lecture 9 duality

40
Lecture 9 Duality 09-13-2009

Upload: vanliem

Post on 12-Feb-2017

233 views

Category:

Documents


1 download

TRANSCRIPT

Page 1: Lecture 9 Duality

Lecture 9Duality

09-13-2009

Page 2: Lecture 9 Duality

DualityEvery LP has its Dual.

Primal(Ex 4.1-1)

max z = 5x1 + 12x2 + 4x3s.t. x1 + 2x2 + x3 ≤ 10

2x1 − x2 + 3x3 = 8x1, x2, x3 ≥ 0.

Dual

min w = 10y1 + 8y2s.t. y1 + 2y2 ≥ 5

2y1 − y2 ≥ 12y1 + 3y2 ≥ 4y1 ≥ 0

Page 3: Lecture 9 Duality

Primal Optimal Solution

Primal

max z = 5x1 + 12x2 + 4x3s.t. x1 + 2x2 + x3 ≤ 10

2x1 − x2 + 3x3 = 8x1, x2, x3 ≥ 0.

(x∗1 , x∗2 , x∗3 ) = (5.2, 2.4, 0).

z∗ = 54.8.

Page 4: Lecture 9 Duality

Dual Optimal Solution

Dual

min w = 10y1 + 8y2s.t. y1 + 2y2 ≥ 5

2y1 − y2 ≥ 12y1 + 3y2 ≥ 4y1 ≥ 0

(y1, y2) = (5.8,−0.4).

w∗ = 54.8.

Page 5: Lecture 9 Duality

DualityDual can be constructed from its primal.

Primal(Ex 4.1-1)

max z = 5x1 + 12x2 + 4x3s.t. x1 + 2x2 + x3 ≤ 10

2x1 − x2 + 3x3 = 8x1, x2, x3 ≥ 0.

Dual

min w = 10y1 + 8y2s.t. y1 + 2y2 ≥ 5

2y1 − y2 ≥ 12y1 + 3y2 ≥ 4y1 ≥ 0

Page 6: Lecture 9 Duality

Strong Duality

Page 7: Lecture 9 Duality

Economic Interpretation

Page 8: Lecture 9 Duality

Economic Interpretation

Ex 4.3-2TOYCO assembles three types of toys: trains, trucks, and carsusing three operations. Available assembly times for the threeoperations are 430, 460 and 420 minutes per day, respectively, andthe revenues per toy train, truck, and car are $3, $2 and $5,respectively. The assembly times per train for the three operationsare 1, 3 and 1 minutes, respectively. The corresponding times pertruck and per car are (2, 0, 4) and (1, 2, 0) minutes (a zero timeindicates that the operations is not used).

Page 9: Lecture 9 Duality

Economic Interpretation

Primal

max z = 3x1 + 2x2 + 5x3s.t. x1 + 2x2 + x3 ≤ 430

3x1 + 2x3 ≤ 460x1 + 4x2 ≤ 420x1, x2, x3 ≥ 0.

Optimal solution:z∗ = $1350x∗ = (0, 100, 230).

Page 10: Lecture 9 Duality

Economic Interpretation

Dual side of the storyTOYCO’s available assembly times for the three operations are430, 460 and 420 minutes per day. You want to buy all assemblytimes from TOYCO, by paying prices y1, y2, y3 per minute,respectively. You must pay enough for the assembly times becauseotherwise TOYCO would choose not to sell to you, they wouldproduce on their own and profit from it.TOYCO’s revenues per toy train, truck, and car are $3, $2 and $5,respectively. The assembly times per train for the three operationsare 1, 3 and 1 minutes, respectively. The corresponding times pertruck and per car are (2, 0, 4) and (1, 2, 0) minutes.

Page 11: Lecture 9 Duality

Economic Interpretation

Dual

max w = 430y1 + 460y2 + 420y3s.t. y1 + 3y2 + y3 ≥ 3

2y1 + 4y3 ≥ 2y1 + 2y2 ≥ 5y1, y2, y3 ≥ 0.

Optimal solution:w∗ = $1350y∗ = (1, 2, 0).

Page 12: Lecture 9 Duality

Economic Interpretation

Primal Dualmax z = 3x1 + 2x2 + 5x3 min w = 430y1 + 460y2 + 420y3

s.t. x1 + 2x2 + x3 ≤ 430 s.t. y1 + 3y2 + y3 ≥ 33x1 + 2x3 ≤ 460 2y1 + 4y3 ≥ 2x1 + 4x2 ≤ 420 y1 + 2y2 ≥ 5x1, x2, x3 ≥ 0. y1, y2, y3 ≥ 0.

z∗ = $1350 w∗ = $1350x∗ = (0, 100, 230). y∗ = (1, 2, 0).

Page 13: Lecture 9 Duality

Constructing Dual LP

Page 14: Lecture 9 Duality

Constructing Dual LP

I Transpose all coefficients.I Flip max/min.

