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Integer Linear Programming

Professor Ahmadi

Chapter 11Integer Linear Programming

- Types of Integer Linear Programming Models
- Graphical Solution for an All-Integer LP
- Spreadsheet Solution for an All-Integer LP
- Application Involving 0-l Variables
- Special 0-1 Constraints

Types of Integer Programming Models

- A linear program in which all the variables are

restricted to be integers is called an integer

linear program (ILP). - If only a subset of the variables are restricted

to be integers, the problem is called a mixed

integer linear program (MILP). - Binary variables are variables whose values are

restricted to be 0 or 1. If all variables are

restricted to be 0 or 1, the problem is called a

0-1 or binary integer program.

Example All-Integer LP

- Consider the following all-integer linear

program - Max 3x1 2x2
- s.t. 3x1 x2 lt 9
- x1 3x2 lt

7 - -x1 x2

lt 1 - x1, x2 gt 0

and integer

Example All-Integer LP

- LP Relaxation

x2

-x1 x2 lt 1

5

3x1 x2 lt 9

4

Max 3x1 2x2

3

LP Optimal (2.5, 1.5)

2

x1 3x2 lt 7

1

x1

1 2 3 4

5 6 7

Example All-Integer LP

- LP Relaxation
- Solving the problem as a linear program

ignoring the integer constraints, the optimal

solution to the linear program gives fractional

values for both x1 and x2. From the graph on the

previous slide, we see that the optimal solution

to the linear program is - x1 2.5, x2 1.5, z 10.5

Example All-Integer LP

- Rounding Up
- If we round up the fractional solution (x1

2.5, x2 1.5) to the LP relaxation problem, we

get x1 3 and x2 2. From the graph on the next

page, we see that this point lies outside the

feasible region, making this solution

infeasible.

Example All-Integer LP

- Rounded Up Solution

x2

-x1 x2 lt 1

5

3x1 x2 lt 9

4

Max 3x1 2x2

3

ILP Infeasible (3, 2)

2

LP Optimal (2.5, 1.5)

x1 3x2 lt 7

1

x1

1 2 3 4

5 6 7

Example All-Integer LP

- Rounding Down
- By rounding the optimal solution down to x1

2, x2 1, we see that this solution indeed is an

integer solution within the feasible region, and

substituting in the objective function, it gives

z 8. - We have found a feasible all-integer solution,

but have we found the optimal all-integer

solution? - ---------------------
- The answer is NO! The optimal solution is x1

3 and x2 0 giving z 9, as evidenced in the

next two slides.

Example All-Integer LP

- Complete Enumeration of Feasible ILP Solutions
- There are eight feasible integer solutions to

this problem - x1 x2 z
- 1. 0 0 0
- 2. 1 0 3
- 3. 2 0 6
- 4. 3 0 9

optimal solution - 5. 0 1 2
- 6. 1 1 5
- 7. 2 1 8
- 8. 1 2 7

Example All-Integer LP

x2

5

-x1 x2 lt 1

3x1 x2 lt 9

4

Max 3x1 2x2

3

2

ILP Optimal (3, 0)

x1 3x2 lt 7

1

x1

1 2 3 4

5 6 7

Special 0-1 Constraints

- When xi and and xj represent binary variables

designating whether projects i and j have been

completed, the following special constraints may

be formulated - At most k out of n projects will be completed
- Sxj lt k
- Project j is conditional on project i
- xj - xi lt 0
- Project i is a co-requisite for project j
- xj - xi 0
- Projects i and j are mutually exclusive
- xi xj lt 1

Example Chattanooga Electronics

- Chattanooga Electronics, Inc. is planning to

expand its operations into other electronic

equipment. The company has identified seven new

product lines it can carry. Relevant information

about each line follows - Initial

Floor Space Exp. Rate - Product Line Investment

(Sq.Ft.) of Return - 1. Digital TVs 6,000 125

8.1 - 2. HD TVs 12,000

150 9.0 - 3. Large Screen TVs 20,000

200 11.0 - 4. DVDs 14,000

40 10.2 - 5. DVD/RWs 15,000

40 10.5 - 6. Video Games 2,000

20 14.1 - 7. PC Computers 32,000 100

13.2

Chattanooga Electronics - Continued

- Define the Decision Variables
- xj 1 if product line j is introduced
- 0 otherwise.
- Where the Product lines are defined as
- (X1) Digital TVs
- (X2) HD TVs
- (X3) Large Screen TVs
- (X4) DVDs
- (X5) DVD/RWs
- (X6) Video Games
- (X7) Computers

