# WES

December 10, 2018 | Author: Holly Venturini | Category: Linear Programming, Mathematical Optimization, Systems Analysis, Operations Research, Mathematical Analysis

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Chapter 7—Integer Linear Programming MULTIPLE CHOICE

1. Which of of the followin following g is the most most useful contrib contributio ution n of integer integer programmin programming? g? a. finding finding whole whole number number solutions solutions where where fractional fractional soluti solutions ons would would not be appropr appropriate iate  b. using using 0-1 0-1 variables variables for modeling modeling flexibili flexibility ty c. incr increa ease sed d ease ease of of solu soluti tion on d. provision provision for for solution solution procedures procedures for for transportat transportation ion and assignme assignment nt problems problems ANS: B

PTS: 1

TOP: Introduction

2. In a model, x1 ≥ 0 and integer, x 2 ≥ 0, and x3 = 0, 1. Which solution would not be feasible? a. x1 = 5, x2 = 3, x3 = 0 b. x1 = 4, x2 = .389, x3 = 1 c. x1 = 2, x2 = 3, x3 = .578 d. x1 = 0, x2 = 8, x3 = 0 ANS: C

PTS: 1

TOP: Introduction

3. Rounded Rounded solutio solutions ns to linear linear progra programs ms must must be evaluate evaluated d for  a. feas feasib ibil ilit ity y and opt optim imal alit ity. y.  b.  b. sens sensit itiv ivit ity y and and dual dualit ity. y. c. rela relaxa xati tion on and and boun bounde dedn dnes ess. s. d. each each of the the abo above ve is is tru true. e. ANS: A

PTS: 1

TOP: LP relaxation

4. Rounding Rounding the the solution solution of an LP Relaxati Relaxation on to the nearest nearest integer integer values values provide providess a. a feasible feasible but not not necessa necessarily rily optim optimal al integer integer solution. solution.  b. an inte integer ger solu solutio tion n that that is is optim optimal. al. c. an integer integer solut solution ion that that might might be neithe neitherr feasible feasible nor nor optimal. optimal. d. an inf infea easi sibl blee solu soluti tion on.. ANS: C

PTS: 1

TOP: Graphical solution

5. The solutio solution n to the LP Relaxatio Relaxation n of a maximizatio maximization n integer integer linear program program provid provides es a. an upper upper bound bound for for the value value of the object objective ive funct function. ion.  b. a lower lower bound bound for for the value value of the the objecti objective ve functi function. on. c. an upper upper bound bound for for the value value of the decis decision ion variab variables. les. d. a lower lower bound bound for for the value value of the the decisio decision n variable variables. s. ANS: A

PTS: 1

TOP: Graphical solution

6. The grap graph h of a prob problem lem that that requir requires es x1 and x2 to be integer has a feasible region a. the the same same as as its its LP rela relaxa xati tion on.. b. of do dots. c. of hori horizo zont ntal al stri stripe pes. s. d. of vert vertic ical al stri stripe pes. s. ANS: B

PTS: 1

TOP: Graphical solution

7. The 0-1 0-1 variables variables in the fixed cost models models correspond correspond to

a.  b. c. d.

a process for which a fixed cost occurs. the number of products produced. the number of units produced. the actual value of the fixed cost.

ANS: A

PTS: 1

TOP: Fixed costs

8. Sensitivity analysis for integer linear programming a. can be provided only by computer.  b. has precisely the same interpretation as that from linear programming. c. does not have the same interpretation and should be disregarded. d. is most useful for 0-1 models. ANS: C

PTS: 1

TOP: Sensitivity analysis

9. Let x1 and x2 be 0-1 variables whose values indicate whether projects 1 and 2 are not done or are done. Which answer below indicates that project 2 can be done only if project 1 is done? a. x1 + x2 = 1 b. x1 + x2 = 2 c. x1 − x2 ≤ 0 d. x1 − x2 ≥ 0 ANS: D

PTS: 1

TOP: Conditional and corequisite constraints

10. Let x1 , x2 , and x3 be 0-1 variables whose values indicate whether the projects are not done (0) or are done (1). Which answer below indicates that at least two of the projects must be done? a. x1 + x2 + x3 ≥ 2  b. x1 + x2 + x3 ≤ 2 c. x1 + x2 + x3 = 2 d. x1 − x2 = 0 ANS: A

