OPTIMUM FOUND AT STEP 2
OBJECTIVE FUNCTION VALUE
1) 612.50000 Eight of the entries have been deleted from the LINDO output that follows. Use what you know about linear programming to find values for the blanks. MIN 6 X1 + 7.5 X2 + 10 X3 SUBJECT TO 2) 25 X1 + 35 X2 + 30 X3 >= 2400 3) 2 X1 + 4 X2 + 8 X3 >= 400 END LP OPTIMUM FOUND AT STEP 2 OBJECTIVE FUNCTION VALUE 1) 612.50000     NO. ITERATIONS= 2 RANGES IN WHICH THE BASIS IS UNCHANGED:    Eight of the entries have been deleted from the LINDO output that follows. Use what you know about linear programming to find values for the blanks. MIN 6 X1 + 7.5 X2 + 10 X3 SUBJECT TO 2) 25 X1 + 35 X2 + 30 X3 >= 2400 3) 2 X1 + 4 X2 + 8 X3 >= 400 END LP OPTIMUM FOUND AT STEP 2 OBJECTIVE FUNCTION VALUE 1) 612.50000     NO. ITERATIONS= 2 RANGES IN WHICH THE BASIS IS UNCHANGED:    NO. ITERATIONS= 2
RANGES IN WHICH THE BASIS IS UNCHANGED: Eight of the entries have been deleted from the LINDO output that follows. Use what you know about linear programming to find values for the blanks. MIN 6 X1 + 7.5 X2 + 10 X3 SUBJECT TO 2) 25 X1 + 35 X2 + 30 X3 >= 2400 3) 2 X1 + 4 X2 + 8 X3 >= 400 END LP OPTIMUM FOUND AT STEP 2 OBJECTIVE FUNCTION VALUE 1) 612.50000     NO. ITERATIONS= 2 RANGES IN WHICH THE BASIS IS UNCHANGED:    Eight of the entries have been deleted from the LINDO output that follows. Use what you know about linear programming to find values for the blanks. MIN 6 X1 + 7.5 X2 + 10 X3 SUBJECT TO 2) 25 X1 + 35 X2 + 30 X3 >= 2400 3) 2 X1 + 4 X2 + 8 X3 >= 400 END LP OPTIMUM FOUND AT STEP 2 OBJECTIVE FUNCTION VALUE 1) 612.50000     NO. ITERATIONS= 2 RANGES IN WHICH THE BASIS IS UNCHANGED:
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45
In a linear programming problem, the binding constraints for the optimal solution are
5X + 3Y ≤ 30
2X + 5Y ≤ 20
a.Fill in the blanks in the following sentence:As long as the slope of the objective function stays between _______ and _______, the current optimal solution point will remain optimal.
b.Which of these objective functions will lead to the same optimal solution?1) 2X + 1Y 2) 7X + 8Y 3) 80X + 60Y 4) 25X + 35Y
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46
​Describe each of the sections of output that come from The Management Scientist and how you would use each.
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47
LINDO output is given for the following linear programming problem.
MIN 12 X1 + 10 X2 + 9 X3
SUBJECT TO
2) 5 X1 + 8 X2 + 5 X3 >= 60
3) 8 X1 + 10 X2 + 5 X3 >= 80
END
LP OPTIMUM FOUND AT STEP 1
OBJECTIVE FUNCTION VALUE
1) 80.000000 LINDO output is given for the following linear programming problem. MIN 12 X1 + 10 X2 + 9 X3 SUBJECT TO 2) 5 X1 + 8 X2 + 5 X3 >= 60 3) 8 X1 + 10 X2 + 5 X3 >= 80 END LP OPTIMUM FOUND AT STEP 1 OBJECTIVE FUNCTION VALUE 1) 80.000000     NO. ITERATIONS= 1 RANGES IN WHICH THE BASIS IS UNCHANGED:     a.What is the solution to the problem? b.Which constraints are binding? c.Interpret the reduced cost for x<sub>1</sub>. d.Interpret the dual price for constraint 2. e.What would happen if the cost of x<sub>1</sub> dropped to 10 and the cost of x<sub>2</sub> increased to 12? LINDO output is given for the following linear programming problem. MIN 12 X1 + 10 X2 + 9 X3 SUBJECT TO 2) 5 X1 + 8 X2 + 5 X3 >= 60 3) 8 X1 + 10 X2 + 5 X3 >= 80 END LP OPTIMUM FOUND AT STEP 1 OBJECTIVE FUNCTION VALUE 1) 80.000000     NO. ITERATIONS= 1 RANGES IN WHICH THE BASIS IS UNCHANGED:     a.What is the solution to the problem? b.Which constraints are binding? c.Interpret the reduced cost for x<sub>1</sub>. d.Interpret the dual price for constraint 2. e.What would happen if the cost of x<sub>1</sub> dropped to 10 and the cost of x<sub>2</sub> increased to 12? NO. ITERATIONS= 1
