Virginia Tech BIT 3434 Test 1

3.0 Points

8/20/2015 Test 1

Test 1

Part 1 of 1 ­ 100.0 Points

Question 1 of 33 3.0 Points

In a decision­making problem, anchoring effects occur when

A. decision makers are tied too closely to previous decisions.

B. organizations refuse to consider new alternatives.

C. a seemingly trivial factor serves as a starting point for estimations.

D. a person in a position of authority exerts his or her opinion very forcefully.

Question 2 of 33 3.0 Points

In the following expression, which is (are) the dependent variable(s)? PROFIT = REVENUE – EXPENSES

A. Profit

B. Revenue

C. Expenses

D. Revenue and Expenses

Question 3 of 33 3.0 Points

In a decision­making framework presented in Chapter One, the term "poetic justice" refers to a situation when the

following occur:

A. Good decision quality and good outcome quality.

B. Good decision quality and bad outcome quality.

C. Bad decision quality and good outcome quality.

D. Bad decision quality and bad outcome quality.

Question 4 of 33

Framing effect refers to:

A. how a decision maker views the alternatives in a decision problem.

B. how difficult the decision is.

C. whether a software program can be used to obtain an optimal solution to a decision problem. D. how structured the decision problem is.

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Question 5 of 33

The constraint for resource 1 is

5 X1 + 4 X2 ≤ 200

If X1 = 20, what it the maximum value for X2?

A. 20

B. 25

C. 40 D. 50

Question 6 of 33

The constraints of an LP model define the

A. feasible region

B. practical region

C. maximal region D. opportunity region

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Question 7 of 33 3.0 Points

Level curves are used when solving LP models using the graphical method. To what part of the model do level

curves correspond?

A. constraints

B. boundaries

C. right hand sides

D. objective function

Question 8 of 33

When do alternate optimal solutions occur in LP models?

A. When a binding constraint is parallel to a level curve.

B. When a non­binding constraint is perpendicular to a level curve.

C. When a constraint is parallel to another constraint.

D. Alternate optimal solutions indicate an infeasible condition.

Question 9 of 33

A redundant constraint is one which

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A. plays no role in determining the feasible region of the problem.

B. is parallel to the level curve.

C. is added after the problem is already formulated.

D. can only increase the objective function value.

Question 10 of 33

If there is no way to simultaneously satisfy all the constraints in an LP model the problem is said to be

A. infeasible.

B. open ended.

C. multi­optimal. D. unbounded.

Question 11 of 33

A facility produces two products. The labor constraint (in hours) is formulated as: 350x1+300x2 ≤ 10,000. The

number 10,000 represents

A. a profit contribution of one unit of product 1.

B. one unit of product 1 uses 10,000 hours of labor.

C. there are 10,000 hours of labor available for use. D. the problem has no objective function.

Question 12 of 33

Suppose that a constraint 4x1+6x2 ≥ 1,800 is binding. Then, a constraint 2x1+3x2 ≥ 600 is

A. redundant.

B. binding.

C. limiting. D. infeasible.

Question 13 of 33

The following linear programming problem has been written to plan the production of two products. The company wants to maximize its profits.

X1 = number of product 1 produced in each batch

X2 = number of product 2 produced in each batch

MAX: 150 X1 + 250 X2

Subject to:

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2 X1 + 5 X2 ≤ 200

3 X1 + 7 X2 ≤ 175

X1, X2 ≥ 0

How many units of resource one (the first constraint) are used if the company produces 10 units of product 1 and 5 units of product 2?

A. 50

B. 15

C. 55

D. 45

Question 14 of 33

Solve the following LP problem graphically using level curves.

MAX: 5 X1 + 6 X2

Subject to:

3 X1 + 8 X2 ≤ 48

12 X1 + 11 X2 ≤ 132

2 X1 + 3 X2 ≤ 24

X1, X2 ≥ 0

A. X1 = 0, X2 = 6

B. X1 = 9.43, X2 = 1.71

C. X1 = 6.85, X2 = 3.43

D. X1 = 11, X2 = 0

Question 15 of 33

Consider the following LP model:

Max Z = 30X1 + 70X2

4X1 + 10X2 ≤ 80

14X1 + 8X2 ≤ 112

X1 + X2 ≤ 10

4X1 ­ 16X2 ≤ 16

X1, X2 ≥ 0

What is the slope of the fourth constraint?

