Deck 8: Lp Sensitivity Analysis and Interpretation of Solution

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Question
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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Question
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.
Question
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.
Question
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.
Question
The reduced cost for a positive decision variable is 0.
Question
The amount by which an objective function coefficient would have to improve before it would be possible for the corresponding variable to assume a positive value in the optimal solution is called the

A)reduced cost.
B)relevant cost.
C)sunk cost.
D)dual price.
Question
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.
Question
The dual price measures,per unit increase in the right hand side,

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.
Question
Sensitivity analysis information in computer output is based on the assumption of

A)no coefficient change.
B)one coefficient change.
C)two coefficient change.
D)all coefficients change.
Question
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.
Question
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.
Question
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 the above is true.
Question
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.
Question
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.
Question
The amount that 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.
Question
Output from a computer package is precise and answers should never be rounded.
Question
Which of the following is not a question answered by sensitivity analysis?

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?
Question
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.
Question
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.
Question
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.
Question
If the optimal value of a decision variable is zero and its reduced cost is zero,this indicates that alternative optimal solutions exist.
Question
Any change to the objective function coefficient of a variable that is positive in the optimal solution will change the optimal solution.
Question
The 100% Rule does not imply that the optimal solution will necessarily change if the percentage exceeds 100%.
Question
A negative dual price indicates that increasing the right-hand side of the associated constraint would be detrimental to the objective.
Question
There is a dual price for every decision variable in a model.
Question
If the dual price for the right-hand side of a < constraint is zero,there is no upper limit on its range of feasibility.
Question
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.
Question
Decreasing the objective function coefficient of a variable to its lower limit will create a revised problem that is unbounded.
Question
Decision variables must be clearly defined before constraints can be written.
Question
For any constraint,either its slack/surplus value must be zero or its dual price must be zero.
Question
The 100 percent rule can be applied to changes in both objective function coefficients and right-hand sides at the same time.
Question
For a minimization problem,a positive dual price indicates the value of the objective function will increase.
Question
The amount of a sunk cost will vary depending on the values of the decision variables.
Question
Relevant costs should be reflected in the objective function,but sunk costs should not.
Question
The dual price associated with a constraint is the improvement in the value of the solution per unit decrease in the right-hand side of the constraint.
Question
The binding constraints for this problem are the first and second.
Min x1 + 2x2
s.t.x1 + x2 \ge 300
2x1 + x2 \ge 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.
Question
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.
Question
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 \le 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.
Question
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
Question
The dual price for a percentage constraint provides a direct answer to questions about the effect of increases or decreases in that percentage.
Question
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>
Question
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?
Question
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?
Question
