Deck 18: Simplex-Based Sensitivity Analysis and Duality
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Deck 18: Simplex-Based Sensitivity Analysis and Duality
1
The range of optimality is calculated by considering changes in the cj − zj value of the variable in question.
False
2
Dual prices and ranges for objective function coefficients and right-hand side values are found by considering
A) dual analysis.
B) optimality analysis.
C) ranging analysis.
D) sensitivity analysis.
A) dual analysis.
B) optimality analysis.
C) ranging analysis.
D) sensitivity analysis.
D
3
As long as the objective function coefficient remains within the range of optimality, the variable values will not change although the value of the objective function could.
True
4
The range of optimality is useful only for basic variables.
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5
The dual price for an equality constraint is the zj value for its artificial variable.
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6
If the dual price for b1 is 2.7, the range of feasibility is 20 ≤ b1 ≤ 50, and the original value of b1 was 30, which of the following is true?
A) There currently is no slack in the first constraint.
B) We would be willing to pay up to $2.70 per unit for up to 20 more units of resource 1.
C) If only 25 units of resource 1 were available, profit would drop by $13.50.
D) Each of the above is true.
A) There currently is no slack in the first constraint.
B) We would be willing to pay up to $2.70 per unit for up to 20 more units of resource 1.
C) If only 25 units of resource 1 were available, profit would drop by $13.50.
D) Each of the above is true.
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7
The dual price is the improvement in value of the optimal solution per unit increase in the value of the right-hand side associated with a linear programming problem.
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8
The dual variable represents
A) the marginal value of the constraint
B) the right-hand side value of the constraint
C) the artificial variable
D) the technical coefficient of the constraint
A) the marginal value of the constraint
B) the right-hand side value of the constraint
C) the artificial variable
D) the technical coefficient of the constraint
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9
If the simplex tableau is from a maximization converted from a minimization, the signs and directions of the inequalities that give the objective function ranges will need to be adjusted to apply to the original coefficients.
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10
The range of optimality for a basic variable defines the objective function coefficient values for which the variable will remain part of the current optimal basic feasible solution.
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11
A one-sided range of optimality
A) always occurs for non-basic variables.
B) always occurs for basic variables.
C) indicates changes in more than one coefficient.
D) indicates changes in a slack variable's coefficient.
A) always occurs for non-basic variables.
B) always occurs for basic variables.
C) indicates changes in more than one coefficient.
D) indicates changes in a slack variable's coefficient.
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12
For the basic feasible solution to remain optimal
A) all cj − zj values must remain ≤ 0.
B) no objective function coefficients are allowed to change.
C) the value of the objective function must not change.
D) each of the above is true.
A) all cj − zj values must remain ≤ 0.
B) no objective function coefficients are allowed to change.
C) the value of the objective function must not change.
D) each of the above is true.
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13
The range of feasibility indicates right-hand side values for which
A) the value of the objective function will not change.
B) the values of the decision variables will not change.
C) those variables which are in the basis will not change.
D) more simplex iterations must be performed.
A) the value of the objective function will not change.
B) the values of the decision variables will not change.
C) those variables which are in the basis will not change.
D) more simplex iterations must be performed.
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14
Given the simplex tableau for the optimal primal solution
A) the values of the dual variables can be found from the cj − zj values of the slack/surplus variable columns.
B) the values of the dual surplus variables can be found from the cj − zj values of the primal decision variable columns.
C) the value of the dual objective function will be the same as the objective function value for the primal problem.
D) each of the above is true.
A) the values of the dual variables can be found from the cj − zj values of the slack/surplus variable columns.
B) the values of the dual surplus variables can be found from the cj − zj values of the primal decision variable columns.
C) the value of the dual objective function will be the same as the objective function value for the primal problem.
D) each of the above is true.
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15
There is a dual price associated with each decision variable.
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16
The improvement in the value of the optimal solution per-unit increase in a constraint's right-hand side is
A) the slack value.
B) the dual price.
C) never negative.
D) the 100% rule.
A) the slack value.
B) the dual price.
C) never negative.
D) the 100% rule.
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17
A linear programming problem with the objective function 3x1 + 8x2 has the optimal solution x1 = 5, x2 = 6. If c2 decreases by 2 and the range of optimality shows 5 ≤ c2 ≤ 12, the value of Z
A) will decrease by 12.
B) will decrease by 2.
C) will not change.
D) cannot be determined from this information.
A) will decrease by 12.
B) will decrease by 2.
C) will not change.
D) cannot be determined from this information.
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18
The number of constraints to the dual of the following problem is: Max Z
= 3x1 + 2x2 + 6x3
S)t.
4x1 + 2x2 + 3x3 ≥ 100
2x1 + x2 − 2x3 ≤ 200
4x2 + x3 ≥ 200
A) 1.
B) 2.
C) 3.
D) 4.
= 3x1 + 2x2 + 6x3
S)t.
4x1 + 2x2 + 3x3 ≥ 100
2x1 + x2 − 2x3 ≤ 200
4x2 + x3 ≥ 200
A) 1.
B) 2.
C) 3.
D) 4.
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19
The ranges for which the right-hand side values are valid are the same as the ranges over which the dual prices are valid.
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20
The entries in the associated slack column of the final tableau indicate the changes in the values of the current basic variables corresponding to a one-unit increase in the right-hand side.
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21
Given the following linear programming problem
Max Z
0.5x1 + 6x2 + 5x3
s.t.
4x1 + 6x2 + 3x3 ≤ 24
1x1 + 1.5x2 + 3x3 ≤ 12
3x1 + x2 ≤ 12
and the final tableau is
a.Find the range of optimality for c1, c2, c3, c4, c5, and c6.
b.Find the range of feasibility for b1, b2, and b3.
Max Z
0.5x1 + 6x2 + 5x3
s.t.
4x1 + 6x2 + 3x3 ≤ 24
1x1 + 1.5x2 + 3x3 ≤ 12
3x1 + x2 ≤ 12
and the final tableau is

