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Linear programming using the simplex method

Date post: 09-Jun-2015
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Linear Programming Application Using Matrices
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Page 1: Linear programming using the simplex method

Linear ProgrammingApplication Using Matrices

Page 2: Linear programming using the simplex method

LP History LP first developed by Leonid

Kontorovich in 1939 to plan

expenditures and returns

during WW 2.

It was kept secret until 1947. Revealed after publication of Dantzig's Simplex Algorithm.

Page 3: Linear programming using the simplex method

To maximize:

f = c1x+c2y+c3z ...

Subjected to constraints :0<= ax + by + cz + ... <= P10<= dx + ey + fz + ... <= P2...

Application

STANDARD FORM(x >= 0 y >= 0 ...)

Page 4: Linear programming using the simplex method

To minimize:

f = c1x+c2y+c3z ...

We maximize:

g = -f = -(c1x+c2y+c3z ...)

Page 5: Linear programming using the simplex method

1. L acres of land2. Two crops to be planted : potato and ladyfinger3. Budget :

a. F for fertilisersb. P for pesticides

4. Crops has the following requirements/ returns per acre per season:

Crop Plantation Problem

Crop Water Manure Pesticide Profit

Potato W1 M1 P1 R1

Ladyfinger W2 M2 P2 R2

Page 6: Linear programming using the simplex method

AimDistribute land to Maximize profit.

Page 7: Linear programming using the simplex method

Simplex Algorithmx = Potato area y = Ladyfinger area

Constraints :1. x , y >= 0 (non negative)2. x + y <= L (land)3. 0<= xP1 + yP2 <= P (Pesticide)4. 0<= xM1 + yM2 <= M (Manure)

Aim : To Maximize Profit (f)f = xR1 + yR2

Page 8: Linear programming using the simplex method

Simplex MethodIntroduce slack variables & remove inequalities

Constraints

1. x + y <= L x + y + u = L2. xP1 + yP2 <= P xP1 + yP2 + v = P3. xM1 + yM2 <= M xM1 + yM2 + w = M

-xR1 - yR2 + f = 0

Page 9: Linear programming using the simplex method

For solution purpose, let :P1 = 10, P2 = 12, P = 18 | L = 6M1 = 5, M2 = 7, M = 10 | R1 = 3 ; R2 = 6

Constraints Slacks Values

Page 10: Linear programming using the simplex method

Algorithm1) In constraints, select the column with min. negative value at bottom

Constraints

-6 < -

3

Page 11: Linear programming using the simplex method

Algorithm2) Pivot element in the selected row is min(value/respected value)

= 7

Page 12: Linear programming using the simplex method

Algorithm3) Apply row operations to make pivot element = 1 and all other elements in that column = 0

1. R3 = R3 + R42. R1 = R1 - R33. R2 = R2 - 2R4

Page 13: Linear programming using the simplex method

Algorithm4) Repeat until all elements in the last row of constraints become >=0

Page 14: Linear programming using the simplex method

SolutionThe last element of last row is the optimal solution.

Page 15: Linear programming using the simplex method

Determining x,yFrom final matrix we get the following equations :

1. 0.28x + 1u -0.14w = 4.572. 10x + 1v = 183. 0.7x + 1y + 0.14w = 1.424. 1.28x + 0.85w + 1f = 8.57

Therefore f is 8.57 (max) when x = 0, w = 0y = 1.42 (using x,w,(3))

Page 16: Linear programming using the simplex method

Graphical Interpretationhttp://fooplot.com/plot/ipyhavtwvc

Page 17: Linear programming using the simplex method

Simplex method mechanically traverses every corner point starting with (0,0)

Page 18: Linear programming using the simplex method
Page 20: Linear programming using the simplex method

1. Matrix images : Roger's Online Equation Editor http://rogercortesi.com/eqn/

2. Title font : Amatic Sc by Vernon Adams https://plus.google.com/107807505287232434305/posts

Credits

Page 21: Linear programming using the simplex method

Thank You


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