Primal Dualmax z = 3x1 + 2x2 + 5x3 min w = 430y1 + 460y2 + 420y3

s.t. x1 + 2x2 + x3 ≤ 430 s.t. y1 + 3y2 + y3 (?) 33x1 + 2x3 ≤ 460 2y1 + 4y3 (?) 2x1 + 4x2 ≤ 420 y1 + 2y2 (?) 5x1, x2, x3 ≥ 0. y1, y2, y3 (?) 0.

Page 15: Lecture 9 Duality

Constructing Dual LP

Constraints Variablesmax min≥ ⇔ ≤ 0≤ ⇔ ≥ 0= ⇔ Unrestrictedmin max≥ ⇔ ≥ 0≤ ⇔ ≤ 0= ⇔ Unrestricted

Page 16: Lecture 9 Duality

Constructing Dual LP

TOYCO’s example: primal

max z = 3x1 + 2x2 + 5x3s.t. x1 + 2x2 + x3 ≤ 430

3x1 + 2x3 ≤ 460x1 + 4x2 ≤ 420x1, x2, x3 ≥ 0.

Page 17: Lecture 9 Duality

Constructing Dual LP

TOYCO’s example: dual

max w = 430y1 + 460y2 + 420y3s.t. y1 + 3y2 + y3 ≥ 3

2y1 + 4y3 ≥ 2y1 + 2y2 ≥ 5y1, y2, y3 ≥ 0.

Page 18: Lecture 9 Duality

QuizMaximization, all variables nonnegative.

Basic x1 x2 x3 x4 x5 x6 Solutionz 7 0 a 0 0 0 210x5 2 0 c 3 1 0 9x2 −3 1 d −1 0 0 bx6 1 0 e 2 0 1 8

I (a) Assume b ≥ 0. What are the basic variables? What is thecurrent objective value? What is the current solution?

I (b) Given a = 2, b = 3, is the tableau optimal?I (c) Given a = 2, b = 3, find another optimal solution.I (d) For what values of a, b, c, d , e is the current table optimal?I (e) If a = −1, b ≥ 0, c, d , e ≤ 0, what can you conclude

about the optimal value?I (f) Give a possible value of (a, b, c, d , e) so that x3 would

replace x2 in the basis.

Page 19: Lecture 9 Duality

You can Obtain an optimal tableau by simply knowing two things:I Initial table.I Optimal basic variables.

Example: Initial Table

Basic x1 x2 s1 s2 s3 s4 RHSz −5 −4 0 0 0 0 0s1 6 4 1 0 0 0 24s2 1 2 0 1 0 0 6s3 −1 1 0 0 1 0 1s4 0 1 0 0 0 1 2

Page 20: Lecture 9 Duality

Example: Intermediate Table

Basic x1 x2 s1 s2 s3 s4 RHSz 0 −2/3 5/6 0 0 0 20x1 1 2/3 1/6 0 0 0 4s2 0 4/3 −1/6 1 0 0 2s3 0 5/3 1/6 0 1 0 5s4 0 1 0 0 0 1 2

There can be many intermediate tables.

Page 21: Lecture 9 Duality

Example: Final(Optimal) Table

Basic x1 x2 s1 s2 s3 s4 RHSz 0 0 3/4 1/2 0 0 21x1 1 0 1/4 −1/2 0 0 3x2 0 1 −1/8 3/4 0 0 3/2s3 0 0 3/8 −5/4 1 0 5/2s4 0 0 1/8 −3/4 0 1 1/2

Page 22: Lecture 9 Duality

Constructing Dual LP

Page 23: Lecture 9 Duality

Constructing Dual LP

Constraints Variablesmax min≥ ⇔ ≤ 0≤ ⇔ ≥ 0= ⇔ Unrestrictedmin max≥ ⇔ ≥ 0≤ ⇔ ≤ 0= ⇔ Unrestricted

Page 24: Lecture 9 Duality

Constructing Dual LP

Primal(Ex 4.1-1)

max z = 5x1 + 12x2 + 4x3s.t. x1 + 2x2 + x3 ≤ 10

2x1 − x2 + 3x3 = 8x1, x2, x3 ≥ 0.

Page 25: Lecture 9 Duality

Constructing Dual LP

Dual(Ex 4.1-1)

min w = 10y1 + 8y2s.t. y1 + 2y2 ≥ 5

2y1 − y2 ≥ 12y1 + 3y2 ≥ 4y1 ≥ 0

Page 26: Lecture 9 Duality

Constructing Dual LP from standard form

Standard form:I Constraints: =.I Variables: ≥ 0.

Dual of standard form:I Dual variables: unrestricted.I Dual Constraints:

I ≥ 0 if dual is min.I ≤ 0 if dual is max.