a.Find the range of optimality for c1, c2, c3, c4, c5, and c6.
b.Find the range of feasibility for b1, b2, and b3.
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22
Explain the simplex tableau location of the dual constraint for each type of constraint.
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23
When sensitivity calculations yield several potential upper bounds and several lower bounds, how is the range
determined?
determined?
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24
Given the following linear programming problem
Max
10x1 + 12x2
s.t.
1x1 + 2x2 ≥ 40
5x1 + 8x2 ≤ 160
1x1 + 1x2 ≤ 40
x1, x2 ≥ 0
the final tableau is
a.
Find the range of optimality for c1 and c2.
b.
Find the range of feasibility for b1, b2, and b3.
c.
Find the dual prices.
Max
10x1 + 12x2
s.t.
1x1 + 2x2 ≥ 40
5x1 + 8x2 ≤ 160
1x1 + 1x2 ≤ 40
x1, x2 ≥ 0
the final tableau is

a.
Find the range of optimality for c1 and c2.
b.
Find the range of feasibility for b1, b2, and b3.
c.
Find the dual prices.
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25
Explain why the zj value for a slack variable is the dual price.
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26
Write the dual to the following problem.
Min
12x1 + 15x2 + 20x3 + 18x4
s.t.
x1 + x2 + x3 + x4 ≥ 50
3x1 + 4x3 ≥ 60
2x2 + x3 − 2x4 ≤ 10
x1, x2, x3, x4 ≥ 0
Min
12x1 + 15x2 + 20x3 + 18x4
s.t.
x1 + x2 + x3 + x4 ≥ 50
3x1 + 4x3 ≥ 60
2x2 + x3 − 2x4 ≤ 10
x1, x2, x3, x4 ≥ 0
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27
The linear programming problem:
Max
6x1 + 2x2 + 3x3 + 4x4
s.t.
x1 + x2 + x3 + x4 ≤ 100
4x1 + x2 + x3 + x4 ≤ 160
3x1 + x2 + 2x3 + 3x4 ≤ 240
x1, x2, x 3, x4 ≥ 0
has the final tableau:
Fill in the table below to show what you would have found if you had used The Management Scientist to solve this problem.
LINEAR PROGRAMMING PROBLEM
MAX
6X1+2X2+3X3+4X4
S.T.
1) 1X1 + 1X2 + 1X3 + 1X4 < 100
2) 4X1 + 1X2 + 1X3 + 1X4 < 160
3) 3X1 + 1X2 + 2X3 + 3X4 < 240
OPTIMAL SOLUTION
Objective Function Value =
OBJECTIVE COEFFICIENT RANGES
RIGHT HAND SIDE RANGES
Max
6x1 + 2x2 + 3x3 + 4x4
s.t.
x1 + x2 + x3 + x4 ≤ 100
4x1 + x2 + x3 + x4 ≤ 160
3x1 + x2 + 2x3 + 3x4 ≤ 240
x1, x2, x 3, x4 ≥ 0
has the final tableau:

Fill in the table below to show what you would have found if you had used The Management Scientist to solve this problem.
LINEAR PROGRAMMING PROBLEM
MAX
6X1+2X2+3X3+4X4
S.T.
1) 1X1 + 1X2 + 1X3 + 1X4 < 100
2) 4X1 + 1X2 + 1X3 + 1X4 < 160
3) 3X1 + 1X2 + 2X3 + 3X4 < 240
OPTIMAL SOLUTION
Objective Function Value =


OBJECTIVE COEFFICIENT RANGES

RIGHT HAND SIDE RANGES

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28
For this optimal simplex tableau the original right-hand sides were 100 and 90. The problem was a maximization.
a.What would the new solution be if there had been 150 units available in the first constraint?
b.What would the new solution be if there had been 70 units available in the second constraint?

