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1 Review Problem #1 INTERNATIONAL SHIPPING. The Takahashi Transport Company (TTC) leases excess...

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1 Review Problem #1 INTERNATIONAL SHIPPING. The Takahashi Transport Company (TTC) leases excess space on commercial vessels to the United States at a reduced rate of $10 per square foot. The only condition is that goods must be packaged in standard 30-inch-high crates. TTC ships items in two standard 30-inch-high crates, an eight-square-foot crate (two feet by four feet) and a four-square-foot (two feet by two feet) specially insulated crate. It charges customers $160 to ship an eight-square-foot crate and $100 to ship the insulated four-square-foot crate. Allowing for the cost of $10 per square foot, TTC makes $80 per standard eight-foot crate and (160 – 10*8) $60 on the four-foot crate (100 – 10*4)
Transcript

1

Review Problem #1

• INTERNATIONAL SHIPPING. The Takahashi Transport Company (TTC) leases excess space on commercial vessels to the United States at a reduced rate of $10 per square foot. The only condition is that

goods must be packaged in standard 30-inch-high crates. • TTC ships items in two standard 30-inch-high crates,

– an eight-square-foot crate (two feet by four feet) and

– a four-square-foot (two feet by two feet) specially insulated crate.

• It charges customers – $160 to ship an eight-square-foot crate and

– $100 to ship the insulated four-square-foot crate.

• Allowing for the cost of $10 per square foot, TTC makes – $80 per standard eight-foot crate and (160 – 10*8)

– $60 on the four-foot crate (100 – 10*4)

2

• TTC stores the crates until space becomes available on a cargo ship, at which time TTC receives payment from its customers. TTC has been able to lease – 1200 square feet of cargo space on the Formosa Frigate cargo ship,

which leaves for the United States in two days.

• As of this date, TTC has – 140 eight-square-foot crates and

– 100 insulated four-square-foot crates awaiting shipment to the United States.

• It has – 48 hours to finish loading the crates, and

• it estimates the average loading time to be – 12 minutes (.2 hour) per eight-square-foot crate and

– 24 minutes (.4 hour) per four-square-foot crate (owing to the special handling of the insulated crates).

3

• Formulate and solve a linear program for TTC to optimize its profit on the upcoming sailing of the Formosa Frigate.

8-SQFT 4-SQFT

Profit 80 60

# of 8 FT 1 <= 140

# of 4 FT 1 <= 100

Load Time 0.2 0.4 <= 48

Space 8 4 <= 1200

4

• What are the optimal values of the slack on each constraint in the optimal solution? Express this result in words.

Constraints

Cell Name Cell Value Formula Status Slack

$D$4 # of 8 FT 120 $D$4<=$F$4 Not Binding 20

$D$5 # of 4 FT 60 $D$5<=$F$5 Not Binding 40

$D$6 Load Time 48 $D$6<=$F$6 Binding 0

$D$7 Space 1200 $D$7<=$F$7 Binding 0

5

Adjustable Cells

    Final Reduced Objective Allowable Allowable

Name Value Cost Coefficient Increase Decrease

8-SQFT 120 0 80 40 50

4-SQFT 60 0 60 100 20

Review Problem # 1 - continued

a. Determine the range of optimality for each revenue coefficient.

The ranges of optimality are:80+40, 80-5060+100, 60-20

6

Constraints

    Final Shadow Constraint Allowable Allowable

Name Value Price R.H. Side Increase Decrease

# of 8 FT 120 0 140 1E+30 20

# of 4 FT 60 0 100 1E+30 40

Load Time 48 66.66666667 48 12 12

Space 1200 8.333333333 1200 120 480

Review Problem # 1 - continued

b. Determine the range of feasibility for the number of square feet available, the loading time, the number of standard containers available, and the number of insulated containers available.

The ranges of feasibility are:140+infinity, 140-20100+infinity, 100-4048+12, 48-121200+120, 1200-480

7

c. Determine the shadow price for each resource for which a range of feasibility was calculated in part (b). Do you think that any of these should be treated as a sunk cost? Given your answer, explain the meaning of each shadow price.