Consider the following linear program:
MIN 6x1 + 9x2 ($ cost)
s.t.x1 + 2x2 < 8
10x1 + 7.5x2 > 30
x2 > 2
x1,x2 > 0
The Management Scientist provided the following solution output:
OPTIMAL SOLUTION
Objective Function Value = 27.000
Consider the following linear program: MIN 6x<sub>1</sub> + 9x<sub>2</sub> ($ cost) s.t.x<sub>1</sub> + 2x<sub>2</sub> < 8 10x<sub>1</sub> + 7.5x<sub>2</sub> > 30 x<sub>2</sub> > 2 x<sub>1</sub>,x<sub>2</sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 27.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the unit cost of x<sub>1</sub> is decreased to $4.Is the above solution still optimal? What is the value of the objective function when this unit cost is decreased to $4? c.How much can the unit cost of x<sub>2</sub> be decreased without concern for the optimal solution changing? d.If simultaneously the cost of x<sub>1</sub> was raised to $7.5 and the cost of x<sub>2</sub> was reduced to $6,would the current solution still remain optimal? e.If the right-hand side of constraint 3 is increased by 1,what will be the effect on the optimal solution?<div style=padding-top: 35px> Consider the following linear program: MIN 6x<sub>1</sub> + 9x<sub>2</sub> ($ cost) s.t.x<sub>1</sub> + 2x<sub>2</sub> < 8 10x<sub>1</sub> + 7.5x<sub>2</sub> > 30 x<sub>2</sub> > 2 x<sub>1</sub>,x<sub>2</sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 27.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the unit cost of x<sub>1</sub> is decreased to $4.Is the above solution still optimal? What is the value of the objective function when this unit cost is decreased to $4? c.How much can the unit cost of x<sub>2</sub> be decreased without concern for the optimal solution changing? d.If simultaneously the cost of x<sub>1</sub> was raised to $7.5 and the cost of x<sub>2</sub> was reduced to $6,would the current solution still remain optimal? e.If the right-hand side of constraint 3 is increased by 1,what will be the effect on the optimal solution?<div style=padding-top: 35px> OBJECTIVE COEFFICIENT RANGES
Consider the following linear program: MIN 6x<sub>1</sub> + 9x<sub>2</sub> ($ cost) s.t.x<sub>1</sub> + 2x<sub>2</sub> < 8 10x<sub>1</sub> + 7.5x<sub>2</sub> > 30 x<sub>2</sub> > 2 x<sub>1</sub>,x<sub>2</sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 27.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the unit cost of x<sub>1</sub> is decreased to $4.Is the above solution still optimal? What is the value of the objective function when this unit cost is decreased to $4? c.How much can the unit cost of x<sub>2</sub> be decreased without concern for the optimal solution changing? d.If simultaneously the cost of x<sub>1</sub> was raised to $7.5 and the cost of x<sub>2</sub> was reduced to $6,would the current solution still remain optimal? e.If the right-hand side of constraint 3 is increased by 1,what will be the effect on the optimal solution?<div style=padding-top: 35px> RIGHT HAND SIDE RANGES
Consider the following linear program: MIN 6x<sub>1</sub> + 9x<sub>2</sub> ($ cost) s.t.x<sub>1</sub> + 2x<sub>2</sub> < 8 10x<sub>1</sub> + 7.5x<sub>2</sub> > 30 x<sub>2</sub> > 2 x<sub>1</sub>,x<sub>2</sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 27.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the unit cost of x<sub>1</sub> is decreased to $4.Is the above solution still optimal? What is the value of the objective function when this unit cost is decreased to $4? c.How much can the unit cost of x<sub>2</sub> be decreased without concern for the optimal solution changing? d.If simultaneously the cost of x<sub>1</sub> was raised to $7.5 and the cost of x<sub>2</sub> was reduced to $6,would the current solution still remain optimal? e.If the right-hand side of constraint 3 is increased by 1,what will be the effect on the optimal solution?<div style=padding-top: 35px>
a.What is the optimal solution including the optimal value of the objective function?
b.Suppose the unit cost of x1 is decreased to $4.Is the above solution still optimal? What is the value of the objective function when this unit cost is decreased to $4?
c.How much can the unit cost of x2 be decreased without concern for the optimal solution changing?
d.If simultaneously the cost of x1 was raised to $7.5 and the cost of x2 was reduced to $6,would the current solution still remain optimal?
e.If the right-hand side of constraint 3 is increased by 1,what will be the effect on the optimal solution?
Question
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.