A. ­ ¼

B. ¼

C. ­ 4

D. 4

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Question 16 of 33

For the model in problem 15, the optimal solution is at the intersection of constraints:

A. 1 and 2

B. 2 and 3

C. 1 and 3

D. 2 and 4 E. 3 and 4

Question 17 of 33

For the model in problem 15, the optimal solution values are

A. X1 = 5.33, X2 = 4.66

B. X1 = 0, X2 = 8

C. X1 = 3.33, X2 = 6.66

D. X1 = 5.33, X2 = 3.18

E. X1 = 7.5, X2 = .875

Question 18 of 33

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Using the refinery problem described below, which of the following is the best (most logical) objective function?

A refinery blends three petroleum components into two grades of gasoline – regular and premium. The maximum quantities available of each component and the cost per barrel are as follows:

Maximum barrels

Component available/day Cost per barrel

1 5000 $ 115

2 3400 $ 103

3 1800 $ 144

To ensure that each gasoline grade retains certain essential characteristics, the refinery has put limits on the amount of the components in each blend. The limits and the selling prices for the grades are as follows:

Selling price

Grade Component Specs per barrel

Not less than 40% of 1

Regular Not more than 20% of 2 $ 198

Not less than 30% of 3

Premium Not more than 20% of 1 $ 215

Not less than 50% of 3

The refinery wants to produce at least 3000 barrels of each grade of gasoline. Let xij be the barrels of component i in grade j.

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A. Min Z = 115(x11 + x12) + 103(x21 + x22) + 144(x31 + x32)

B. Min Z = ((115+103+144)/3)(x11 + x12 + x21 + x22 + x31 + x32)

C. Max Z = 83x11 + 100x12 + 95x21+112x22 + 54x31 + 71x32

D. Max Z = 198(x11 + x21 + x31) + 215(x12 + x22 + x32)

E. Max Z = x11 + x12 + x21 + x22 + x31 + x32

Question 19 of 33 3.0 Points

Using the refinery problem described below, for the blending recipe for regular gas, which of the following constraints is correct?

A refinery blends three petroleum components into two grades of gasoline – regular and premium. The maximum quantities available of each component and the cost per barrel are as follows:

Maximum barrels

Component available/day Cost per barrel

1 5000 $ 115

2 3400 $ 103

3 1800 $ 144

To ensure that each gasoline grade retains certain essential characteristics, the refinery has put limits on the amount of the components in each blend. The limits and the selling prices for the grades are as follows:

Selling price

Grade Component Specs per barrel

Not less than 40% of 1

Regular Not more than 20% of 2 $ 198

Not less than 30% of 3

Premium Not more than 20% of 1 $ 215

Not less than 50% of 3

The refinery wants to produce at least 3000 barrels of each grade of gasoline. Let xij be the barrels of component i in grade j.

A. x11 + x21 + x31 ≤ .3x31

B. .3x11 + .3x21 ­ .7x31 ≤ 0

C. x11 + x21 + x31 ≥ .3x31

D. .3(x11 + x21 + x31) ≥ x31 E. None of the above

Question 20 of 33 3.0 Points

Using the refinery problem described below, for the maximum component availability, which of the following constraints is correct?

A refinery blends three petroleum components into two grades of gasoline – regular and premium. The

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8/20/2015 Test 1

maximum quantities available of each component and the cost per barrel are as follows:

Maximum barrels

Component available/day Cost per barrel

1 5000 $ 115

2 3400 $ 103

3 1800 $ 144

To ensure that each gasoline grade retains certain essential characteristics, the refinery has put limits on the amount of the components in each blend. The limits and the selling prices for the grades are as follows:

Selling price

Grade Component Specs per barrel

Not less than 40% of 1

Regular Not more than 20% of 2 $ 198

Not less than 30% of 3

Premium Not more than 20% of 1 $ 215

Not less than 50% of 3

The refinery wants to produce at least 3000 barrels of each grade of gasoline. Let xij be the barrels of component i in grade j.

A. x12 + x22 ≤ 5000

B. x11 + x12 ≤ 3400

C. x31 + x32 ≤ 5000

D. x31 + x32 ≤ 1800 E. x11 + x21 ≤ 1800

Question 21 of 33 3.0 Points

Using the refinery problem described below, for the desired production level, which constraint is correct?

