[PDF] SEN301 OPERATIONS RESEARCH I PREVIUOS EXAM


SEN301 OPERATIONS RESEARCH I PREVIUOS EXAM


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DEPARTMENT OF MECHANICAL ENGINEERING BM7002 DEPARTMENT OF MECHANICAL ENGINEERING BM7002

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[PDF] sen301 operations research i previuos exam questions

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What are the principal operations research (or) tools?

    Introduction This volume presents the principal operations research (OR) tools that help in the planning and management of all sorts of networks. The term “network” is to be understood in a very broad sense. In effect, this term also designates physical networks, such as road or railway networks, as well as logical networks, used for

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    Operations Research and Networks Edited by Gerd Finke Series Editor Pierre Dumolard First published in France in 2002 by Hermes Science/Lavoisier entitled: “Recherche opérationnelle et réseaux: Méthodes d’analyse spatiale” First published in Great Britain and the United States in 2008 by ISTE Ltd and John Wiley & Sons, Inc.

What are the constraints in operations research and networks?

    Introduction written by Gerd FINKE. x Operations Research and Networks certain conditions (constraints). These constraints are linear (equations or inequations) and model the use of finite capacity resources, distance limits, budget restrictions, etc.

SEN301 OPERATIONS RESEARCH I

PREVIUOS EXAM QUESTIONS

1. A company is involved in the production of two items (X and Y). The resources need to produce X and Y

are twofold, namely machine time for automatic processing and craftsman time for hand finishing. The table below gives the number of minutes required for each item:

Machine time Craftsman time

Item X 13 20

Item Y 19 29

The company has 40 hours of machine time available in the next working week but only 35 hours of

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hour worked. Both machine and craftsman idle times incur no costs. The revenue received for each item

produced (alO SURGXŃPLRQ LV VROG LV ...20 IRU ; MQG ...30 IRU KB 7OH ŃRPSMQ\ OMV M VSHŃLILŃ ŃRQPUMŃP PR

produce 10 items of X per week for a particular customer. Formulate the problem of deciding how much to produce per week as a linear program.

2. Answer the questions related to the model below:

max. 3 x1 + 2 x2 st 2 x1 + 2 x2

2 x1 + x2

x1 + 2 x2 x1, x2 a. Use the graphical solution technique to find the optimal solution to the model. b. Use the simplex algorithm to find the optimal solution to the model.

c. For which objective function coefficient value ranges of x1 and x2 does the solution remain optimal?

d. Find the dual of the model.

3. Consider the following problem.

max 3x1 + 2x2 s.t. 3x1 + x2 " 12 x1 + x2 " 6

5x1 + 3x2 " 27

x1, x2 • 0.

a) Solve the problem by the original simplex method (in tabular form). Identify the complementary basic

solution for the dual problem obtained at each iteration.

b) Solve the dual of this problem manually by the dual simplex method. Compare the resulting sequence

of basic solutions with the complementary basic solutions obtained in part (a).

4. Use the revised simplex algorithm manually to solve the following problem.

min 5x1 + 2x2 + 4x3 s.t. 3x1 + x2 + 2x3 " 4

6x1 + 3x2 + 5x3 " 10

x1, x2, x3 " 0

5. 0MoNM 3ROLŃH 6PMPLRQ HPSOR\V 30 SROLŃH RIILŃHUVB (MŃO RIILŃHU RRUNV IRU D GM\V SHU RHHNB 7OH ŃULPH UMPH

fluctuates with the day of week, so the number of the police officers required each day depends on

which day of the week it is: Monday, 18; Tuesday, 24; Wednesday, 25; Thursday, 16; Friday, 21;

Saturday, 28; Sunday, 18. The Police Station wants to schedule police officers to minimize the number

whose days off are not consecutive. Formulate an LP that will accomplish this goal.

6. Turkish national swimming team coach is putting together a relay team for the 400 meter relay. Each

swimmer must swim 100 meters of breaststroke, backstroke, butterfly, or free style. The coach believes

that each swimmer will attain the tLPHV VHŃRQGV JLYHQ LQ POH 7MNOH NHORRB 7R PLQLPL]H POH PHMP·V PLPH

for the race, assign each swimmer for a stroke.

