8 Problems, Hart Manufacturing makes three products. Each product requires manufacturing operations in three departments: A, B, and C. The labor-hour requirements, by department, are as follows: Probl
Problem 11-11
Hart Manufacturing makes three products. Each product requires manufacturing operations in three departments: A, B, and C. The labor-hour requirements, by department, are as follows:
During the next production period, the labor-hours available are 450 in department A, 350 in department B, and 50 in department C. The profit contributions per unit are $25 for product 1, $28 for product 2, and $30 for product 3.
Formulate a linear programming model for maximizing total profit contribution. If required, round your answers to two decimal places. For those boxes in which you must enter subtractive or negative numbers use a minus sign. (Example: -300)
Let Pi = units of product i producedMax
fill in the blank 1P1
fill in the blank 2P2
fill in the blank 3P3
s.t.
fill in the blank 4P1
fill in the blank 5P2
2P3
≤
fill in the blank 6
2P1
fill in the blank 7P2
fill in the blank 8P3
≤
fill in the blank 9
fill in the blank 10P1
.25P2
fill in the blank 11P3
≤
fill in the blank 12
P1, P2, P3 ≥ 0
Solve the linear program formulated in part (a). How much of each product should be produced, and what is the projected total profit contribution?
P1 = fill in the blank 13
P2 = fill in the blank 14
P3 = fill in the blank 15
Profit = $ fill in the blank 16After evaluating the solution obtained in part (b), one of the production supervisors noted that production setup costs had not been taken into account. She noted that setup costs are $400 for product 1, $550 for product 2, and $600 for product 3. If the solution developed in part (b) is to be used, what is the total profit contribution after taking into account the setup costs?
Profit = $ fill in the blank 17Management realized that the optimal product mix, taking setup costs into account, might be different from the one recommended in part (b). Formulate a mixed-integer linear program that takes setup costs into account. Management also stated that we should not consider making more than 175 units of product 1, 150 units of product 2, or 140 units of product 3. If required, round your answers to two decimal places. For those boxes in which you must enter subtractive or negative numbers use a minus sign. (Example: -300) Here introduce a 0-1 variable yi that is one if any quantity of product i is produced and zero otherwise.
Max
fill in the blank 18P1
fill in the blank 19P2
fill in the blank 20P3
fill in the blank 21y1
fill in the blank 22y2
fill in the blank 23y3
s.t.
fill in the blank 24P1
fill in the blank 25P2
2P3
≤
fill in the blank 26
2P1
fill in the blank 27P2
fill in the blank 28P3
≤
fill in the blank 29
fill in the blank 30P1
.25P2
fill in the blank 31P3
≤
fill in the blank 32
fill in the blank 33P1
fill in the blank 34y1
≤
fill in the blank 35
fill in the blank 36P2
fill in the blank 37y2
≤
fill in the blank 38
fill in the blank 39P3
fill in the blank 40y3
≤
fill in the blank 41
P1, P2, P3 ≥ 0; y1, y2, y3 = 0, 1
Solve the mixed-integer linear program formulated in part (d). How much of each product should be produced, and what is the projected total profit contribution? Compare this profit contribution to that obtained in part (c).
P1 = fill in the blank 42
P2 = fill in the blank 43
P3 = fill in the blank 44
Profit = $ fill in the blank 45
The profit is by $ fill in the blank 47.
Problem 11-13
The Martin-Beck Company operates a plant in St. Louis with an annual capacity of 30,000 units. Product is shipped to regional distribution centers located in Boston, Atlanta, and Houston. Because of an anticipated increase in demand, Martin-Beck plans to increase capacity by constructing a new plant in one or more of the following cities: Detroit, Toledo, Denver, or Kansas City. The estimated annual fixed cost and the annual capacity for the four proposed plants are as follows:
Proposed Plant | Annual Fixed Cost | Annual Capacity |
Detroit | $175,000 | 10,000 |
Toledo | $300,000 | 20,000 |
Denver | $375,000 | 30,000 |
Kansas City | $500,000 | 40,000 |
The company's long-range planning group developed forecasts of the anticipated annual demand at the distribution centers as follows:
Distribution Center | Annual Demand |
Boston | 30,000 |
Atlanta | 20,000 |
Houston | 20,000 |
The shipping cost per unit from each plant to each distribution center is shown in table below.
A network representation of the potential Martin-Beck supply chain is shown in figure below.
