Operations Research

GRAPHICAL METHOD

wine production

Objective Function:

Maximize 50X_{1}+120X_{2}

Constraints:

  • X_{1}+X_{2}\leq 110
  • 100X_{1}+200X_{2}\leq 10.000
  • 10X_{1}+30X_{2}\leq 1.200
  • X_{1},X_{2}\geq 0

 

SIMPLEX METHOD

Maximize z = 3x1 + 2x2

subject to:

-x1 + 2x2 ≤ 4
3x1 + 2x≤ 14
x1 – x2 ≤ 3

x1, x2 ≥ 0

Converting inequalities to equalities

-x1 + 2x2 + x3 = 4
3x1 + 2x2 + x4 = 14
x1 – x2 + x5 = 3
x1, x2, x3, x4, x5 ≥ 0

Where x3, x4 and x5 are slack variables.

Maximize z = 3x1 + 2x2 + 0x3 + 0x4 + 0x5

x1 = 0, x2 = 0, z = 0
x3 = 4, x4 = 14, x5 = 3

Simplex Method Examples, Operations Research

a11 = -1, a12 = 2, a13 = 1, a14 = 0, a15 = 0, b1 = 4
a21 = 3, a22 = 2, a23 = 0, a24 = 1, a25 = 0, b2 = 14
a31= 1, a32 = -1, a33 = 0, a34 = 0, a35 = 1, b= 3

Calculating values for the index row (z– cj)

z– c1 = (0 X (-1) + 0 X 3 + 0 X 1) – 3 = -3
z– c2 = (0 X 2 + 0 X 2 + 0 X (-1)) – 2 = -2
z– c3 = (0 X 1 + 0 X 0 + 0 X 0) – 0 = 0
z– c4 = (0 X 0 + 0 X 1 + 0 X 0) – 0 = 0
z– c5 = (0 X 0 + 0 X 0 + 0 X 1) – 0 = 0

 

Calculating values for table 2

x3 row

a11 = -1 – 1 X ((-1)/1) = 0
a12 = 2 – (-1) X ((-1)/1) = 1
a13 = 1 – 0 X ((-1)/1) = 1
a14 = 0 – 0 X ((-1)/1) = 0
a15 = 0 – 1 X ((-1)/1) = 1
b1 = 4 – 3 X ((-1)/1) = 7

x4 row

a21 = 3 – 1 X (3/1) = 0
a22 = 2 – (-1) X (3/1) = 5
a23 = 0 – 0 X (3/1) = 0
a24 = 1 – 0 X (3/1) = 1
a25 = 0 – 1 X (3/1) = -3
b2 = 14 – 3 X (3/1) = 5

x1 row

a31 = 1/1 = 1
a32 = -1/1 = -1
a33 = 0/1 = 0
a34 = 0/1 = 0
a35 = 1/1 = 1
b3 = 3/1 = 3

Table 2

cj 3 2 0 0 0
cB Basic variables
B
x1 x2 x3 x4 x5 Solution values
b (= XB)
0 x3 0 1 1 0 1 7
0 x4 0 5 0 1 -3 5
3 x1 1 -1 0 0 1 3
zj-cj 0 -5 0 0 3

(z– cj)

z– c1 = (0 X 0 + 0 X 0 + 3 X 1) – 3 = 0
z– c2 = (0 X 1 + 0 X 5 + 3 X (-1)) – 2 = -5
z– c3 = (0 X 1 + 0 X 0 + 3 X 0) – 0 = 0
z– c4 = (0 X 0 + 0 X 1 + 3 X 0) – 0 = 0
z– c5 = (0 X 1 + 0 X (-3) + 3 X 1) – 0 = 3

 

a11 = 0 – 0 X (1/5) = 0
a12 = 1 – 5 X (1/5) = 0
a13 = 1 – 0 X (1/5) = 1
a14 = 0 – 1 X (1/5) = -1/5
a15 = 1 – (-3) X (1/5) = 8/5
b1 = 7 – 5 X (1/5) = 6

x2 row

a21 = 0/5 = 0
a22 = 5/5 = 1
a23 = 0/5 = 0
a24 = 1/5
a25 = -3/5
b2 = 5/5 = 1

x1 row

a31 = 1 – 0 X (-1/5) = 1
a32 = -1 – 5 X (-1/5) = 0
a33 = 0 – 0 X (-1/5) = 0
a34 = 0 – 1 X (-1/5) = 1/5
a35 = 1 – (-3) X (-1/5) = 2/5
b3 = 3 – 5 X (-1/5) = 4

cj 3 2 0 0 0
cB Basic variables
B
x1 x2 x3 x4 x5 Solution values
b (= XB)
0 x3 0 0 1 -1/5 8/5 6
2 x2 0 1 0 1/5 -3/5 1
3 x1 1 0 0 1/5 2/5 4
zj-cj 0 0 0 1 0

Since all the values of zj – cj are positive, this is the optimal solution.
x= 4, x2 = 1
z = 3 X 4 + 2 X 1 = 14.

DUALITY AND SENSITIVITY ANALYSIS.

Forming Dual when Primal is in Canonical Form:

Forming Dual when Primal is in Canonical Form

Constraint Relationships of the Primal and Dual

Duality in Linear Programme

Duality in Linear Programme

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Duality in Linear Programme

Duality in Linear Programme

TRANSPORTATION MODEL