• As long as extra space could be leased for 10 + 8.33 = $18.33 it should be leased. Explanation: The leasing cost per sq-ft was included in determining the profit per sq-ft (for an 8-sq ft crate it is 160/8-10). Thus, TCC should be willing to pay up to $8.33 above $10 per sq ft, but not more).

• Loading time is a sunk cost. Extra loading time will add $66.67 to the profit per hour added

8

e. Suppose that at the last second, the Formosa Frigate decided to raise its charge per square foot from $10 to $12. Would the optimal solution change?

Two coefficients in the objective function are changing.Percent change: For 8-square foot crate=((80-64)/(80-30))=.32

For 4-square foot crate=((60-52)/(60-40))=.40Total=.72 < 1.00

The optimal solution will not change.

Cover only if the 100% rule was discussed in class

9

Review Problem #2

BAKERY. Mary Custard's is a pie shop that specializes in custard and fruit pies. It makes delicious pies and sells them at reasonable prices so that it can sell all the pies it makes in a day. Every dozen custard pies nets Mary Custard's $ 15 and requires 12 pounds of flour, 50 eggs, and 5 pounds of sugar (and no fruit mixture). Every dozen fruit pies nets a $25 profit and uses 10 pounds of flour, 40 eggs, 10 pounds of sugar, and 15 pounds of fruit mixture. On a given day, the bakers at Mary Custard's had 150 pounds of flour, 500 eggs, 90 pounds of sugar, and 120 pounds of fruit mixture.

10

Problem 2 - solution

• Formulate a linear program that will give the optimal

production schedule of pies for the day.

X1 = the number of dozen custard pies baked

X2 = the number of dozen fruit pies baked

MAX 15X1+25X2

S.T. 12X1 + 10X2 <= 150 (Flour)

50X1 + 40X2 <= 500 (Eggs)

5X1 + 10X2 <= 90 (Sugar)

15X2 <= 120 (Fruit mixture)

XI, X2 >= 0

11

Adjustable Cells

  Final Reduced Objective Allowable Allowable

Value Cost Coefficient Increase Decrease

x1 4.67 0 15 0.5 7

x2 6.67 0 25 14 0.4

• Solve for the optimal production schedule

Bake 56 (4 2/3 dozen) custard pies and 80 (6 2/3 dozen) fruit pies;Profit = $236.67

Problem 2 - solution

12

Adjustable Cells

  Final Reduced Objective Allowable Allowable

Value Cost Coefficient Increase Decrease

x1 4.67 0 12 16.25 2.5

x2 6.67 0 10 5 13

d. If Mary Custard's raised the price (and hence the profit) on all pies by $0.25 ($3.00 per dozen), would the optimal production schedule for the day change? Would the profit change?Percent changes: Custard pies 3/16.25 = 18.46% Fruit pies 3/5 = 60.00%. Total = 78.46%

No change in the quantities produced; change in the profit.

c. If Mary Custard's could double its profit on custard pies, should more custard pies be produced? Explain.$30 is within the range of optimality - no change.

Cover only if the 100% rule was discussed in class

13

e. Suppose Mary Custard's found that 10% of its fruit mixture had been stored in containers that were not air-tight. For quality and health reasons, it decided that it would be unwise to use any of this portion of the fruit mixture. How would this affect the optimal production schedule? Explain.

12 pounds of fruit mixture are not available (10% of 120); yet there is a slack of 20 pounds and thus the optimal solution will not be affected.