PTS: 1

TOP: k out of n alternatives constraint

11. If the acceptance of project A is conditional on the acceptance of project B, and vice versa, the appropriate constraint to use is a a. multiple-choice constraint.  b. k out of n alternatives constraint. c. mutually exclusive constraint. d. corequisite constraint. ANS: D PTS: 1 TOP: Modeling flexibility provided by 0-1 integer variables 12. In an all-integer linear program, a. all objective function coefficients must be integer.  b. all right-hand side values must be integer. c. all variables must be integer. d. all objective function coefficients and right-hand side values must be integer. ANS: C

PTS: 1

TOP: Types of integer linear programming models

13. To perform sensitivity analysis involving an integer linear program, it is recommended to a. use the dual prices very cautiously.

b. make multiple computer runs. c. use the same approach as you would for a linear program. d. use LP relaxation. ANS: B

PTS: 1

TOP: A cautionary note about sensitivity analysis

14. Modeling a fixed cost problem as an integer linear program requires a. adding the fixed costs to the corresponding variable costs in the objective function.  b. using 0-1 variables. c. using multiple-choice constraints. d. using LP relaxation. ANS: B

PTS: 1

TOP: Applications involving 0-1 variables

15. Most practical applications of integer linear programming involve a. only 0-1 integer variables and not ordinary integer variables.  b. mostly ordinary integer variables and a small number of 0-1 integer variables. c. only ordinary integer variables. d. a near equal number of ordinary integer variables and 0-1 integer variables. ANS: A

PTS: 1

TOP: Applications involving 0-1 variables

TRUE/FALSE

1. The LP Relaxation contains the objective function and constraints of the IP problem, but drops all integer restrictions. ANS: T

PTS: 1

TOP: LP relaxation

2. In general, rounding large values of decision variables to the nearest integer value causes fewer   problems than rounding small values. ANS: T

PTS: 1

TOP: LP relaxation

3. The solution to the LP Relaxation of a minimization problem will always be less than or equal to the value of the integer program minimization problem. ANS: F

PTS: 1

TOP: Graphical solution

4. If the optimal solution to the LP relaxation problem is integer, it is the optimal solution to the integer  linear program. ANS: T

PTS: 1

TOP: LP relaxation

5. Slack and surplus variables are not useful in integer linear programs. ANS: F

PTS: 1

TOP: Capital budgeting

6. A multiple choice constraint involves selecting k out of n alternatives, where k  ≥ 2. ANS: F

PTS: 1

TOP: Multiple choice constraint

7. In a model involving fixed costs, the 0-1 variable guarantees that the capacity is not available unless the cost has been incurred.

ANS: T

PTS: 1

TOP: Fixed costs

8. If x1 + x2 ≤ 500y1 and y1 is 0-1, then if y 1 is 0, x1 and x2 will be 0. ANS: T

PTS: 1

TOP: Distribution system design

9. The constraint x1 + x2 + x3 + x4 ≤ 2 means that two out of the first four projects must be selected. ANS: F

PTS: 1

TOP: k out of n alternatives constraint

10. The constraint x 1 −x2 = 0 implies that if project 1 is selected, project 2 cannot be. ANS: F

PTS: 1

TOP: Conditional and corequisite constraints

11. The product design and market share optimization problem presented in the textbook is formulated as a 0-1 integer linear programming model. ANS: T PTS: 1 TOP: Product design and market share optimization problem 12. The objective of the product design and market share optimization problem presented in the textbook  is to choose the levels of each product attribute that will maximize the number of sampled customers  preferring the brand in question. ANS: T PTS: 1 TOP: Product design and market share optimization problem 13. If a problem has only less-than-or-equal-to constraints with positive coefficients for the variables, rounding down will always provide a feasible integer solution. ANS: T

PTS: 1

TOP: Rounding to obtain an integer solution

14. Dual prices cannot be used for integer programming sensitivity analysis because they are designed for  linear programs. ANS: T

PTS: 1

TOP: A cautionary note about sensitivity analysis

15. Some linear programming problems have a special structure which guarantees that the variables will have integer values. ANS: T

PTS: 1

TOP: Introduction to integer linear programming

1. The use of integer variables creates additional restrictions but provides additional flexibility. Explain. ANS: Answer not provided. PTS: 1