A refinery blends three petroleum components into two grades of gasoline – regular and premium. The maximum quantities available of each component and the cost per barrel are as follows:

Maximum barrels

Component available/day Cost per barrel

1 5000 $ 115

2 3400 $ 103

3 1800 $ 144

To ensure that each gasoline grade retains certain essential characteristics, the refinery has put limits on the amount of the components in each blend. The limits and the selling prices for the grades are as follows:

Selling price

Grade Component Specs per barrel

Not less than 40% of 1

Regular Not more than 20% of 2 $ 198

Not less than 30% of 3

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Premium Not more than 20% of 1 $ 215

Not less than 50% of 3

The refinery wants to produce at least 3000 barrels of each grade of gasoline. Let xij be the barrels of component i in grade j.

A. x11 + x21 + x31 ≥ 3000

B. x11 + x12 ≥ 3000

C. x11 + x21 + x31 ≤ 5000

D. x11 + x21 + x31 ≤ 3000 E. x11 + x21 + x31 ≤ 3400

Question 22 of 33

A major electronics producer produces three primary products. Their planning problem, solution, and sensitivity report are shown below. Which constraints are binding?

X1 = number of PCs to produce

X2 = number of Laptops to produce

X3 = number of PDAs to produce

Max Z = $37X1 + $35X2 + $45X3

2X1 + 3X2 + 2X3 <= 130 (assembly hours) 4X1 + 3X2 + X3 <= 150 (testing hours) 2X1 + 2X2 + 4X3 <= 90 (packing hours) X1 + X2 + X3 <= 50 (storage, sq. ft.)

X1, X2, X3 >= 0

PCs Laptops PDAs

Quantities 15 30 0

Profits 37 35 45 Z = 1605

LHS RHS

Const. 1 2 3 2 120 <= 130 (assembly hrs.)

Const. 2 4 3 1 150 <= 150 (testing hrs.)

Const. 3 2 2 4 90 <= 90 (packing hrs.)

Const. 4 1 1 1 45 <= 50 (storage, sq.ft.)

Microsoft Excel 12.0 Sensitivity Report

Worksheet: [sensitivity.xls]Sheet1

Adjustable Cells

Final Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease

$B$2 Quantities PCs 15 0 37 3 2

$C$2 Quantities Laptops 30 0 35 2 2.142857143

$D$2 Quantities PDAs 0 ­15 45 15 1E+30

Constraints

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Final Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease

$E$7 Const. 1 LHS 120 0 130 1E+30 10

$E$8 Const. 2 LHS 150 2 150 30 10

$E$9 Const. 3 LHS 90 14.5 90 3.333333333 15

$E$10 Const. 4 LHS 45 0 50 1E+30 5

A. 1 and 2

B. 1 and 3

C. 2 and 3

D. 1 and 4

E. 2 and 4

Question 23 of 33

A major electronics producer produces three primary products. Their planning problem, solution, and sensitivity report are shown below. Suppose you have been paying your “testers” $12 per hour. What is the most you would be willing to pay them to work overtime?

X1 = number of PCs to produce

X2 = number of Laptops to produce

X3 = number of PDAs to produce

Max Z = $37X1 + $35X2 + $45X3

2X1 + 3X2 + 2X3 <= 130 (assembly hours) 4X1 + 3X2 + X3 <= 150 (testing hours) 2X1 + 2X2 + 4X3 <= 90 (packing hours) X1 + X2 + X3 <= 50 (storage, sq. ft.)

X1, X2, X3 >= 0

PCs Laptops PDAs

Quantities 15 30 0

Profits 37 35 45 Z = 1605

LHS RHS

Const. 1 2 3 2 120 <= 130 (assembly hrs.)

Const. 2 4 3 1 150 <= 150 (testing hrs.)

Const. 3 2 2 4 90 <= 90 (packing hrs.)

Const. 4 1 1 1 45 <= 50 (storage, sq.ft.)

Microsoft Excel 12.0 Sensitivity Report

Worksheet: [sensitivity.xls]Sheet1

Adjustable Cells

Final Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease

$B$2 Quantities PCs 15 0 37 3 2

$C$2 Quantities Laptops 30 0 35 2 2.142857143

$D$2 Quantities PDAs 0 ­15 45 15 1E+30

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Constraints

Final Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease

$E$7 Const. 1 LHS 120 0 130 1E+30 10

$E$8 Const. 2 LHS 150 2 150 30 10

$E$9 Const. 3 LHS 90 14.5 90 3.333333333 15

$E$10 Const. 4 LHS 45 0 50 1E+30 5

A. $ 2

B. $12

C. $10

D. $14

E. I would not be willing to work them overtime

Question 24 of 33

A major electronics producer produces three primary products. Their planning problem, solution, and sensitivity report are shown below. Suppose we schedule 10 fewer hours of packing? Which of the following is the new profit?