Free Breast Fly Back

Derya 54 54 51 53

Murat 51 57 52 52

Deniz 50 53 54 56

Ceyhun 56 54 55 53

7. A shoe company forecasts the following demands during the next three months: 200, 260, 240. It costs

$7 to produce a pair of shoes with regular time labor (RT) and $11 with overtime labor (OT). During each

month regular production is limited to 200 pairs of shoes, and overtime production is limited to 100 pairs.

It costs $1 per month to hold a pair of shoes in inventory. Formulate a balanced transportation problem

to minimize the total cost of meeting the next three months of demand on time (Do not try to solve it!).

8. 6XSSRVH POMP \RX RQO\ OMYH POH ´UMQJH VHQVLPLYLP\ MQMO\VLVµ SMUP RI M ILQGR RXPSXP IRU M PLQLPL]MPLRQ

problem. a. What is the reduced cost of a non-basic variable? b. What is the surplus quantity for a constraint that is not binding?

9. For the following LP show the starting basis (bfs) of the Big M method (form the initial tableau only!). At

the initial tableau, show the leaving and entering variables. (PS: Please do not try to solve the problem,

optimal solution can be found at iteration 5.) min 4 x1 + x2 s.t. 3 x1 + x2 10 x1 + x2 5 x1 3 x1, x2 0

10. A freight plane has three large compartments to carry cargo. Weight and volume limitations of these

compartments are:

Compartment Weight

(Tons)

Volume

(m3)

Front 10 6800

Center 16 8700

Rear 8 5300

There are four cargos waiting to be loaded in this plane. Properties of these cargos are shown on the

table below: Cargo

Total Weight

(Tons)

Total Volume

(m3)

Profit (TL/ton)

K1 18 8640 310

K2 15 9750 380

K3 23 13340 350

K4 12 4680 285

Furthermore, the weight of the cargo in the respective compartments must be the same proportion of

that compartment's weight capacity to maintain the balance of the plane. Any proportion of these

cargoes can be accepted. Formulate a linear programming model to maximize the profit by choosing how many tons of which cargo to load on the plane under these circumstances.

11. Answer the following questions related with the model given below:

min x1 + x2 s.t. x1 " D x2 " 4 a. Use the Graphical Method to solve the model. b. Use the Simplex Algorithm to solve the model. c. Find the dual of the model.

12. Answer the following questions related with the model given below:

max x1 + x2 s.t. x1 " D x2 " 4 a. Use the Simplex Algorithm to solve the model. b. Find the dual of the model.

13. Consider the following LP model:

1 2 3 1 2 3 12 1 2 3 53
23
4 0 t mak. 2 z x x x x x x xx x x x a. Find the dual of the model. b. Given that basic variables are 1x and 3x in the primal optimal solution, find the dual optimal solution (dual variables value and dual objective function value) without solving the dual model.

INFORMATION FOR QUESTIONS 14-25

I3 0RGHO IRU ´Modified $GYHUPLVHPHQP ([MPSOHµ x1: The number of comedy spots x2: The number of football spots min z = 30x1 + 70x2 st 12x1 + 3x2 • 32 (high income women)

4x1 + 9x2 • 16 (high income men)

x1, x2 • 0 Useful information (Please do not solve the model, use this information only):

The optimal solution implies that the 1st constraint is nonbinding with an excess value of 16 and the 2nd

constraint is binding with a shadow price of ²7.5.

14. Please fill in the blanks below at the story of the given LP model:

Dorian makes luxury cars and jeeps for high-income men and women. It wishes to advertise with 1

minute spots in comedy shows and football games. Each comedy spot costs $................. and is seen by

.............. high-income women and .............. high-income men. Each football spot costs $................. and

is seen by .............. high-income women and .............. high-income men. How can Dorian reach .............. high-income women and .............. high-income men at the least cost?

15. Please fill in the blanks below at the report (executive summary):

The minimum cost of reaching the target audience is $.................. , with .............. comedy spots

and .............. football spots.

16. Find the dual of the LP model given. What is the economic interpretation of the dual model (define

decision variables and constraints as well as objective function in the dual model)?

17. What is the optimal solution of the dual model? (Please do not solve the dual model, only submit the

optimal values for the objective function and the decision variables of the dual model)

18. What is the allowable range for the objective function coefficient of x2 in which current solution (basis)

remains optimal? (Hint: Use the relation of Duality-Sensitivity)

19. What are the reduced costs for the decisions variables in the primal model? Why?

20. What is the allowable range for RHS of the first constraint in the primal model in which current solution

(basis) remains optimal?