Each potential plant location is shown; capacities and demands are shown in thousands of units. This network representation is for a transportation problem with a plant at St. Louis and at all four proposed sites. However, the decision has not yet been made as to which new plant or plants will be constructed.
Formulate a model that could be used for choosing the best plant locations and for determining how much to ship from each plant to each distribution center. There is a policy restriction that a plant must be located either in Detroit or in Toledo, but not both. For those boxes in which you must enter subtractive or negative numbers use a minus sign. (Example: -300)
Let
y1 = 1 if a plant is constructed in Detroit; 0 if not
y2 = 1 if a plant is constructed in Toledo; 0 if not
y3 = 1 if a plant is constructed in Denver; 0 if not
y4 = 1 if a plant is constructed in Kansas City; 0 if not
xij = the units shipped in thousands from plant i to distribution center j
i= 1,2,3,4,5, and j = 1,2,3
-
Min
fill in the blank 1x11
fill in the blank 2x12
fill in the blank 3x13
fill in the blank 4x21
fill in the blank 5x22
fill in the blank 6x23
fill in the blank 7x31
fill in the blank 8x32
fill in the blank 9x33
fill in the blank 10x41
fill in the blank 11x42
fill in the blank 12x43
fill in the blank 13x51
fill in the blank 14x52
fill in the blank 15x53
fill in the blank 16y1
fill in the blank 17y2
fill in the blank 18y3
fill in the blank 19y4
s.t. | |||||||||||||||||||
x11 | fill in the blank 21x12 | fill in the blank 22x13 | fill in the blank 23y1 |
| fill in the blank 25 | Detriot capacity | |||||||||||||
fill in the blank 26x21 | fill in the blank 27x22 | fill in the blank 28x23 | fill in the blank 29y2 |
| fill in the blank 31 | Toledo capacity | |||||||||||||
fill in the blank 32x31 | fill in the blank 33x32 | fill in the blank 34x33 | fill in the blank 35y3 |
| fill in the blank 37 | Denver capacity | |||||||||||||
fill in the blank 38x41 | fill in the blank 39x42 | fill in the blank 40x43 | fill in the blank 41y4 |
| fill in the blank 43 | Kansas City capacity | |||||||||||||
fill in the blank 44x51 | fill in the blank 45x52 | fill in the blank 46x53 |
| fill in the blank 48 | St. Louis capacity | ||||||||||||||
fill in the blank 49x11 | fill in the blank 50x21 | fill in the blank 51x31 | fill in the blank 52x41 | fill in the blank 53x51 |
| fill in the blank 55 | Boston demand | ||||||||||||
fill in the blank 56x12 | fill in the blank 57x22 | fill in the blank 58x32 | fill in the blank 59x42 | fill in the blank 60x52 |
| fill in the blank 62 | Atlanta demand | ||||||||||||
fill in the blank 63x13 | fill in the blank 64x23 | fill in the blank 65x33 | fill in the blank 66x43 | fill in the blank 67x53 |
| fill in the blank 69 | Houston demand | ||||||||||||
xij ≥ for all i and j; y1 , y2 , y3 , y1 + y2 |
Formulate a model that could be used for choosing the best plant locations and for determining how much to ship from each plant to each distribution center. There is a policy restriction that no more than two plants can be located in Denver, Kansas City, and St. Louis. For those boxes in which you must enter subtractive or negative numbers use a minus sign. (Example: -300)
Let | |
y1 = 1 if a plant is constructed in Detroit; 0 if not | |
y2 = 1 if a plant is constructed in Toledo; 0 if not | |
y3 = 1 if a plant is constructed in Denver; 0 if not | |
y4 = 1 if a plant is constructed in Kansas City; 0 if not | |
xij = the units shipped in thousands from plant i to distribution center j | |
i= 1,2,3,4,5, and j = 1,2,3 |
Min | fill in the blank 78x11 | fill in the blank 79x12 | fill in the blank 80x13 | fill in the blank 81x21 | fill in the blank 82x22 | fill in the blank 83x23 | fill in the blank 84x31 | fill in the blank 85x32 | fill in the blank 86x33 | fill in the blank 87x41 | fill in the blank 88x42 | ||||||||||
fill in the blank 89x43 | fill in the blank 90x51 | fill in the blank 91x52 | fill in the blank 92x53 | fill in the blank 93y1 | fill in the blank 94y2 | fill in the blank 95y3 | fill in the blank 96y4 |
s.t. | |||||||||||||||||||