    Final Shadow Constraint Allowable Allowable

  Name Value Price R.H. Side Increase Decrease

  Flour 122.67 0 150 1E+30 27.333

  Eggs 500 0.083 500 117.143 80

  Sugar 90 2.17 90 8 40

  Fruit 100 0 120 1E+30 20

14

f. Mary Custard's currently pays $2.50 for a five-pound bag of sugar from its bakery supply vendor. (The $0.50 per pound price of sugar is included in the unit profits given earlier.) Its vendor has already made its deliveries for the day. If Mary Custard's wishes to purchase additional sugar, it must buy it from Donatelli's Market, a small, independent grocery store that sells sugar in one-pound boxes for $2.25 a box. Should Mary Custard's purchase any boxes of sugar from Donatelli's Market? ExplainThe shadow price for sugar is $2.17. Since cost of sugar is included, extra sugar is worth $2.17 + $0.50 = $2.67. Since this is greater than $2.25, Mary Custard's should purchase it.

    Final Shadow Constraint Allowable Allowable

  Name Value Price R.H. Side Increase Decrease

  Flour 122.67 0 150 1E+30 27.333

  Eggs 500 0.083 500 117.143 80

  Sugar 90 2.17 90 8 40

  Fruit 100 0 120 1E+30 20

15

Review Problem # 3

• This problem focuses on modeling a blending problem, multiple changes and the application of the 100% rule.

• The Party Nut Company has on hand 550 pounds of peanuts, 150 pounds of cashews, 90 pounds of Brazil nuts. It packages and sells four varieties of mixed nuts in standard 8-ounce (half pound) cans. The mix requirements and the unit profit per can are shown in the table below. What mix of products (how many cans of each product) should be produced and sold?

16

Data

Mix Contents Profit per can

1 Peanuts only $0.26

2 No more than 50% peanutsAt least 15% cashew

$0.40

3 Cashew only $0.51

4 At least 30% cashewAt least 20% brazil nuts

$0.52

17

Solution

• Definitions:• M1, M2, M3, M4 = the number of cans produced of

mix 1, 2, 3, 4 respectively.

• Pi, Ci, Bi = the amount (in pounds) of peanuts, cashew, brazil use in mix ‘i’.

18

The model

– Max .26M1+.40M2+.51M3+.52M4ST. P1 = .5M1

P2 (50%)(.5M2)

C2 (15%)(.5M2)C3 = .5M3C4 (30%)(.5M4)B4 (20%)(.5M4)

P1 + P2 550

C2 + C3 + C4 150

B4 90

Available resources

Required quantities

19

WINQSB solution and sensitivity analysis

• Assume the profit drops by 10 cents per can for mix 1, increases by 10 cents per can for mix 2, and by 20 cents per can for mix 3. Would the optimal production plan change?

• (.16-.26)/(0-.26)+ (.50-.40)/(M-.40)+(.71-.51)/(2.67-.51) = .4772 < 1. The optimal solution will not change.

M=infinity

20

• Assume the available amount of all the materials used decreases by 10% each.Would the optimal solution change. Would the total profit change? By how much?

• Observe the last three constraints, and check the 100% rule: –55/(0-550)+ (-15)/(0-150)+(-9)/(0-90) = .3 < 1. The shadow prices will remain the same, but the solution will change, because the changes are made in binding constraints (no slack).

• The new profit = old profit + shadow price(change in the constraint’s RHS)] = 1086 + (52)(-55)+5.33(-15)+(0)(-9) = 977.45

WINQSB solution and sensitivity analysis

21

Modeling and Sensitivity Analysis – Example 1

APPAREL INDUSTRY. Exclaim! Jeans is setting up a production schedule for the coming week. Exclaim! Can make four jean products: men’s and women’s jackets and pants. Although it can make different sizes of each, the variation in material usage and labor between sizes is negligible. Each jacket and pair of pants goes through cutting and stitching operations before being boxed. The following table gives the profit, denim, cutting time, stitching time, and boxing time required per 100 items, as well as the total resource availabilities during the week.

22

Item Profit

($)

Denim (yd.)

Cutting

(hr.)

Stitching

(hr.)

Boxing

(hr.)

Men’s Jacket

Women’s Jacket

Men’s Pants

Women’s Pants

$2,000

2,800

1200

1500

150

125

200

150

3

4

2

2

4

3

2

2

.75

.75

.50

.50

Available 2500 36 36 8

APPAREL INDUSTRY

23

• Develop and solve a linear programming model. For Exclaim! Jeans which will maximize its profit for the week.