X1 = number of PCs to produce

X2 = number of Laptops to produce

X3 = number of PDAs to produce

Max Z = $37X1 + $35X2 + $45X3

2X1 + 3X2 + 2X3 <= 130 (assembly hours) 4X1 + 3X2 + X3 <= 150 (testing hours) 2X1 + 2X2 + 4X3 <= 90 (packing hours) X1 + X2 + X3 <= 50 (storage, sq. ft.)

X1, X2, X3 >= 0

PCs Laptops PDAs

Quantities 15 30 0

Profits 37 35 45 Z = 1605

LHS RHS

Const. 1 2 3 2 120 <= 130 (assembly hrs.)

Const. 2 4 3 1 150 <= 150 (testing hrs.)

Const. 3 2 2 4 90 <= 90 (packing hrs.)

Const. 4 1 1 1 45 <= 50 (storage, sq.ft.)

Microsoft Excel 12.0 Sensitivity Report

Worksheet: [sensitivity.xls]Sheet1

Adjustable Cells

Final Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease

$B$2 Quantities PCs 15 0 37 3 2

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$C$2 Quantities Laptops 30 0 35 2 2.142857143

$D$2 Quantities PDAs 0 ­15 45 15 1E+30

Constraints

Final Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease

$E$7 Const. 1 LHS 120 0 130 1E+30 10

$E$8 Const. 2 LHS 150 2 150 30 10

$E$9 Const. 3 LHS 90 14.5 90 3.333333333 15

$E$10 Const. 4 LHS 45 0 50 1E+30 5

A. $ 1460

B. $ 1605

C. $ 1750

D. $ 1590

E. We cannot tell. The solution will change.

Question 25 of 33

A major electronics producer produces three primary products. Their planning problem, solution, and sensitivity report are shown below. What unit profit would have to be made from PDAs before you should consider producing them?

X1 = number of PCs to produce

X2 = number of Laptops to produce

X3 = number of PDAs to produce

Max Z = $37X1 + $35X2 + $45X3

2X1 + 3X2 + 2X3 <= 130 (assembly hours) 4X1 + 3X2 + X3 <= 150 (testing hours) 2X1 + 2X2 + 4X3 <= 90 (packing hours) X1 + X2 + X3 <= 50 (storage, sq. ft.)

X1, X2, X3 >= 0

PCs Laptops PDAs

Quantities 15 30 0

Profits 37 35 45 Z = 1605

LHS RHS

Const. 1 2 3 2 120 <= 130 (assembly hrs.)

Const. 2 4 3 1 150 <= 150 (testing hrs.)

Const. 3 2 2 4 90 <= 90 (packing hrs.)

Const. 4 1 1 1 45 <= 50 (storage, sq.ft.)

Microsoft Excel 12.0 Sensitivity Report

Worksheet: [sensitivity.xls]Sheet1

Adjustable Cells

Final Reduced Objective Allowable Allowable

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Cell Name Value Cost Coefficient Increase Decrease

$B$2 Quantities PCs 15 0 37 3 2

$C$2 Quantities Laptops 30 0 35 2 2.142857143

$D$2 Quantities PDAs 0 ­15 45 15 1E+30

Constraints

Final Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease

$E$7 Const. 1 LHS 120 0 130 1E+30 10

$E$8 Const. 2 LHS 150 2 150 30 10

$E$9 Const. 3 LHS 90 14.5 90 3.333333333 15

$E$10 Const. 4 LHS 45 0 50 1E+30 5

A. $ 46.00

B. $ 60.00

C. $ 59.50

D. $ 15.00

E. PDA’s will never be profitable at any profit level

Question 26 of 33

A major electronics producer produces three primary products. Their planning problem, solution, and sensitivity report are shown below. If the company changed the selling price of PCs such that the profit margin changed to $39, what would happen to the optimal values of the decision variables?

X1 = number of PCs to produce

X2 = number of Laptops to produce

X3 = number of PDAs to produce

Max Z = $37X1 + $35X2 + $45X3

2X1 + 3X2 + 2X3 <= 130 (assembly hours) 4X1 + 3X2 + X3 <= 150 (testing hours) 2X1 + 2X2 + 4X3 <= 90 (packing hours) X1 + X2 + X3 <= 50 (storage, sq. ft.)