21. Please fill in the blanks at the Lindo output given below:

OBJECTIVE FUNCTION VALUE

1) ..............

VARIABLE VALUE REDUCED COST

X1 .............. ..............

X2 .............. ..............

ROW SLACK OR SURPLUS DUAL PRICES

2) .............. ..............

3) .............. ..............

RANGES IN WHICH THE BASIS IS UNCHANGED:

OBJ COEFFICIENT RANGES

VARIABLE CURRENT ALLOWABLE ALLOWABLE

COEF INCREASE DECREASE

X1 .............. 1.111111 30.000000 X2 .............. .............. ..............

RIGHTHAND SIDE RANGES

ROW CURRENT ALLOWABLE ALLOWABLE

RHS INCREASE DECREASE

2 .............. .............. ..............

3 .............. INFINITY 5.333333

22. If the cost of a comedy spot is $40K, what would be the new optimal solution to the problem?

23. If the cost of a comedy spot is $25K, what would be the new optimal solution to the problem?

24. If Dorian wishes to reach 13M high income men, what would be the new optimal solution to the problem?

25. Assume that Dorian wishes to make additional advertisements with 1 minute spots in a reality show which

is seen by 6M high income women and 9M high income men. What should be the cost of the reality show spot that would make it reasonable to be selected (to be recommended in the solution)?

26. Consider the following LP problem:

min z x x xx xx xx d d t 12 12 12 12 39
48
24
0

Let the slack variables are

3x and x4 . Find the optimal solution with revised simplex method given that current set of basic variables is `,xx32

27. Consider the following problem:

1 2 3 1 2 3 1 2 3 max 5 5 12 such that 3 20

12 4 10 90

0j

Z x x x

x x x x x x xj d d t Let 4x and 5x represents the slack variables for constraints 1 and 2 respectively. The optimal table is given below: 34

1 2 3 4

1 3 4 5

(0) 3 5 100 (1) 3 20 (2) 16 2 4 10 Z x x x x x x x x x x

Then consider the following changes in the model independently. State for each case, whether the set of

current basic variables or their values change or not, and then if they change, then find the new optimal set

of basic variables and the new optimal solution. a. Add the following constraint:

1 2 32 3 5 50x x x

b. Change the objective function coefficient 1: 11c

28. Recall that the optimal solution for Powerco problem was z=$1,020 and the optimal tableau was:

City 1 City 2 City 3 City 4 Supply

ui/vj 6 6 10 2

Plant 1 0

8 6 10 9

35 10 25

Plant 2 3

9 12 13 7

50 45 5

Plant 3 3

14 9 16 5

40 10 30

Demand

45 20 30 30

a) For what range of values of the cost of shipping 1 million kwh of electricity from plant 3 to city 3 will

the current basis remain optimal? b) Suppose we increase both s3 and d3 by 3. Find the new value of the cost and new values of the decision variables.

29. Nicole Kidman, Jennifer Lopez, Catherine Zeta Jones, and Cameron Diaz are marooned on a desert island

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table given below indicate how much happiness each couple would experience if they spent all their time

together. Determine the partner for each person.

NK JL CZJ CD

BP 7 5 8 2

AB 7 8 9 4

RW 3 5 7 9

TC 5 7 6 9

30. 7OH GHMQ RI M ŃROOHJH PXVP SOMQ POH VŃORRO·V ŃRXUVH RIIHULQJV Ior the fall semester. Student demands

make it necessary to offer at least 30 undergraduate and 20 graduate courses in the term. Faculty

contracts also dictate that at least 60 courses be offered in total. Each undergraduate course taught

costs the college an average of $2500 in faculty wages, and each graduate course costs $3000.

Formulate an LP model to identify number of undergraduate and graduate courses that should be taught

in the fall so at total faculty salaries are kept to a minimum (What are the decision variables, objective,

and the constraints? Indicate sign restrictions if any. Please do not solve the problem).