Decision variables and objective functionMax 2000MJacket+2800WJacket+1200MPants+1500WPants

APPAREL INDUSTRY - Solution

ConstraintsMaterial constraint150MJacket+125WJacket+200MPants+150WPants 2500Cutting time constraint 3MJacket+ 4WJacket+ 2MPants+ 2WPants 36Stitching time constraint 4MJacket+ 3WJacket+ 2MPants+ 2WPants 36

Boxing time constraint .75MJacket+ .75WJacket+ .50MPants+ .50WPants 7.5

24

APPAREL INDUSTRY - Solution

• Develop and solve a linear programming model. For Exclaim! Jeans which will maximize its profit for the week.

MenJackets WomenJackets MenPants WomenPants

TotalProfit 2000 2800 1200 1500 0Denim-Yds 150 125 200 150 0 <= 2500Cutting-Hrs 3 4 2 2 0 <= 36Stitching-Hrs 4 3 2 2 0 <= 36Boxing-Hrs 0.75 0.75 0.5 0.5 0 <= 7.5

MenJackets WomenJackets MenPants WomenPants

0 6 0 6Total

Profit 2000 2800 1200 1500 25800Denim-Yds 150 125 200 150 1650 <= 2500Cutting-Hrs 3 4 2 2 36 <= 36Stitching-Hrs 4 3 2 2 30 <= 36Boxing-Hrs 0.75 0.75 0.5 0.5 7.5 <= 7.5

25

• How much should the profit for Men’s Jacket increase before it becomes part of the production plan?

Adjustable CellsFinal Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease$B$2 MenJackets 0 -250 2000 250 1E+30$C$2 WomenJackets 6 0 2800 200 550$D$2 MenPants 0 -300 1200 300 1E+30$E$2 WomenPants 6 0 1500 366.6666667 100

ConstraintsFinal Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease$F$5 Denim-Yds Total 1650 0 2500 1E+30 850$F$6 Cutting-Hrs Total 36 550 36 4 6$F$7 Stitching-Hrs Total 30 0 36 1E+30 6$F$8 Boxing-Hrs Total 7.5 800 7.5 1.214285714 0.75

APPAREL INDUSTRY - Solution

+

26

• Assume the unit profit of women’s pants increases by 20%. If all pants produced can still be sold should Exclaim change its production plan in order to sell more women’s pants? Explain.

Adjustable CellsFinal Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease$B$2 MenJackets 0 -250 2000 250 1E+30$C$2 WomenJackets 6 0 2800 200 550$D$2 MenPants 0 -300 1200 300 1E+30$E$2 WomenPants 6 0 1500 366.6666667 100

ConstraintsFinal Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease$F$5 Denim-Yds Total 1650 0 2500 1E+30 850$F$6 Cutting-Hrs Total 36 550 36 4 6$F$7 Stitching-Hrs Total 30 0 36 1E+30 6$F$8 Boxing-Hrs Total 7.5 800 7.5 1.214285714 0.75

APPAREL INDUSTRY - Solution

No.20%(1500)=300 < 366.67

27

• Management is considering allocating one hour of overtime in one department. Where should this hour be allocated? How much should be paid per hour? Adjustable Cells

Final Reduced Objective Allowable AllowableCell Name Value Cost Coefficient Increase Decrease

$B$2 MenJackets 0 -250 2000 250 1E+30$C$2 WomenJackets 6 0 2800 200 550$D$2 MenPants 0 -300 1200 300 1E+30$E$2 WomenPants 6 0 1500 366.6666667 100

ConstraintsFinal Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease$F$5 Denim-Yds Total 1650 0 2500 1E+30 850$F$6 Cutting-Hrs Total 36 550 36 4 6$F$7 Stitching-Hrs Total 30 0 36 1E+30 6$F$8 Boxing-Hrs Total 7.5 800 7.5 1.214285714 0.75

APPAREL INDUSTRY - Solution

+1+1

+1

Both Cutting and Boxing are candidates at the shadow price contribution shown. Prefer the boxing department because 1 hour of overtime contributes $800 to theprofit (more than $550 in the cutting department).