a.What would the new solution be if there had been 150 units available in the first constraint?
b.What would the new solution be if there had been 70 units available in the second constraint?
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29
Explain how to put an equality constraint into canonical form and how to calculate its dual variable value.
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30
For the following linear programming problem
Max Z
−2x1 + x2 − x3
s.t.
2x1 + x2 ≤ 7
1x1 + x2 + x3 ≥ 4
the final tableau is
a.Find the range of optimality for c1, c2 , c3. c4, c5 , and c6.
b.Find the range of feasibility for b1, and b2.
Max Z
−2x1 + x2 − x3
s.t.
2x1 + x2 ≤ 7
1x1 + x2 + x3 ≥ 4
the final tableau is

a.Find the range of optimality for c1, c2 , c3. c4, c5 , and c6.
b.Find the range of feasibility for b1, and b2.
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31
The primal problem is
Min
2x1 + 5x2 + 4x3
s.t.
x1 + 3x2 + 3x3 ≥ 30
3x1 + 7x2 + 5x3 ≥ 70
x1, x2, x3 ≥ 0
The final tableau for its dual problem is
Give the complete solution to the primal problem.
Min
2x1 + 5x2 + 4x3
s.t.
x1 + 3x2 + 3x3 ≥ 30
3x1 + 7x2 + 5x3 ≥ 70
x1, x2, x3 ≥ 0
The final tableau for its dual problem is

Give the complete solution to the primal problem.
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32
Creative Kitchen Tools manufactures a wide line of gourmet cooking tools from stainless steel. For the coming production period, there is demand of 1200 for 8 quart stock pots, and unlimited demand for 3 quart mixing bowls and large slotted spoons. In the following model, the three variables measure the number of pots, bowls, and spoons to make. The objective function measures profit. Constraint 1 measures steel, constraint 2 measures manufacturing time, constraint 3 measures finishing time, and constraint 4 measures the stock pot demand.
Max
5x1 + 3x2 + 6x3
s.t.
3x1 + 1x2 + 2x3 ≤ 15000
4x1 + 4x2 + 5x3 ≤ 18000
2x1 + 1x2 + 2x3 ≤ 10000
x1 ≤ 1200
x1, x2, x3 ≥ 0
The final tableau is:
a.
Calculate the range of optimality for c1, c2, and c3.
b.
Calculate the range of feasibility for b1, b2, b3, and b4.
c.
Suppose that the inventory records were incorrect and the company really has only 14000 units of steel. What effect will this have on your solution?
d.
Suppose that a cost increase will change the profit on the pots to $4.62. What effect will this have on your solution?
e.
Assume that the cost of time in production and finishing is relevant. Would you be willing to pay a $1.00 premium over the normal cost for 1000 more hours in the production department? What would this do to your solution?
Max
5x1 + 3x2 + 6x3
s.t.
3x1 + 1x2 + 2x3 ≤ 15000
4x1 + 4x2 + 5x3 ≤ 18000
2x1 + 1x2 + 2x3 ≤ 10000
x1 ≤ 1200
x1, x2, x3 ≥ 0
The final tableau is:

a.
Calculate the range of optimality for c1, c2, and c3.
b.
Calculate the range of feasibility for b1, b2, b3, and b4.
c.
Suppose that the inventory records were incorrect and the company really has only 14000 units of steel. What effect will this have on your solution?
d.
Suppose that a cost increase will change the profit on the pots to $4.62. What effect will this have on your solution?
e.
Assume that the cost of time in production and finishing is relevant. Would you be willing to pay a $1.00 premium over the normal cost for 1000 more hours in the production department? What would this do to your solution?
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33
For an objective function coefficient change outside the range of optimality, explain how to calculate the new optimal
solution. Must you return to the (revised) initial tableau?
solution. Must you return to the (revised) initial tableau?
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34
For this optimal simplex tableau, the right-hand sides for the two original ≥ constraints were 300 and 250. The problem was a minimization.
a.
What would the new solution be if the right-hand side value in the first constraint had been 325?
b.
What would the new solution be if the right-hand side value for the second constraint had been 220?

a.
What would the new solution be if the right-hand side value in the first constraint had been 325?
b.
What would the new solution be if the right-hand side value for the second constraint had been 220?
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35
Write the dual of the following problem
Min Z
= 2x1 − 3x2 + 5x3
s.t.
−3x1 + 2x2 + 5x3 ≥ 7
2x1 − x3 ≥ 5
4x 2 + 3x3 ≥ 8.
Min Z
= 2x1 − 3x2 + 5x3
s.t.
−3x1 + 2x2 + 5x3 ≥ 7
2x1 − x3 ≥ 5
4x 2 + 3x3 ≥ 8.
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