31. A company must deliver ݀௜ units of its product at the end of the ݅th month (for i= 1,..5, ݀௜ values are

given in the following table). Material produced during a month at a cost of $100 can be delivered at the

end of the same month or can be stored as inventory and delivered at the end of a subsequent month;

however, there is a storage cost of 5 dollars per month for each unit of product held in inventory. At the

beginning of month 1, 3 products are available. If the company produces ݔ௜ units in month ݅ and ݔ௜>5 units

in month ݅

production level. Formulate a linear programming problem whose objective is to minimize the total cost of

the production and inventory schedule over a period of five months. Assume that inventory left at the

end of the year has no value and does not incur any storage cost. (What are the decision variables, objective, and the constraints? Indicate sign restrictions if any. Please do not solve the problem).

Aylar 1 2 3 4 5

݀௜ 15 17 19 11 7

32. 0M[ ] 100L67 í [A + xB + xC )]

S.t; xA + xB + xC 67

3xA 40

10xC 70

5xD 60

(3xA + 7xB + 10xC + 5xD )/5 50 xA + xB + xC = 1,5 xD xA, xB, xC 0; xD urs

Considering the above given LP model;

a) Convert the model to standard form. b) Build the initial tableau to solve it using Big M Method. c) Determine whether the initial bfs is optimal. If it is not, determine which nonbasic variable should become a basic variable and which basic variable should become a nonbasic variable to improve the objective function (do not make any operation to find the next table)

33. max z = 3x1 - 6x2 + x3

s.t. x1 + x2 + x3 8

2x1 - x2 = 5

-x1 +3x2 + 2x3 7 x1, x2, x3 0

While solving the above given LP problem using two-phase simplex method, we reach the following table as

the optimal first Phase LP. Continue to the solution procedure with the second phase (if it is required) and

find an optimal solution for the original problem. w x1 x2 x3 e1 a1 a2 s3 Rhs

1 0 0 0 0 -1 -1 0 0

0 0 1 2/3 -2/3 2/3 -1/3 0 11/3

0 1 0 1/3 -1/3 1/3 1/3 0 13/3

0 0 0 1/3 5/3 -5/3 4/3 1 1/3

34. Silicon Valley Corporation (Silvco) manufactures transistors. An important aspect of the manufacture of

transistors is the melting of the element germanium (a major component of a transistor) in a furnace.

Unfortunately, the melting process yields germanium of highly variable quality. Two methods can be used to melt germanium; method 1 costs $50 per transistor, and method 2 costs

$70 per transistor. The qualities of germanium obtained by methods 1 and 2 are shown in Table 1. Grade

1 is poor while grade 4 is excellent. The quality of the germanium dictates the quality of the

manufactured transistor. Silvco can refire melted germanium in an attempt to improve its quality. It costs $25 to refire the

melted germanium for one transistor. The results of the refiring process are shown in Table 2. Silvco has

sufficient furnace capacity to melt or refire germanium for at most 20,000 transistors per month.

6LOYŃR·V PRQPOO\ GHPMQGV MUH IRU 1000 JUMGH 4 PUMQVLVPRUV 2000 JUMGH 3 PUMQVLVPRUV 3000 JUMGH 2

transistors, and 3,000 grade 1 transistors. Formulate an LP model in general form (with σve ׊ minimize the cost of producing the needed transistors.

Table 1. Percent yielded by melting (%)

Grade of Melted

Germanium

Melting Methods

Method 1 Method 2

Defective 30 20

1 30 20

2 20 25

3 15 20

4 5 15

Table 2. Percent yielded by refiring (%)

Grade Yielded by

Refiring

Refired Grade of germanium

Defective Grade 1 Grade 2 Grade 3

Defective 30 0 0 0

1 25 30 0 0

2 15 30 40 0

3 20 20 30 50

4 10 20 30 50

35. Consider the following LP;

Optimal Tableau:

Z x1 x2 x3 e1 a1 e2 a2 s3 STD TD

1 -2.5 0 0 0 -M -1.25 1.25-M -0.75 7.5 Z = 7.5

-0.5 0 1 0 0 0.25 -0.25 0.75 1.5 x3 = 1.5

0.5 1 0 0 0 -0.25 0.25 0.25 3.5 x2 = 3.5

-1 0 0 1 -1 0 0 1 1 e1 = 1

Lindo Output:

LP OPTIMUM FOUND AT STEP 3 OBJECTIVE FUNCTION VALUEquotesdbs_dbs17.pdfusesText_23
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