28

• Suppose that, in addition to the existing restrictions,management wishes to produce at least 300 of each item. Add these constraints to your linear program and re-solve the problem. What is the result? To what do you attribute this result?

MenJackets WomenJackets MenPants WomenPants

TotalProfit 2000 2800 1200 1500 0Denim-Yds 150 125 200 150 0 <= 2500Cutting-Hrs 3 4 2 2 0 <= 36Stitching-Hrs 4 3 2 2 0 <= 36Boxing-Hrs 0.75 0.75 0.5 0.5 0 <= 7.5M-Jacket>3 1 0 >= 5W-Jacket>3 1 0 >= 5M-Pants>3 1 0 >= 5W-Pants>3 1 0 >= 5

MenJackets WomenJackets MenPants WomenPants

3 3 3 3Total

Profit 2000 2800 1200 1500 22500Denim-Yds 150 125 200 150 1875 <= 2500Cutting-Hrs 3 4 2 2 33 <= 36Stitching-Hrs 4 3 2 2 33 <= 36Boxing-Hrs 0.75 0.75 0.5 0.5 7.5 <= 7.5M-Jacket>3 1 3 >= 3W-Jacket>3 1 3 >= 3M-Pants>3 1 3 >= 3W-Pants>3 1 3 >= 3

APPAREL INDUSTRY - Solution

Additional constraints

29

• If the minimum required of 300 women’s pants is increased to 350, what will happen to the profit?

Adjustable CellsFinal Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease$B$2 MenJackets 3 0 2000 800 1E+30$C$2 WomenJackets 3.666666667 0 2800 1E+30 550$D$2 MenPants 3 0 1200 666.6666667 1E+30$E$2 WomenPants 3 0 1500 366.6666667 1E+30

ConstraintsFinal Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease$F$5 Denim-Yds Total 1958.333333 0 2500 1E+30 541.6666667$F$6 Cutting-Hrs Total 35.66666667 0 36 1E+30 0.333333333$F$7 Stitching-Hrs Total 35 0 36 1E+30 1$F$8 Boxing-Hrs Total 8 3733.333333 8 0.0625 0.5$F$9 M-Jacket>3Total 3 -800 3 0.666666667 0.333333333$F$10 W-Jacket>3 Total 3.666666667 0 3 0.666666667 1E+30$F$11 M-Pants>3 Total 3 -666.6666667 3 1 0.5$F$12 W-Pants>3 Total 3 -366.6666667 3 1 0.5

APPAREL INDUSTRY - Solution

3.5

Cover only if the 100% rule was discussed in class

30

• Managements wants to relax one of the constraints on the minimum of 300 units production by 30 units. Which constraint should be selected? What is the new profit?

APPAREL INDUSTRY - Solution

Discussion:

Material constraint150MJacket+125WJacket+200MPants+150WPants £ 2500

2600

Minimum required constraint MJacket 32

Cover only if the 100% rule was discussed in class

31

Adjustable CellsFinal Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease$B$2 MenJackets 3 0 2000 800 1E+30$C$2 WomenJackets 3.666666667 0 2800 1E+30 550$D$2 MenPants 3 0 1200 666.6666667 1E+30$E$2 WomenPants 3 0 1500 366.6666667 1E+30

ConstraintsFinal Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease$F$5 Denim-Yds Total 1958.333333 0 2500 1E+30 541.6666667$F$6 Cutting-Hrs Total 35.66666667 0 36 1E+30 0.333333333$F$7 Stitching-Hrs Total 35 0 36 1E+30 1$F$8 Boxing-Hrs Total 8 3733.333333 8 0.0625 0.5$F$9 M-Jacket>3Total 3 -800 3 0.666666667 0.333333333$F$10 W-Jacket>3 Total 3.666666667 0 3 0.666666667 1E+30$F$11 M-Pants>3 Total 3 -666.6666667 3 1 0.5$F$12 W-Pants>3 Total 3 -366.6666667 3 1 0.5

• Managements wants to relax one of the constraints on the minimum of 300 units production by 30 units. Which constraint should be selected? What is the new profit?