Example Chattanooga Electronics

- Chattanooga Electronics has decided that
- they should not stock large screen TVs (X3)

unless they stock either digital (X1) or HD TVs

(X2). - also, they will not stock both types of DVDs (X4

X5). - they will stock video games (X6) only if they

stock HD TVs (X2). - the company wishes to introduce at least three

new product lines. - If the company has 45,000 to invest and 420 sq.

ft. of floor space available, formulate an

integer linear program for Chattanooga

Electronics to maximize its overall expected rate

of return.

Example Chattanooga Electronics

- Define the Objective Function
- Maximize total overall expected return
- Max .081(6000)x1 .09(12000)x2

.11(20000)x3 - .102(14000)x4 .105(15000)x5

.141(2000)x6 - .132(32000)x7 or
- Max 486x1 1080x2 2200x3 1428x4 1575x5
- 282x6 4224x7

Example Chattanooga Electronics

- Define the Constraints
- 1) Money
- 60x1 12x2 20x3 14x4 15x5 2x6

32x7 lt 45 - 2) Space
- 125x1 150x2 200x3 40x4 40x5

20x6 100x7 lt 420

Example Chattanooga Electronics

- Define the Constraints (continued)
- 3) Stock large screen TVs (X3) only if stock

digital (X2) or HD (X2) - 4) Do not stock both types of DVDs (X4 X5)
- 5) Stock video games (X6) only if they stock HD

TV's (X2) - 6) At least 3 new lines
- 7) Variables are 0 or 1
- xj 0 or 1 for j 1, , , 7

Example Mos Programming

- Mo's Programming has five idle Programmers and

four custom Programs to develop. The estimated

time (in hours) it would take each Programmer to

write each Program is listed below. (An 'X' in

the table indicates an unacceptable

Programmer-Program assignment.) -

Programmer - Program 1 2

3 4 5 - Java 19 23 20

21 18 - C 11 14

X 12 10 - Assembler 12 8

11 X 9 - Pascal X 20

20 18 21

Example Mos Programming

- Formulate an integer program for determining

the Programmer-Program assignments that minimize

the total estimated time spent writing the four

Programs. No Programmer is to be assigned more

than one Program and each Program is to be worked

on by only one Programmer. - --------------------
- This problem can be formulated as a 0-1 integer

program. The LP solution to this problem will

automatically be integer (0-1).

Example Mos Programming

- Define the decision variables
- xij 1 if Program i is assigned to

Programmer j - 0 otherwise.
- Number of decision variables
- (number of Programs)(number of Programmers)
- - (number of unacceptable assignments)
- 4(5) - 3 17
- Define the objective function
- Minimize total time spent writing Programs
- Min 19x11 23x12 20x13 21x14 18x15

11x21 - 14x22 12x24 10x25 12x31 8x32

11x33 - 9x35 20x42 20x43 18x44 21x45

Example Mos Programming

- Define the Constraints
- Exactly one Programmer per Program
- 1) x11 x12 x13 x14 x15 1
- 2) x21 x22 x24 x25 1
- 3) x31 x32 x33 x35 1
- 4) x42 x43 x44 x45 1

Example Mos Programming

- Define the Constraints (continued)
- No more than one Program per Programmer
- 5) x11 x21 x31 lt 1
- 6) x21 x22 x23 x24 lt 1
- 7) x31 x33 x34 lt 1
- 8) x41 x42 x44 lt 1
- 9) x51 x52 x53 x54 lt 1
- Non-negativity xij gt 0 for i 1, . . ,4

and j 1, . . ,5

The End of Chapter 6

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