fill in the blank 97x11 | fill in the blank 98x12 | fill in the blank 99x13 | fill in the blank 100y1 |
| fill in the blank 102 | Detriot capacity | |||||||||||||
fill in the blank 103x21 | fill in the blank 104x22 | fill in the blank 105x23 | fill in the blank 106y2 |
| fill in the blank 108 | Toledo capacity | |||||||||||||
fill in the blank 109x31 | fill in the blank 110x32 | fill in the blank 111x33 | fill in the blank 112y3 |
| fill in the blank 114 | Denver capacity | |||||||||||||
fill in the blank 115x41 | fill in the blank 116x42 | fill in the blank 117x43 | fill in the blank 118y4 |
| fill in the blank 120 | Kansas City capacity | |||||||||||||
fill in the blank 121x51 | fill in the blank 122x52 | fill in the blank 123x53 |
| fill in the blank 125 | St. Louis capacity | ||||||||||||||
fill in the blank 126x11 | fill in the blank 127x21 | fill in the blank 128x31 | fill in the blank 129x41 | fill in the blank 130x51 |
| fill in the blank 132 | Boston demand | ||||||||||||
fill in the blank 133x12 | fill in the blank 134x22 | fill in the blank 135x32 | fill in the blank 136x42 | fill in the blank 137x52 |
| fill in the blank 139 | Atlanta demand | ||||||||||||
fill in the blank 140x13 | fill in the blank 141x23 | fill in the blank 142x33 | fill in the blank 143x43 | fill in the blank 144x53 |
| fill in the blank 146 | Houston demand | ||||||||||||
xij ≥ for all i and j; y1 , y2 , y3 , y3 + y4 |
Problem 11-3
Consider the following all-integer linear program:
Choose the correct graph which shows the constraints for this problem and uses dots to indicate all feasible integer solutions.
(i) | (ii) | ||
(iii) | (iv) |
Graph_______?_______
Solve the LP Relaxation of this problem.
The optimal solution to the LP Relaxation is x1 = fill in the blank 2, x2 = fill in the blank 3. Its value is fill in the blank 4.Find the optimal integer solution.
The optimal solution to the LP Relaxation is x1 = fill in the blank 5, x2 = fill in the blank 6. Its value is fill in the blank 7.
Problem 11-23
Roedel Electronics produces a variety of electrical components, including a remote control for televisions and a remote control for DVD players. Each remote control consists of three subassemblies that are manufactured by Roedel: a base, a cartridge, and a keypad. Both remote controls use the same base subassembly, but different cartridge and keypad subassemblies.
Roedel's sales forecast indicates that 7000 TV remote controls and 5000 DVD remote controls will be needed to satisfy demand during the upcoming Christmas season. Because only 500 hours of in-house manufacturing time are available, Roedel is considering purchasing some, or all, of the subassemblies from outside suppliers. If Roedel manufactures a subassembly in-house, it incurs a fixed setup cost as well as a variable manufacturing cost. The following table shows the setup cost, the manufacturing time per subassembly, the manufacturing cost per subassembly, and the cost to purchase each of the subassemblies from an outside supplier:
Determine how many units of each subassembly Roedel should manufacture and how many units Roedel should purchase.
Variable names
Value
No. of bases manufactured
fill in the blank 1
No. of bases purchased
fill in the blank 2
No. of TV cartridges made
fill in the blank 3
No. of TV cartridges purchased
fill in the blank 4
No. of DVD cartridge made
fill in the blank 5
No. of DVD cartridge purchased
fill in the blank 6
No. of TV keypads made
fill in the blank 7
No. of TV keypads purchased
fill in the blank 8
No. of DVD keypads made
fill in the blank 9
No. of DVD keypads purchased
fill in the blank 10
What is the total manufacturing and purchase cost associated with your recommendation?
$ fill in the blank 11Suppose Roedel is considering purchasing new machinery to produce DVD cartridges. For the new machinery, the setup cost is $3000; the manufacturing time is 2.5 minutes per cartridge, and the manufacturing cost is $2.60 per cartridge. Assuming that the new machinery is purchased, determine how many units of each subassembly Roedel should manufacture and how many units of each subassembly Roedel should purchase.