APPAREL INDUSTRY - Solution

32

• Managements wants to relax one of the constraints on the minimum of 300 units production by 30 units. Which constraint should be selected? What is the new profit?

APPAREL INDUSTRY - Solution

Change in objective value = (Shadow price)(Change in the right hand side) = (-800)(-.3) = +240.The new objective value is: 22,500+240 = 22,740.

The change in the right hand side is (-.3) because:(i) Relaxing this constraint means a reduction(!) in the right hand side(ii) A change of 30 units translates to .3

33

Modeling and Sensitivity Analysis– Example 2

• AGRICULTURE: BP Farms is a 300-acre farm located near Lawrence, Kansas, owned and operated exclusively By Bill Phashley. For the upcoming growing season, Bill will grow wheat, corn, oats, and soybeans. The following table gives relevant data concerning expected crop yields, labor required, expected expenses, and water required. Also included is the price per bushel Bill expects to r4eceivre when the crops are harvested.

34

• Bill wishes to produce at least 30,000 bushels of wheat and 30,000 bushels of corn, but not more than 25,000 bushels of oats.

• Bill has $25,000 to invest in his crop.

• Bill plans to work 12 hours a day during the 150-day season.

• He does not wish to exceed the base water supply of 1200acre-feet allocated to him.

Yield (bush./acr

e

Labor (hr/acre

)

Expenses ($/acre)

Water

(acre-ft./acre)

Price

($/bushel)

Wheat 210 4 $50 2 $3.20

Corn 300 5 $75 6 $2.55

Oats 180 3 $30 1 $1.45

Soybeans 240 10 $60 4 $3.10

AGRICALTURE

35

• How many acres should Bill allocate to each crop?

Discussion:• Since the return depends on the acres allocated to each crop, the decision

variables are Wheat, Corn, Oats, and Soybeans expressed in acres.• The objective function represents the return, that is sales minus expenses.

In general for each crop:Return from selling a crop = {[Price per bushel][Yield in bushels per acre] – [Expenses in $ per acre]}[Acres]For example: Return from selling wheat = [(3.20$/bu.)(210bu./acre) – 50](“Wheat” in acres)

AGRICALTURE – Solution

36

• How many acres should Bill allocate to each crop?

AGRICALTURE – Solution

Wheat Corn Oats Soybeans

TotalSales 622 690 231 684 0Acres 1 1 1 1 0 <= 300Wheat>30K 1 0 >= 30000Corn>30K 1 0 >= 30000Oats<25K 1 0 <= 25000Budget 50 75 30 60 0 <= 25000Water 2 6 1 4 0 <= 1200Labor 4 5 3 10 0 = 1800

622=(3.2)(210)-50

Wheat Corn Oats Soybeabs142.8571 142.8571 0 14.28571

TotalSales 622 690 231 684 197200Acres 1 1 1 1 300 <= 300Wheat>30K 210 30000 >= 30000Corn>30K 300 42857.14 >= 30000Oats<25K 180 0 <= 25000Budget 50 75 30 60 18714.29 <= 25000Water 2 6 1 4 1200 <= 1200Labor 4 5 3 10 1428.571 <= 1800

622=(3.2)(210)-50

37

• If the selling price of oats remains $1.45 a bushel, (1) to what level must the yield increase before oats should be planted? (2) If the yield remains 180 bu./acre, to what level would the price of oats have to rise before oats should be planted?