Page 27: Lecture 9 Duality

Constructing Dual LP from standard form

Ex 4.1-1

max z = 5x1 + 12x2 + 4x3s.t. x1 + 2x2 + x3 ≤ 10

2x1 − x2 + 3x3 = 8x1, x2, x3 ≥ 0.

Page 28: Lecture 9 Duality

Constructing Dual LP from standard form

Ex 4.1-1, standard form

max z = 5x1 + 12x2 + 4x3s.t. x1 + 2x2 + x3 + x4 = 10

2x1 − x2 + 3x3 = 8x1, · · · , x4 ≥ 0.

Page 29: Lecture 9 Duality

Constructing Dual LP from standard form

Dual of Ex 4.1-1

min w = 10y1 + 8y2s.t. y1 + 2y2 ≥ 5

2y1 − y2 ≥ 12y1 + 3y2 ≥ 4y1 ≥ 0

Page 30: Lecture 9 Duality

Constructing Dual LP from standard form

Primal of Ex 4.1-2

min z = 15x1 + 12x2s.t. x1 + 2x2 ≥ 3

2x1 − 4x2 ≤ 5x1, x2 ≥ 0.

Page 31: Lecture 9 Duality

Constructing Dual LP from standard form

Ex 4.1-2, standard form

min z = 15x1 + 12x2s.t. x1 + 2x2 − x3 = 3

2x1 − 4x2 + x4 = 5x1, · · · , x4 ≥ 0.

Page 32: Lecture 9 Duality

Constructing Dual LP from standard form

Dual of Ex 4.1-2

min w = 3y1 + 5y2s.t. y1 + 2y2 ≤ 15

2y1 − 4y2 ≤ 12y1 ≥ 0y2 ≤ 0.

Page 33: Lecture 9 Duality

Constructing Dual LP from standard form

Primal of Ex 4.1-3

max z = 5x1 + 6x2s.t. x1 + 2x2 = 5

−x1 + 5x2 ≥ 34x1 + 7x2 ≤ 8x1 unrestrictedx2 ≥ 0.

Page 34: Lecture 9 Duality

Constructing Dual LP from standard form

Substitute x1 = x+1 − x−1 :

Ex 4.1-3, standard form

max z = 5x+1 − 5x−1 + 6x2

s.t. x+1 − x−1 + 2x2 = 5−x+

1 + x−1 + 5x2 − x3 = 34x+

1 − 4x−1 + 7x2 + x4 = 8x+

1 , x−1 , x2, x3, x4 ≥ 0.

Page 35: Lecture 9 Duality

Constructing Dual LP from standard form

Dual of Ex 4.1-3

min w = 5y1 + 3y2 + 8y3s.t. y1 − y2 + 4y3 = 5

2y1 + 5y2 + 7y3 ≥ 6y1 unrestrictedy2 ≤ 0y3 ≥ 0.

Page 36: Lecture 9 Duality

Optimal Dual Solution

Primal and Dual solution meet at optimality. How do youdetermine the optimal dual variables when you solved the primal?

Ex 4.2-1

max z = 5x1 + 12x2 + 4x3s.t. x1 + 2x2 + x3 ≤ 10

2x1 − x2 + 3x3 = 8x1, x2, x3 ≥ 0.

Page 37: Lecture 9 Duality

Optimal Dual Solution

Primal Dualmax z = 5x1 + 12x2 + 4x3 −MR min w = 10y1 + 8y2

s.t. x1 + 2x2 + x3 + x4 = 10 s.t. y1 + 2y2 ≥ 52x1 − x2 + 3x3 + R = 8 2y1 − y2 ≥ 12x1, · · · , x4,R ≥ 0 y1 + 3y2 ≥ 4

y1 ≥ 0y2 ≥ −M.

Page 38: Lecture 9 Duality

Optimal Dual Solution

Initial Table

Basic x1 x2 x3 x4 R RHSz −5 −12 −4 0 M 0

x4 1 2 1 1 0 10R 2 −1 3 0 1 8

Optimal Table

Basic x1 x2 x3 x4 R RHSz 0 0 3

5295 −2

5 + M 5445

x2 0 1 −15

25 −1

5125

x1 1 0 75

15

25

265

Page 39: Lecture 9 Duality

Method 1

Optimal value of dual variable yi =

Optimal primal z-coefficient of starting basic variable xi

+

Original objective coefficient of xi .(y1y2

)=

(29/5

−2/5 + M

)+

(0−M

)=

(29/5−2/5

)

I Distinguish between starting basis and optimal basis.I Distinguish between z-coefficient and objective coefficient.

Page 40: Lecture 9 Duality

Method 2Optimal value of dual variables = Row vectors of

original objective coefficientsof optimal primal basic variables

× (Optimal primal

inverse

)

(y1 y2

)=

(12 5

)×(

2 1−1 2

)−1

=(12 5

)×(2/5 −1/51/5 2/5

)=

(29/5 −2/5

)

I (·)−1 means matrix inversion.