Variable names
Value
No. of bases manufactured
fill in the blank 12
No. of bases purchased
fill in the blank 13
No. of TV cartridges made
fill in the blank 14
No. of TV cartridges purchased
fill in the blank 15
No. of DVD cartridge made
fill in the blank 16
No. of DVD cartridge purchased
fill in the blank 17
No. of TV keypads made
fill in the blank 18
No. of TV keypads purchased
fill in the blank 19
No. of DVD keypads made
fill in the blank 20
No. of DVD keypads purchased
fill in the blank 21
What is the total manufacturing and purchase cost associated with your recommendation?
$ fill in the blank 22
Do you think the new machinery should be purchased?
Explain.
The input in the box below will not be graded, but may be reviewed and considered by your instructor.
Problem 11-1
(a) | Indicate whether the following linear program is an all-integer linear program or a mixed-integer linear program. |
Max | 30x1 + 25x2 |
s.t. | |
3x1 + 1.5x2 ≤ 400 | |
1.5x1 + 2x2 ≤ 250 | |
1x1 + 1x2 ≤ 150 | |
x1, x2 ≥ 0 and x2 integer |
This is a ____?_____linear program. |
Write the LP Relaxation for the problem but do not attempt to solve. | |
If required, round your answers to one decimal place. | |
Its LP Relaxation is |
Max | fill in the blank 2x1 + _______?_____x2 | |
s.t. | ||
fill in the blank 4x1 + 1.5x2 __?___ | ||
1.5x1 + fill in the blank 7x2 _____?____ | ||
fill in the blank 10x1 + ___?____x2 ____?____ | ||
x1 , x2 |
(b) | Indicate whether the following linear program is an all-integer linear program or a mixed-integer linear program. |
Max | 3x1 + 4x2 |
s.t. | |
2x1 + 4x2 ≥ 8> | |
2x1 + 6x2 ≥ 12 | |
x1, x2 ≥ 0 and integer |
This is a linear program. |
Write the LP Relaxation for the problem but do not attempt to solve. | |
If required, round your answers to one decimal place. | |
Its LP Relaxation is |
Max | fill in the blank 17x1 + fill in the blank 18x2 |
s.t. | |
2x1 + fill in the blank 19x2 fill in the blank 21 | |
fill in the blank 22x1 + 6x2 fill in the blank 24 | |
x1 , x2 |
Problem 12-07
Hanson Inn is a 96-room hotel located near the airport and convention center in Louisville, Kentucky. When a convention or a special event is in town, Hanson increases its normal room rates and takes reservations based on a revenue management system. The Classic Corvette Owners Association scheduled its annual convention in Louisville for the first weekend in June. Hanson Inn agreed to make at least 50% of its rooms available for convention attendees at a special convention rate in order to be listed as a recommended hotel for the convention. Although the majority of attendees at the annual meeting typically request a Friday and Saturday two-night package, some attendees may select a Friday night only or a Saturday night only reservation. Customers not attending the convention may also request a Friday and Saturday two-night package, or make a Friday night only or Saturday night only reservation. Thus, six types of reservations are possible: convention customers/two-night package; convention customers/Friday night only; convention customers/Saturday night only; regular customers/two-night package; regular customers/Friday night only; and regular customers/Saturday night only.
The cost for each type of reservation is shown here.
The anticipated demand for each type of reservation is as follows:
Hanson Inn would like to determine how many rooms to make available for each type of reservation in order to maximize total revenue.
Define the decision variables and state the objective function.
Let
CT = number of convention two-night rooms
CF = number of convention Friday only rooms
CS = number of convention Saturday only rooms
RT = number of regular two-night rooms
RF = number of regular Friday only rooms
RS = number of regular Saturday only room
-
fill in the blank 2CT
fill in the blank 3CF
fill in the blank 4CS
fill in the blank 5RT
fill in the blank 6RF
fill in the blank 7RS
Formulate a linear programming model for this revenue management application.
fill in the blank 9CT
fill in the blank 10CF
fill in the blank 11CS
fill in the blank 12RT
fill in the blank 13RF
fill in the blank 14RS
-
S.T.