AGRICALTURE – Solution

Adjustable CellsFinal Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease$B$2 Wheat 142.8571429 0 672 50.99999999 1E+30$C$2 Corn 142.8571429 0 765 50.99999999 21$D$2 Oats 0 -451.5000055 260.9999967 451.5000055 1E+30$E$2 Soybeabs 14.28571429 0 744 21 25.5

ConstraintsFinal Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease$F$5 Acres Total 300 702 300 18.57142857 4.761904762$F$6 Wheat>30K Total 30000 -0.242857143 30000 1500 7090.909091$F$7 Corn>30K Total 42857.14286 0 30000 12857.14286 1E+30$F$8 Oats<25K Total 0 0 25000 1E+30 25000$F$9 Budget Total 18714.28571 0 25000 1E+30 6285.714286$F$10 Water Total 1200 10.5 1200 28.57142857 85.71428571$F$11 Labor Total 1428.571429 0 1800 1E+30 371.4285714

We need to use the range of optimality for the coefficientof Oats in the objective function. For Oats to be planted itsreturn per acre should be at least 261+451.5 = $712.5.(1) If the price remains $1.45 a bushel, the yield should increase to 712.5/1.45 = 491.38 bushels per acre.(2) If the yield remain 180 bushels/acre the price should increase to 712.5/180 = $3.95 per bushel

38

• If there were no constraint on the minimum production of corn, would corn be planted?

AGRICALTURE – Solution

Adjustable CellsFinal Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease$B$2 Wheat 142.8571429 0 672 50.99999999 1E+30$C$2 Corn 142.8571429 0 765 50.99999999 21$D$2 Oats 0 -451.5000055 260.9999967 451.5000055 1E+30$E$2 Soybeabs 14.28571429 0 744 21 25.5

ConstraintsFinal Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease$F$5 Acres Total 300 702 300 18.57142857 4.761904762$F$6 Wheat>30K Total 30000 -0.242857143 30000 1500 7090.909091$F$7 Corn>30K Total 42857.14286 0 30000 12857.14286 1E+30$F$8 Oats<25K Total 0 0 25000 1E+30 25000$F$9 Budget Total 18714.28571 0 25000 1E+30 6285.714286$F$10 Water Total 1200 10.5 1200 28.57142857 85.71428571$F$11 Labor Total 1428.571429 0 1800 1E+30 371.4285714

No constraint on the minimum production of corn translates to aconstraint of the form 300Corn 0. Notice that this is always true (and in fact already exists as a non-negativity constraint). A change in the right hand side of this constraint has occurred (from 30000 down to zero).Since the current solution calls for a production of 42,857 bushels,the optimal solution remains unchanged, and corn is still planted.

39

• Bill can lease an adjacent 40-acre parcel for $10000. Should Bill lease this property for this price?

Adjustable CellsFinal Reduced Objective Allowable Allowable

Cell Name Value Cost Coefficient Increase Decrease$B$2 Wheat 142.8571429 0 672 50.99999999 1E+30$C$2 Corn 142.8571429 0 765 50.99999999 21$D$2 Oats 0 -451.5000055 260.9999967 451.5000055 1E+30$E$2 Soybeabs 14.28571429 0 744 21 25.5

ConstraintsFinal Shadow Constraint Allowable Allowable

Cell Name Value Price R.H. Side Increase Decrease$F$5 Acres Total 300 702 300 18.57142857 4.761904762$F$6 Wheat>30K Total 30000 -0.242857143 30000 1500 7090.909091$F$7 Corn>30K Total 42857.14286 0 30000 12857.14286 1E+30$F$8 Oats<25K Total 0 0 25000 1E+30 25000$F$9 Budget Total 18714.28571 0 25000 1E+30 6285.714286$F$10 Water Total 1200 10.5 1200 28.57142857 85.71428571$F$11 Labor Total 1428.571429 0 1800 1E+30 371.4285714

AGRICALTURE – Solution

A change occurs in the “Acres Total” constraint. The right hand sideis changing from 300 to 340. The maximum value of the right hand side for the shadow price to remain unchanged is 300+18.57=318.57. So the shadow price changes if the total acre is 340. Still, we can answer the question.At 318.57 acres the objective value (total return) increases by (Shadow price)(Constraint change) = (702)(18.57) = $13,036.This amount is greater than the cost of $10,000. Clearly, with a changeof 40 acres the return exceeds the cost. Bill should lease the property.


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