Question
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>
Question
Consider the following linear program:
MAX 3x1 + 4x2 ($ Profit)
s.t.x1 + 3x2 < 12
2x1 + x2 < 8
x1 < 3
x1,x2 > 0
The Management Scientist provided the following solution output:
OPTIMAL SOLUTION
Objective Function Value = 20.000
Consider the following linear program: MAX 3x<sub>1</sub> + 4x<sub>2</sub> ($ Profit) s.t.x<sub>1</sub> + 3x<sub>2</sub> < 12 2x<sub>1</sub> + x<sub>2</sub> < 8 x<sub>1</sub> < 3 x<sub>1</sub>,x<sub>2 </sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 20.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the profit on x<sub>1</sub> is increased to $7.Is the above solution still optimal? What is the value of the objective function when this unit profit is increased to $7? c.If the unit profit on x<sub>2</sub> was $10 instead of $4,would the optimal solution change? d.If simultaneously the profit on x<sub>1</sub> was raised to $5.5 and the profit on x<sub>2</sub> was reduced to $3,would the current solution still remain optimal?<div style=padding-top: 35px> Consider the following linear program: MAX 3x<sub>1</sub> + 4x<sub>2</sub> ($ Profit) s.t.x<sub>1</sub> + 3x<sub>2</sub> < 12 2x<sub>1</sub> + x<sub>2</sub> < 8 x<sub>1</sub> < 3 x<sub>1</sub>,x<sub>2 </sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 20.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the profit on x<sub>1</sub> is increased to $7.Is the above solution still optimal? What is the value of the objective function when this unit profit is increased to $7? c.If the unit profit on x<sub>2</sub> was $10 instead of $4,would the optimal solution change? d.If simultaneously the profit on x<sub>1</sub> was raised to $5.5 and the profit on x<sub>2</sub> was reduced to $3,would the current solution still remain optimal?<div style=padding-top: 35px> OBJECTIVE COEFFICIENT RANGES
Consider the following linear program: MAX 3x<sub>1</sub> + 4x<sub>2</sub> ($ Profit) s.t.x<sub>1</sub> + 3x<sub>2</sub> < 12 2x<sub>1</sub> + x<sub>2</sub> < 8 x<sub>1</sub> < 3 x<sub>1</sub>,x<sub>2 </sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 20.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the profit on x<sub>1</sub> is increased to $7.Is the above solution still optimal? What is the value of the objective function when this unit profit is increased to $7? c.If the unit profit on x<sub>2</sub> was $10 instead of $4,would the optimal solution change? d.If simultaneously the profit on x<sub>1</sub> was raised to $5.5 and the profit on x<sub>2</sub> was reduced to $3,would the current solution still remain optimal?<div style=padding-top: 35px> RIGHT HAND SIDE RANGES
Consider the following linear program: MAX 3x<sub>1</sub> + 4x<sub>2</sub> ($ Profit) s.t.x<sub>1</sub> + 3x<sub>2</sub> < 12 2x<sub>1</sub> + x<sub>2</sub> < 8 x<sub>1</sub> < 3 x<sub>1</sub>,x<sub>2 </sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 20.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the profit on x<sub>1</sub> is increased to $7.Is the above solution still optimal? What is the value of the objective function when this unit profit is increased to $7? c.If the unit profit on x<sub>2</sub> was $10 instead of $4,would the optimal solution change? d.If simultaneously the profit on x<sub>1</sub> was raised to $5.5 and the profit on x<sub>2</sub> was reduced to $3,would the current solution still remain optimal?<div style=padding-top: 35px>
a.What is the optimal solution including the optimal value of the objective function?
b.Suppose the profit on x1 is increased to $7.Is the above solution still optimal? What is the value of the objective function when this unit profit is increased to $7?
c.If the unit profit on x2 was $10 instead of $4,would the optimal solution change?
d.If simultaneously the profit on x1 was raised to $5.5 and the profit on x2 was reduced to $3,would the current solution still remain optimal?
Question
Given the following linear program:
MAX 5x1 + 7x2
s.t.x1 < 6
2x1 + 3x2 < 19
x1 + x2 < 8
x1,x2 > 0
The graphical solution to the problem is shown below.From the graph we see that the optimal solution occurs at x1 = 5,x2 = 3,and z = 46. Given the following linear program: MAX 5x<sub>1</sub> + 7x<sub>2</sub> s.t.x<sub>1</sub> < 6 2x<sub>1</sub> + 3x<sub>2</sub> < 19 x<sub>1</sub> + x<sub>2</sub> < 8 x<sub>1</sub>,x<sub>2</sub> > 0 The graphical solution to the problem is shown below.From the graph we see that the optimal solution occurs at x<sub>1</sub> = 5,x<sub>2</sub> = 3,and z = 46.   a.Calculate the range of optimality for each objective function coefficient. b.Calculate the dual price for each resource.<div style=padding-top: 35px>
a.Calculate the range of optimality for each objective function coefficient.
b.Calculate the dual price for each resource.