TOP: Introduction

2. Why are 0-1 variables sometimes called logical variables? ANS: Answer not provided. PTS: 1

TOP: Introduction

3. Give a verbal interpretation of each of these constraints in the context of a capital budgeting problem. a. x1 −x2 ≥ 0  b. x1 −x2 = 0 c.

x 1 + x2 + x3 ≤ 2

ANS: Answer not provided. PTS: 1

TOP: Capital budgeting

4. Explain how integer and 0-1 variables can be used in an objective function to minimize the sum of  fixed and variable costs for production on two machines. ANS: Answer not provided. PTS: 1

TOP: Distribution system design

5. Explain how integer and 0-1 variables can be used in a constraint to enable production. ANS: Answer not provided. PTS: 1

TOP: Distribution system design

PROBLEM

1. Solve the following problem graphically. Max

5X + 6Y

s.t.

17X + 8Y ≤ 136 3X + 4Y ≤ 36 X, Y ≥ 0 and integer

a.  b. c.

Graph the constraints for this problem. Indicate all feasible solutions. Find the optimal solution to the LP Relaxation. Round down to find a feasible integer  solution. Is this solution optimal? Find the optimal solution.

ANS: a.

The feasible region is those integer values in the space labeled feasible region.

b.

Optimal LP relaxed occurs at X = 5.818, Y = 4.636, with Z = 56.909. Rounded down solution occurs at X = 5, Y = 4, Z= 49.

c.

Optimal solution is at X = 4, Y = 6, and Z = 56.

PTS: 1

TOP: Graphical solution

2. Solve the following problem graphically. Max

X + 2Y

s.t.

6X + 8Y ≤ 48 7X + 5Y ≥ 35 X, Y ≥ 0 Y integer

a.  b. c.

Graph the constraints for this problem. Indicate all feasible solutions. Find the optimal solution to the LP Relaxation. Round down to find a feasible integer  solution. Is this solution optimal? Find the optimal solution.

ANS: a.

The feasible region consists of the portions of the horizontal lines that lie within the area labeled F. R.

b.

The optimal relaxed solution is at X = 1.538, Y = 4.846 where Z = 11.231. The rounded solution is X = 1.538, Y = 4.

c.

The optimal solution is at X = 2.667, Y = 4, Z = 10.667.

PTS: 1

TOP: Graphical solution

3. Solve the following problem graphically. Min

6X + 11Y

s.t.

9X + 3Y ≥ 27 7X + 6Y ≥ 42 4X + 8Y ≥ 32 X, Y ≥ 0 and integer

a.  b. c.

Graph the constraints for this problem. Indicate all feasible solutions. Find the optimal solution to the LP Relaxation. Round up to find a feasible integer  solution. Is this solution optimal? Find the optimal solution.

ANS: a.

The feasible region is the set of integer points in the area labeled feasible region.

b.

The optimal relaxed solution is at X = 4.5, Y = 1.75, and Z = 46.25. The rounded solution is X = 5, Y = 2.

c.

The optimal solution is at X = 6, Y = 1, and Z = 47.

PTS: 1

TOP: Graphical solution

4. Consider a capital budgeting example with five projects from which to select. Let x i = 1 if project i is selected, 0 if not, for i = 1,...,5. Write the appropriate constraint(s) for each condition. Conditions are independent. a.  b. c. d. d.

Choose no fewer than three projects. If project 3 is chosen, project 4 must be chosen. If project 1 is chosen, project 5 must not be chosen. Projects cost 100, 200, 150, 75, and 300 respectively. The budget is 450. No more than two of projects 1, 2, and 3 can be chosen.

ANS: a.

x1 + x2 + x3 + x4 + x5 ≥ 3

b.

x3 − x4 ≤ 0

c.

x1 + x5 ≤ 1

d.

100x1 + 200x2 + 150x3 + 75x4 + 300x5 ≤ 450

e.

x1 + x2 + x3 ≤ 2

PTS: 1

TOP: Capital budgeting

5. Grush Consulting has five projects to consider. Each will require time in the next two quarters according to the table below. Project A B C

Time in first quarter 5 3 7

Time in second quarter 8 12 5

Revenue 12000 10000 15000

D E

2 15

3 1

5000 20000

Revenue from each project is also shown. Develop a model whose solution would maximize revenue, meet the time budget of 25 in the first quarter and 20 in the second quarter, and not do both projects C and D. ANS: Let

A = 1 if project A is selected, 0 otherwise; same for B, C, D, and E

Max

12000A + 10000B + 15000C + 5000D + 20000E

s.t.