X1, X2, X3 >= 0

PCs Laptops PDAs

Quantities 15 30 0

Profits 37 35 45 Z = 1605

LHS RHS

Const. 1 2 3 2 120 <= 130 (assembly hrs.)

Const. 2 4 3 1 150 <= 150 (testing hrs.)

Const. 3 2 2 4 90 <= 90 (packing hrs.)

Const. 4 1 1 1 45 <= 50 (storage, sq.ft.)

Microsoft Excel 12.0 Sensitivity Report

Worksheet: [sensitivity.xls]Sheet1

https://scholar.vt.edu/portal/tool/6abb01f8­47e4­4dc9­bcc6­b313faac5fa7/jsf/select/selectIndex 12/17

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Adjustable Cells

Final Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease

$B$2 Quantities PCs 15 0 37 3 2

$C$2 Quantities Laptops 30 0 35 2 2.142857143

$D$2 Quantities PDAs 0 ­15 45 15 1E+30

Constraints

Final Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease

$E$7 Const. 1 LHS 120 0 130 1E+30 10

$E$8 Const. 2 LHS 150 2 150 30 10

$E$9 Const. 3 LHS 90 14.5 90 3.333333333 15

$E$10 Const. 4 LHS 45 0 50 1E+30 5

A. They would stay the same

B. The variables for the other products would increase

C. The variables for the other products would decrease

D. We are unable to tell with the information given

Question 27 of 33

A major electronics producer produces three primary products. Their planning problem, solution, and sensitivity report are shown below. If the company changed the selling price of PCs such that the profit margin changed to $39, what would happen to the overall profit?

X1 = number of PCs to produce

X2 = number of Laptops to produce

X3 = number of PDAs to produce

Max Z = $37X1 + $35X2 + $45X3

2X1 + 3X2 + 2X3 <= 130 (assembly hours) 4X1 + 3X2 + X3 <= 150 (testing hours) 2X1 + 2X2 + 4X3 <= 90 (packing hours) X1 + X2 + X3 <= 50 (storage, sq. ft.)

X1, X2, X3 >= 0

PCs Laptops PDAs

Quantities 15 30 0

Profits 37 35 45 Z = 1605

LHS RHS

Const. 1 2 3 2 120 <= 130 (assembly hrs.)

Const. 2 4 3 1 150 <= 150 (testing hrs.)

Const. 3 2 2 4 90 <= 90 (packing hrs.)

Const. 4 1 1 1 45 <= 50 (storage, sq.ft.)

Microsoft Excel 12.0 Sensitivity Report

Worksheet: [sensitivity.xls]Sheet1

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8/20/2015 Test 1

Adjustable Cells

Final Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease

$B$2 Quantities PCs 15 0 37 3 2

$C$2 Quantities Laptops 30 0 35 2 2.142857143

$D$2 Quantities PDAs 0 ­15 45 15 1E+30

Constraints

Final Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease

$E$7 Const. 1 LHS 120 0 130 1E+30 10

$E$8 Const. 2 LHS 150 2 150 30 10

$E$9 Const. 3 LHS 90 14.5 90 3.333333333 15

$E$10 Const. 4 LHS 45 0 50 1E+30 5

A. It would go up by $ 2

B. It would increase to $ 1620

C. It would increase to $ 1635

D. It would not change

Question 28 of 33

A major electronics producer produces three primary products. Their planning problem, solution, and sensitivity report are shown below. How much would we be willing to pay for another assembly hour?

X1 = number of PCs to produce

X2 = number of Laptops to produce

X3 = number of PDAs to produce

Max Z = $37X1 + $35X2 + $45X3

2X1 + 3X2 + 2X3 <= 130 (assembly hours) 4X1 + 3X2 + X3 <= 150 (testing hours) 2X1 + 2X2 + 4X3 <= 90 (packing hours) X1 + X2 + X3 <= 50 (storage, sq. ft.)

X1, X2, X3 >= 0

PCs Laptops PDAs

Quantities 15 30 0

Profits 37 35 45 Z = 1605

LHS RHS

Const. 1 2 3 2 120 <= 130 (assembly hrs.)

Const. 2 4 3 1 150 <= 150 (testing hrs.)

Const. 3 2 2 4 90 <= 90 (packing hrs.)