-
1)
fill in the blank 15CT
fill in the blank 17
2)
fill in the blank 18CF
fill in the blank 20
3)
fill in the blank 21CS
fill in the blank 23
4)
fill in the blank 24RT
fill in the blank 26
5)
fill in the blank 27RF
fill in the blank 29
6)
fill in the blank 30RS
fill in the blank 32
7)
fill in the blank 33CT
fill in the blank 34CF
fill in the blank 36
8)
fill in the blank 37CT
fill in the blank 38CS
fill in the blank 40
9)
fill in the blank 41CT
fill in the blank 42CF
fill in the blank 43RT
fill in the blank 44RF
fill in the blank 46
10)
fill in the blank 47CT
fill in the blank 48CS
fill in the blank 49RT
fill in the blank 50RS
fill in the blank 52
What is the optimal allocation and the anticipated total revenue?
Variable
Value
CT
fill in the blank 53
CF
fill in the blank 54
CS
fill in the blank 55
RT
fill in the blank 56
RF
fill in the blank 57
RS
fill in the blank 58
Total Revenue = $ fill in the blank 59Suppose that one week before the convention, the number of regular customers/Saturday night only rooms that were made available sell out. If another nonconvention customer calls and requests a Saturday only room, what is the value of accepting this additional reservation?
The shadow price for constraint 10 is $ fill in the blank 60 and shows an added profit of $ fill in the blank 61 if this additional reservation is accepted.
Problem 12-11 (Algorithmic)
Consider the problem
Min | 2X2 – 15X + 2XY + Y2 – 20Y + 65 |
s.t. | X + 3Y ≤ 10 |
Find the minimum solution to this problem. If required, round your answers to two decimal places.
The optimal solution is X = fill in the blank 1, Y = fill in the blank 2, for an optimal solution value of fill in the blank 3.If the right-hand side of the constraint is increased from 10 to 11, how much do you expect the objective function to change? If required, round your answer to two decimal places.
The optimal objective function value will by fill in the blank 5.Re-solve the problem with a new right-hand side of 11. How does the actual change compare with your estimate? If required, round your answers to two decimal places.
The new optimal objective function value is fill in the blank 6 so the actual is fill in the blank 8.
Problem 12-23
Markowitz portfolio optimization: Harry Markowitz received the 1990 Nobel Prize for his path-breaking work in portfolio optimization. One version of the Markowitz model is based on minimizing the variance of the portfolio subject to a constraint on return. The below table shows the annual return (%) for five 1-year periods for the six mutual funds with the last row that gives the S&P 500 return for each planning scenario. Scenario 1 represents a year in which the annual returns are good for all the mutual funds. Scenario 2 is also a good year for most of the mutual funds. But scenario 3 is a bad year for the small-cap value fund; scenario 4 is a bad year for the intermediate-term bond fund; and scenario 5 is a bad year for four of the six mutual funds.
If each of the scenarios is equally likely and occurs with probability 1/5, then the mean return or expected return of the portfolio is
Using the scenario return data given in Table above, the Markowitz mean-variance model can be formulated. The objective function is the variance of the portfolio and should be minimized. Assume that the required return on the portfolio is 10%. There is also a unity constraint that all of the money must be invested in mutual funds.
Most investors are happy when their returns are "above average," but not so happy when they are "below average." In the Markowitz portfolio optimization model given above, the objective function is to minimize variance, which is given by
where Rs is the portfolio return under scenario s and R is the expected or average return of the portfolio.
With this objective function, we are choosing a portfolio that minimizes deviations both above and below the average, R. However, most investors are happy when Rs > R, but unhappy when Rs < R. With this preference in mind, an alternative to the variance measure in the objective function for the Markowitz model is the semivariance. The semivariance is calculated by only considering deviations below R.
Let Dsp - Dsn - Rs - R and restrict Dsp and DDsn to be nonnegative. Then Dsp measures the positive deviation from the mean return in scenario s (i.e., DDsp = Rs - R when Rs R)
In the case where the scenario return is below the average return, Rs < R, we have - Dsn = Rs - R. Using these new variables, we can reformulate the Markowitz model to only minimize the square of negative deviations below the average return. By doing so, we will use the semivariance rather than the variance in the objective function.
Solve the Markowitz portfolio optimization model that can be prepared for above case to use semivariance in the objective function. Solve the model using either Excel Solver or LINGO. If required, round your answers to one decimal place.
Mutual Funds | Investments in % |
Foreign Stock | fill in the blank 1% |
Intermediate-Term Bond | fill in the blank 2% |
Large-Cap Growth | fill in the blank 3% |
Large-Cap Value | fill in the blank 4% |
Small-Cap Growth | fill in the blank 5% |
Small-Cap Value | fill in the blank 6% |