5A + 3B + 7C + 2D + 15E 8A + 12B + 5C + 3D + 1E C+D ≤ 1

PTS: 1

≤ ≤

25 20

TOP: Capital budgeting

6. The Westfall Company has a contract to produce 10,000 garden hoses for a large discount chain. Westfall has four different machines that can produce this kind of hose. Because these machines are from different manufacturers and use differing technologies, their specifications are not the same.

Machine 1 2 3 4 a.  b. c. d.

Fixed Cost to Set Up Production Run 750 500 1000 300

Variable Cost Per Hose 1.25 1.50 1.00 2.00

Capacity 6000 7500 4000 5000

This problem requires two different kinds of decision variables. Clearly define each kind. The company wants to minimize total cost. Give the objective function. Give the constraints for the problem. Write a constraint to ensure that if machine 4 is used, machine 1 cannot be.

ANS: a.

Let

Pi = the number of hoses produced on machine i Ui = 1 if machine i is used, = 0 otherwise

b.

Min

750U1 + 500U2 + 1000U3 + 300U4 + 1.25P1 + 1.5P2 + P3 + 2P4

c.

P1 ≤ 6000U1 P2 ≤ 7500U2 P3 ≤ 4000U3 P4 ≤ 5000U4 P1 + P2 + P3 + P4 ≥ 10000

c.

U1 + U4 ≤ 1

PTS: 1

TOP: Fixed costs

7. Hansen Controls has been awarded a contract for a large number of control panels. To meet this demand, it will use its existing plants in San Diego and Houston, and consider new plants in Tulsa, St. Louis, and Portland. Finished control panels are to be shipped to Seattle, Denver, and Kansas City. Pertinent information is given in the table.

Sources

San Diego Houston Tulsa St. Louis Portland

Construction Cost

Shipping Cost to Destinatio n:

------350,000 200,000 480,000 Demand

Seattle 5 10 9 12 4 3,000

Capacity

Denver   7 8 4 6 10 8,000

Kansas City 8 6 3 2 11 9,000

2,500 2,500 10,000 10,000 10,000

Develop a model whose solution would reveal which plants to build and the optimal shipping schedule. ANS: Let

Pij = the number of panels shipped from source i to destination j Bi = 1 if plant i is built, = 0 otherwise (i = 3, 4, 5)

Min

350000B 3 + 200000B4 + 480000B 5 + 5P11 + 7P12 + 8P13 + 10P21 + 8P22 + 6P23 + 9P31 + 4P32 + 3P33 + 12P41 + 6P42 + 2P43 + 4P51 + 10P52 + 11P53

s.t.

P11 + P 12 + P13

2500

P21 + P22 + P23

2500

P31 + P32 + P33

10000B3

P41 + P42 + P43

10000B4

P51 + P52 + P53 ≤ 10000B5 P11 + P21 + P31 + P41 + P51 = 3000 P12 + P22 + P32 + P42 + P52 = 8000 P13 + P23 + P33 + P43 + P 53 = 9000 PTS: 1

TOP: Distribution system design

8. Simplon Manufacturing must decide on the processes to use to produce 1650 units. If machine 1 is used, its production will be between 300 and 1500 units. Machine 2 and/or machine 3 can be used only if machine 1's production is at least 1000 units. Machine 4 can be used with no restrictions.

Machine 1 2 3 4

Fixed cost 500 800 200 50

Variable cost 2.00 0.50 3.00 5.00

Minimum Production 300 500 100 any

Maximum Production 1500 1200 800 any

(HINT: Use an additional 0-1 variable to indicate when machines 2 and 3 can be used.) ANS: Let

Ui = the number of units made by machine i Si = 1 if machine i is used (requiring a set-up), = 0 otherwise K = 1 if machine 1 produces at least 1000 units, = 0 otherwise

Min

500S1 + 2U1 + 800S2 + 5U2 + 200S3 + 3U3 + 50S4 + 5U4

s.t.