Question
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.
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Deck 8: Lp Sensitivity Analysis and Interpretation of Solution
1
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.
C
2
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.
A
3
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.
C
4
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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5
The reduced cost for a positive decision variable is 0.
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6
The amount by which an objective function coefficient would have to improve before it would be possible for the corresponding variable to assume a positive value in the optimal solution is called the

A)reduced cost.
B)relevant cost.
C)sunk cost.
D)dual price.
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7
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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8
The dual price measures,per unit increase in the right hand side,

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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9
Sensitivity analysis information in computer output is based on the assumption of

A)no coefficient change.
B)one coefficient change.
C)two coefficient change.
D)all coefficients change.
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10
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.
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11
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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12
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 the above is true.
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13
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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14
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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15
The amount that 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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16
Output from a computer package is precise and answers should never be rounded.
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17
Which of the following is not a question answered by sensitivity analysis?

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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18
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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19
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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20
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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21
If the optimal value of a decision variable is zero and its reduced cost is zero,this indicates that alternative optimal solutions exist.
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22
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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23
The 100% Rule does not imply that the optimal solution will necessarily change if the percentage exceeds 100%.
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24
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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25
There is a dual price for every decision variable in a model.
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26
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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27
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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28
Decreasing the objective function coefficient of a variable to its lower limit will create a revised problem that is unbounded.
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29
Decision variables must be clearly defined before constraints can be written.
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30
For any constraint,either its slack/surplus value must be zero or its dual price must be zero.
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31
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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32
For a minimization problem,a positive dual price indicates the value of the objective function will increase.
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33
The amount of a sunk cost will vary depending on the values of the decision variables.
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34
Relevant costs should be reflected in the objective function,but sunk costs should not.
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35
The dual price associated with a constraint is the improvement in the value of the solution per unit decrease in the right-hand side of the constraint.
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36
The binding constraints for this problem are the first and second.
Min x1 + 2x2
s.t.x1 + x2 \ge 300
2x1 + x2 \ge 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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37