Const. 4 1 1 1 45 <= 50 (storage, sq.ft.)

Microsoft Excel 12.0 Sensitivity Report

Worksheet: [sensitivity.xls]Sheet1

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3.0 Points

8/20/2015 Test 1

Adjustable Cells

Final Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease

$B$2 Quantities PCs 15 0 37 3 2

$C$2 Quantities Laptops 30 0 35 2 2.142857143

$D$2 Quantities PDAs 0 ­15 45 15 1E+30

Constraints

Final Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease

$E$7 Const. 1 LHS 120 0 130 1E+30 10

$E$8 Const. 2 LHS 150 2 150 30 10

$E$9 Const. 3 LHS 90 14.5 90 3.333333333 15

$E$10 Const. 4 LHS 45 0 50 1E+30 5

A. Only what we have been paying previously, because the shadow price is 0

B. We don’t know because the allowable increase is 1E30

C. Up to $10 per unit

D. Nothing

Question 29 of 33

A major electronics producer produces three primary products. Their planning problem, solution, and sensitivity report are shown below. If the square feet of storage changed to 43, would this affect the solution?

X1 = number of PCs to produce

X2 = number of Laptops to produce

X3 = number of PDAs to produce

Max Z = $37X1 + $35X2 + $45X3

2X1 + 3X2 + 2X3 <= 130 (assembly hours) 4X1 + 3X2 + X3 <= 150 (testing hours) 2X1 + 2X2 + 4X3 <= 90 (packing hours) X1 + X2 + X3 <= 50 (storage, sq. ft.)

X1, X2, X3 >= 0

PCs Laptops PDAs

Quantities 15 30 0

Profits 37 35 45 Z = 1605

LHS RHS

Const. 1 2 3 2 120 <= 130 (assembly hrs.)

Const. 2 4 3 1 150 <= 150 (testing hrs.)

Const. 3 2 2 4 90 <= 90 (packing hrs.)

Const. 4 1 1 1 45 <= 50 (storage, sq.ft.)

Microsoft Excel 12.0 Sensitivity Report

Worksheet: [sensitivity.xls]Sheet1

https://scholar.vt.edu/portal/tool/6abb01f8­47e4­4dc9­bcc6­b313faac5fa7/jsf/select/selectIndex 15/17

3.0 Points

3.0 Points

8/20/2015 Test 1

Adjustable Cells

Final Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease

$B$2 Quantities PCs 15 0 37 3 2

$C$2 Quantities Laptops 30 0 35 2 2.142857143

$D$2 Quantities PDAs 0 ­15 45 15 1E+30

Constraints

Final Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease

$E$7 Const. 1 LHS 120 0 130 1E+30 10

$E$8 Const. 2 LHS 150 2 150 30 10

$E$9 Const. 3 LHS 90 14.5 90 3.333333333 15

$E$10 Const. 4 LHS 45 0 50 1E+30 5

A. No

B. Yes

C. Only the profit

D. Not enough information to tell

Question 30 of 33

A binding greater than or equal to (≥) constraint in a minimization problem means that

A. the variable is up against an upper limit.

B. the minimum requirement for the constraint has just been met.

C. another constraint is limiting the solution.

D. the shadow price for the constraint will be positive.

Question 31 of 33

If the allowable increase for a constraint is 100 and we add 110 units of the resource what happens to the objective function value?

A. increase of 100

B. increase of 110

C. decrease of 100

D. increases but by unknown amount

Question 32 of 33 3.0 Points

A change in the right hand side of a constraint changes

A. the slope of the objective function

B. objective function coefficients

https://scholar.vt.edu/portal/tool/6abb01f8­47e4­4dc9­bcc6­b313faac5fa7/jsf/select/selectIndex 16/17

3.0 Points

8/20/2015 Test 1

C. other right hand sides

D. the feasible region

Question 33 of 33

The solution to an LP problem is degenerate if zero.

A. the right hand sides of any of the constraints have an allowable increase or allowable decrease of zero.

B. the shadow prices of any of the constraints have an allowable increase or allowable decrease of infinity.

C. the objective coefficients of any of the variables have an allowable increase or allowable decrease of

D. the shadow prices of any of the constraints have an allowable increase or allowable decrease of zero.

https://scholar.vt.edu/portal/tool/6abb01f8­47e4­4dc9­bcc6­b313faac5fa7/jsf/select/selectIndex 17/17