U1 ≥ 300S1 U1 ≤ 1500S1 U1 ≥ 1000K  S2 ≤ K  S3 ≤ K  U 2 ≥ 500S2 U2 ≤ 1200S2 U3 ≥ 100S3 U3 ≤ 800S 3 U4 ≤ 1650S4 U1 + U2 + U3 + U4 = 1650

PTS: 1

TOP: Distribution system design

9. Your express package courier company is drawing up new zones for the location of drop boxes for  customers. The city has been divided into the seven zones shown below. You have targeted six  possible locations for drop boxes. The list of which drop boxes could be reached easily from each zone is listed below. Zone Downtown Financial Downtown Legal Retail South Retail East Manufacturing North Manufacturing East Corporate West

Can Be Served By Locations: 1, 2, 5, 6 2, 4, 5 1, 2, 4, 6 3, 4, 5 1, 2, 5 3, 4 1, 2, 6

Let xi = 1 if drop box location i is used, 0 otherwise. Develop a model to provide the smallest number  of locations yet make sure that each zone is covered by at least two boxes. ANS: Min

Σ

s.t.

x1 + x2 + x5 + x6

xi

x2 + x4 + x5

2

2

2

x1 + x2 + x4 + x6

x3 + x4 + x5

2

x1 + x 2 + x5

2

2

x3 + x4

2

x1 + x2 + x6 PTS: 1

TOP: Applications of integer linear programming

10. Consider the problem faced by a summer camp recreation director who is trying to choose activities for a rainy day. Information about possible choices is given in the table below.

Category

Activity

Art

1 − Painting 2 − Drawing 3 − Nature craft 4 − Rhythm band 5 − Relay races 6 − Basketball 7 − Internet 8 − Creative writing 9 − Games

Music Sports Computer

a.  b.

Time (minutes) 30 20 30 20 45 60 45 30 40

Popularity with Campers

Popularity with Counselors

4 5 3 5 2 1 1 4 1

2 2 1 5 1 3 1 3 2

Give a general definition of the variables necessary in this problem so that each activity can be considered for inclusion in the day's schedule. The popularity ratings are defined so that 1 is the most popular. If the objective is to keep the campers happy, what should the objective function be?

Write constraints for these restrictions: c. At most one art activity can be done. d. No more than two computer activities can be done. e. If basketball is chosen, then the music must be chosen. f. At least 120 minutes of activities must be selected. g. No more than 165 minutes of activities may be selected. h. To keep the staff happy, the counselor rating should be no higher than 10. ANS: a. b. c.

Let xi = 1 if activity i is chosen, 0 if not, for i = 1, ... , 9 Max 4x 1 + 5x2 + 3x3 + 5x4 + 2x5 + 1x6 + 1x7 + 4x8 + 1x9

d.

x7 + x8 + x9 ≤ 2

e.

x6 ≤ x4

f.

30x 1 + 20x2 + 30x3 + 20x4 + 45x5 + 60x6 + 45x7 + 30x8 + 40x9 ≥ 120

g.

30x1 + 20x2 + 30x3 + 20x4 + 45x5 + 60x6 + 45x7 + 30x8 + 40x9 ≤ 165

h.

2x1 + 2x2 + 1x3 + 5x4 + 1x5 + 3x6 + 1x7 + 3x8 + 2x9 ≤ 10

x1 + x2 + x3 ≤ 1

PTS: 1

TOP: Applications of integer programming

11. Tower Engineering Corporation is considering undertaking several proposed projects for the next fiscal year. The projects, the number of engineers and the number of support personnel required for  each project, and the expected profits for each project are summarized in the following table:

1 20 15 1.0

Engineers Required Support Personnel Required Profit (\$1,000,000s)

2 55 45 1.8

Project 3 4 47 38 50 40 2.0 1.5

5 90 70 3.6

6 63 70 2.2

Formulate an integer program that maximizes Tower's profit subject to the following management constraints: 1) 2) 3) 4) 5) 6)

Use no more than 175 engineers Use no more than 150 support personnel If either project 6 or project 4 is done, both must be done Project 2 can be done only if project 1 is done If project 5 is done, project 3 must not be done and vice versa No more than three projects are to be done.

ANS: Max

P1 + 1.8P2 + 2P3 + 1.5P4 + 3.6P5 + 2.2P6

s.t.

20P1 + 55P2 + 47P3 + 38P4 + 90P5 + 63P6

175

15P1 + 45P2 + 50P3 + 40P4 + 70P5 + 70P6

150

P4 −P6 = 0 P1 −P2 P3 + P5

≥ ≤

0 1

P1 + P2 + P3 + P4 + P5 + P6 Pi = 0 or 1 PTS: 1

3

TOP: Applications of integer programming