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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38
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 \le 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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39
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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40
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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41
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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42
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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43
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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44
Consider the following linear program:
MIN 6x1 + 9x2 ($ cost)
s.t.x1 + 2x2 < 8
10x1 + 7.5x2 > 30
x2 > 2
x1,x2 > 0
The Management Scientist provided the following solution output:
OPTIMAL SOLUTION
Objective Function Value = 27.000
Consider the following linear program: MIN 6x<sub>1</sub> + 9x<sub>2</sub> ($ cost) s.t.x<sub>1</sub> + 2x<sub>2</sub> < 8 10x<sub>1</sub> + 7.5x<sub>2</sub> > 30 x<sub>2</sub> > 2 x<sub>1</sub>,x<sub>2</sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 27.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the unit cost of x<sub>1</sub> is decreased to $4.Is the above solution still optimal? What is the value of the objective function when this unit cost is decreased to $4? c.How much can the unit cost of x<sub>2</sub> be decreased without concern for the optimal solution changing? d.If simultaneously the cost of x<sub>1</sub> was raised to $7.5 and the cost of x<sub>2</sub> was reduced to $6,would the current solution still remain optimal? e.If the right-hand side of constraint 3 is increased by 1,what will be the effect on the optimal solution? Consider the following linear program: MIN 6x<sub>1</sub> + 9x<sub>2</sub> ($ cost) s.t.x<sub>1</sub> + 2x<sub>2</sub> < 8 10x<sub>1</sub> + 7.5x<sub>2</sub> > 30 x<sub>2</sub> > 2 x<sub>1</sub>,x<sub>2</sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 27.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the unit cost of x<sub>1</sub> is decreased to $4.Is the above solution still optimal? What is the value of the objective function when this unit cost is decreased to $4? c.How much can the unit cost of x<sub>2</sub> be decreased without concern for the optimal solution changing? d.If simultaneously the cost of x<sub>1</sub> was raised to $7.5 and the cost of x<sub>2</sub> was reduced to $6,would the current solution still remain optimal? e.If the right-hand side of constraint 3 is increased by 1,what will be the effect on the optimal solution? OBJECTIVE COEFFICIENT RANGES
Consider the following linear program: MIN 6x<sub>1</sub> + 9x<sub>2</sub> ($ cost) s.t.x<sub>1</sub> + 2x<sub>2</sub> < 8 10x<sub>1</sub> + 7.5x<sub>2</sub> > 30 x<sub>2</sub> > 2 x<sub>1</sub>,x<sub>2</sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 27.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the unit cost of x<sub>1</sub> is decreased to $4.Is the above solution still optimal? What is the value of the objective function when this unit cost is decreased to $4? c.How much can the unit cost of x<sub>2</sub> be decreased without concern for the optimal solution changing? d.If simultaneously the cost of x<sub>1</sub> was raised to $7.5 and the cost of x<sub>2</sub> was reduced to $6,would the current solution still remain optimal? e.If the right-hand side of constraint 3 is increased by 1,what will be the effect on the optimal solution? RIGHT HAND SIDE RANGES
Consider the following linear program: MIN 6x<sub>1</sub> + 9x<sub>2</sub> ($ cost) s.t.x<sub>1</sub> + 2x<sub>2</sub> < 8 10x<sub>1</sub> + 7.5x<sub>2</sub> > 30 x<sub>2</sub> > 2 x<sub>1</sub>,x<sub>2</sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 27.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the unit cost of x<sub>1</sub> is decreased to $4.Is the above solution still optimal? What is the value of the objective function when this unit cost is decreased to $4? c.How much can the unit cost of x<sub>2</sub> be decreased without concern for the optimal solution changing? d.If simultaneously the cost of x<sub>1</sub> was raised to $7.5 and the cost of x<sub>2</sub> was reduced to $6,would the current solution still remain optimal? e.If the right-hand side of constraint 3 is increased by 1,what will be the effect on the optimal solution?
a.What is the optimal solution including the optimal value of the objective function?
b.Suppose the unit cost of x1 is decreased to $4.Is the above solution still optimal? What is the value of the objective function when this unit cost is decreased to $4?
c.How much can the unit cost of x2 be decreased without concern for the optimal solution changing?
d.If simultaneously the cost of x1 was raised to $7.5 and the cost of x2 was reduced to $6,would the current solution still remain optimal?
e.If the right-hand side of constraint 3 is increased by 1,what will be the effect on the optimal solution?