RANGES IN WHICH THE BASIS IS UNCHANGED: LINDO output is given for the following linear programming problem. MIN 12 X1 + 10 X2 + 9 X3 SUBJECT TO 2) 5 X1 + 8 X2 + 5 X3 >= 60 3) 8 X1 + 10 X2 + 5 X3 >= 80 END LP OPTIMUM FOUND AT STEP 1 OBJECTIVE FUNCTION VALUE 1) 80.000000     NO. ITERATIONS= 1 RANGES IN WHICH THE BASIS IS UNCHANGED:     a.What is the solution to the problem? b.Which constraints are binding? c.Interpret the reduced cost for x<sub>1</sub>. d.Interpret the dual price for constraint 2. e.What would happen if the cost of x<sub>1</sub> dropped to 10 and the cost of x<sub>2</sub> increased to 12? LINDO output is given for the following linear programming problem. MIN 12 X1 + 10 X2 + 9 X3 SUBJECT TO 2) 5 X1 + 8 X2 + 5 X3 >= 60 3) 8 X1 + 10 X2 + 5 X3 >= 80 END LP OPTIMUM FOUND AT STEP 1 OBJECTIVE FUNCTION VALUE 1) 80.000000     NO. ITERATIONS= 1 RANGES IN WHICH THE BASIS IS UNCHANGED:     a.What is the solution to the problem? b.Which constraints are binding? c.Interpret the reduced cost for x<sub>1</sub>. d.Interpret the dual price for constraint 2. e.What would happen if the cost of x<sub>1</sub> dropped to 10 and the cost of x<sub>2</sub> increased to 12?
a.What is the solution to the problem?
b.Which constraints are binding?
c.Interpret the reduced cost for x1.
d.Interpret the dual price for constraint 2.
e.What would happen if the cost of x1 dropped to 10 and the cost of x2 increased to 12?
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48
Portions of a Management Scientist output are shown below. Use what you know about the solution of linear programs to fill in the ten blanks.
LINEAR PROGRAMMING PROBLEM
MAX 12X1+9X2+7X3
S.T.
1) 3X1+5X2+4X3<150
2) 2X1+1X2+1X3<64
3) 1X1+2X2+1X3<80
4) 2X1+4X2+3X3>116
OPTIMAL SOLUTION
Objective Function Value = 336.000 Portions of a Management Scientist output are shown below. Use what you know about the solution of linear programs to fill in the ten blanks. LINEAR PROGRAMMING PROBLEM MAX 12X1+9X2+7X3 S.T. 1) 3X1+5X2+4X3<150 2) 2X1+1X2+1X3<64 3) 1X1+2X2+1X3<80 4) 2X1+4X2+3X3>116 OPTIMAL SOLUTION Objective Function Value = 336.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES  Portions of a Management Scientist output are shown below. Use what you know about the solution of linear programs to fill in the ten blanks. LINEAR PROGRAMMING PROBLEM MAX 12X1+9X2+7X3 S.T. 1) 3X1+5X2+4X3<150 2) 2X1+1X2+1X3<64 3) 1X1+2X2+1X3<80 4) 2X1+4X2+3X3>116 OPTIMAL SOLUTION Objective Function Value = 336.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES  OBJECTIVE COEFFICIENT RANGES Portions of a Management Scientist output are shown below. Use what you know about the solution of linear programs to fill in the ten blanks. LINEAR PROGRAMMING PROBLEM MAX 12X1+9X2+7X3 S.T. 1) 3X1+5X2+4X3<150 2) 2X1+1X2+1X3<64 3) 1X1+2X2+1X3<80 4) 2X1+4X2+3X3>116 OPTIMAL SOLUTION Objective Function Value = 336.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES  RIGHT HAND SIDE RANGES Portions of a Management Scientist output are shown below. Use what you know about the solution of linear programs to fill in the ten blanks. LINEAR PROGRAMMING PROBLEM MAX 12X1+9X2+7X3 S.T. 1) 3X1+5X2+4X3<150 2) 2X1+1X2+1X3<64 3) 1X1+2X2+1X3<80 4) 2X1+4X2+3X3>116 OPTIMAL SOLUTION Objective Function Value = 336.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES
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49
​How would sensitivity analysis of a linear program be undertaken if one wishes to consider simultaneous changes for
both the right-hand-side values and objective function.