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45
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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46
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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47
Consider the following linear program:
MAX 3x1 + 4x2 ($ Profit)
s.t.x1 + 3x2 < 12
2x1 + x2 < 8
x1 < 3
x1,x2 > 0
The Management Scientist provided the following solution output:
OPTIMAL SOLUTION
Objective Function Value = 20.000
Consider the following linear program: MAX 3x<sub>1</sub> + 4x<sub>2</sub> ($ Profit) s.t.x<sub>1</sub> + 3x<sub>2</sub> < 12 2x<sub>1</sub> + x<sub>2</sub> < 8 x<sub>1</sub> < 3 x<sub>1</sub>,x<sub>2 </sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 20.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the profit on x<sub>1</sub> is increased to $7.Is the above solution still optimal? What is the value of the objective function when this unit profit is increased to $7? c.If the unit profit on x<sub>2</sub> was $10 instead of $4,would the optimal solution change? d.If simultaneously the profit on x<sub>1</sub> was raised to $5.5 and the profit on x<sub>2</sub> was reduced to $3,would the current solution still remain optimal? Consider the following linear program: MAX 3x<sub>1</sub> + 4x<sub>2</sub> ($ Profit) s.t.x<sub>1</sub> + 3x<sub>2</sub> < 12 2x<sub>1</sub> + x<sub>2</sub> < 8 x<sub>1</sub> < 3 x<sub>1</sub>,x<sub>2 </sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 20.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the profit on x<sub>1</sub> is increased to $7.Is the above solution still optimal? What is the value of the objective function when this unit profit is increased to $7? c.If the unit profit on x<sub>2</sub> was $10 instead of $4,would the optimal solution change? d.If simultaneously the profit on x<sub>1</sub> was raised to $5.5 and the profit on x<sub>2</sub> was reduced to $3,would the current solution still remain optimal? OBJECTIVE COEFFICIENT RANGES
Consider the following linear program: MAX 3x<sub>1</sub> + 4x<sub>2</sub> ($ Profit) s.t.x<sub>1</sub> + 3x<sub>2</sub> < 12 2x<sub>1</sub> + x<sub>2</sub> < 8 x<sub>1</sub> < 3 x<sub>1</sub>,x<sub>2 </sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 20.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the profit on x<sub>1</sub> is increased to $7.Is the above solution still optimal? What is the value of the objective function when this unit profit is increased to $7? c.If the unit profit on x<sub>2</sub> was $10 instead of $4,would the optimal solution change? d.If simultaneously the profit on x<sub>1</sub> was raised to $5.5 and the profit on x<sub>2</sub> was reduced to $3,would the current solution still remain optimal? RIGHT HAND SIDE RANGES
Consider the following linear program: MAX 3x<sub>1</sub> + 4x<sub>2</sub> ($ Profit) s.t.x<sub>1</sub> + 3x<sub>2</sub> < 12 2x<sub>1</sub> + x<sub>2</sub> < 8 x<sub>1</sub> < 3 x<sub>1</sub>,x<sub>2 </sub> > 0 The Management Scientist provided the following solution output: OPTIMAL SOLUTION Objective Function Value = 20.000     OBJECTIVE COEFFICIENT RANGES   RIGHT HAND SIDE RANGES   a.What is the optimal solution including the optimal value of the objective function? b.Suppose the profit on x<sub>1</sub> is increased to $7.Is the above solution still optimal? What is the value of the objective function when this unit profit is increased to $7? c.If the unit profit on x<sub>2</sub> was $10 instead of $4,would the optimal solution change? d.If simultaneously the profit on x<sub>1</sub> was raised to $5.5 and the profit on x<sub>2</sub> was reduced to $3,would the current solution still remain optimal?
a.What is the optimal solution including the optimal value of the objective function?
b.Suppose the profit on x1 is increased to $7.Is the above solution still optimal? What is the value of the objective function when this unit profit is increased to $7?
c.If the unit profit on x2 was $10 instead of $4,would the optimal solution change?
d.If simultaneously the profit on x1 was raised to $5.5 and the profit on x2 was reduced to $3,would the current solution still remain optimal?
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48
Given the following linear program:
MAX 5x1 + 7x2
s.t.x1 < 6
2x1 + 3x2 < 19
x1 + x2 < 8
x1,x2 > 0
The graphical solution to the problem is shown below.From the graph we see that the optimal solution occurs at x1 = 5,x2 = 3,and z = 46. Given the following linear program: MAX 5x<sub>1</sub> + 7x<sub>2</sub> s.t.x<sub>1</sub> < 6 2x<sub>1</sub> + 3x<sub>2</sub> < 19 x<sub>1</sub> + x<sub>2</sub> < 8 x<sub>1</sub>,x<sub>2</sub> > 0 The graphical solution to the problem is shown below.From the graph we see that the optimal solution occurs at x<sub>1</sub> = 5,x<sub>2</sub> = 3,and z = 46.   a.Calculate the range of optimality for each objective function coefficient. b.Calculate the dual price for each resource.
a.Calculate the range of optimality for each objective function coefficient.
b.Calculate the dual price for each resource.
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49
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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