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50
Excel's Solver tool has been used in the spreadsheet below to solve a linear programming problem with a maximization objective function and all ≤ constraints. Excel's Solver tool has been used in the spreadsheet below to solve a linear programming problem with a maximization objective function and all ≤ constraints.   ​ a.Give the original linear programming problem. b.Give the complete optimal solution.
a.Give the original linear programming problem.
b.Give the complete optimal solution.
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51
​Explain the two interpretations of dual prices based on the accounting assumptions made in calculating the objective
function coefficients.
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52
The optimal solution of the linear programming problem is at the intersection of constraints 1 and 2.
Max
2x1 + x2
s.t.
4x1 + 1x2 ≤ 400
4x1 + 3x2 ≤ 600
1x1 + 2x2 ≤ 300
x1 , x2 ≥ 0

a.​Over what range can the coefficient of x1 vary before the current solution is no longer optimal?
b.​Over what range can the coefficient of x2 vary before the current solution is no longer optimal?
c.Compute the dual prices for the three constraints.
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53
The binding constraints for this problem are the first and second.
Min
x1 + 2x2
s.t.
x1 + x2 ≥ 300
2x1 + x2 ≥ 400
2x1 + 5x2 ≤ 750
x1 , x2 ≥ 0
a.Keeping c2 fixed at 2, over what range can c1 vary before there is a change in the optimal solution point?
b.Keeping c1 fixed at 1, over what range can c2 vary before there is a change in the optimal solution point?
c.If the objective function becomes Min 1.5x1 + 2x2, what will be the optimal values of x1, x2, and the objective function?
d.If the objective function becomes Min 7x1 + 6x2, what constraints will be binding?
e.Find the dual price for each constraint in the original problem.
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54
​How is sensitivity analysis used in linear programming? Given an example of what type of questions that can be
answered.
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55
Use the following Management Scientist output to answer the questions.
MIN 4X1+5X2+6X3
S.T.
1) X1+X2+X3<85
2) 3X1+4X2+2X3>280
3) 2X1+4X2+4X3>320
Objective Function Value = 400.000 Use the following Management Scientist output to answer the questions. MIN 4X1+5X2+6X3 S.T. 1) X1+X2+X3<85 2) 3X1+4X2+2X3>280 3) 2X1+4X2+4X3>320 Objective Function Value = 400.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution, and what is the value of the profit contribution? b.Which constraints are binding? c.What are the dual prices for each resource? Interpret. d.Compute and interpret the ranges of optimality. e.Compute and interpret the ranges of feasibility. Use the following Management Scientist output to answer the questions. MIN 4X1+5X2+6X3 S.T. 1) X1+X2+X3<85 2) 3X1+4X2+2X3>280 3) 2X1+4X2+4X3>320 Objective Function Value = 400.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution, and what is the value of the profit contribution? b.Which constraints are binding? c.What are the dual prices for each resource? Interpret. d.Compute and interpret the ranges of optimality. e.Compute and interpret the ranges of feasibility. OBJECTIVE COEFFICIENT RANGES Use the following Management Scientist output to answer the questions. MIN 4X1+5X2+6X3 S.T. 1) X1+X2+X3<85 2) 3X1+4X2+2X3>280 3) 2X1+4X2+4X3>320 Objective Function Value = 400.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution, and what is the value of the profit contribution? b.Which constraints are binding? c.What are the dual prices for each resource? Interpret. d.Compute and interpret the ranges of optimality. e.Compute and interpret the ranges of feasibility. RIGHT HAND SIDE RANGES Use the following Management Scientist output to answer the questions. MIN 4X1+5X2+6X3 S.T. 1) X1+X2+X3<85 2) 3X1+4X2+2X3>280 3) 2X1+4X2+4X3>320 Objective Function Value = 400.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution, and what is the value of the profit contribution? b.Which constraints are binding? c.What are the dual prices for each resource? Interpret. d.Compute and interpret the ranges of optimality. e.Compute and interpret the ranges of feasibility.
a.What is the optimal solution, and what is the value of the profit contribution?
b.Which constraints are binding?
c.What are the dual prices for each resource? Interpret.
d.Compute and interpret the ranges of optimality.
e.Compute and interpret the ranges of feasibility.
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56
​Explain the connection between reduced costs and the range of optimality, and between dual prices and the range of
feasibility.
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