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1. Graphical method example ( Enter your problem )
  1. Elements of LPP and Definition
  2. Algorithm & Example-1
  3. Maximization Example-2
  4. Maximization Example-3
  5. Minimization Example-4
  6. Minimization Example-5
  7. Mixed constraints Example-6
  8. Mixed constraints Example-7
  9. Multiple optimal solution example
  10. Unbounded solution example
  11. Infeasible solution example
Other related methods
  1. Formulate linear programming model
  2. Graphical method
  3. Simplex method (BigM method)
  4. Two-Phase method
  5. Primal to dual conversion
  6. Dual simplex method
  7. Integer simplex method
  8. Branch and Bound method
  9. 0-1 Integer programming problem
  10. Revised Simplex method

5. Minimization Example-4
(Previous example)
7. Mixed constraints Example-6
(Next example)

6. Minimization Example-5





Find solution using graphical method
MIN z = 600x1 + 400x2
subject to
3x1 + 3x2 >= 40
3x1 + x2 >= 40
2x1 + 5x2 >= 44
and x1,x2 >= 0


Solution:
Problem is
MIN `z_x``=````600``x_1`` + ``400``x_2`
subject to
```3``x_1`` + ``3``x_2``40`
```3``x_1`` + ````x_2``40`
```2``x_1`` + ``5``x_2``44`
and `x_1,x_2 >= 0; `




Hint to draw constraints

1. To draw constraint `color{red}{3x_1+3x_2>=40 ->(1)}`

Treat it as `color{red}{3x_1+3x_2=40}`

When `x_1=0` then `x_2=?`

`=>3(0)+3x_2=40`

`=>3x_2=40`

`=>x_2=(40)/(3)=13.33`

When `x_2=0` then `x_1=?`

`=>3x_1+3(0)=40`

`=>3x_1=40`

`=>x_1=(40)/(3)=13.33`

`x_1`013.33
`x_2`13.330




2. To draw constraint `color{green}{3x_1+x_2>=40 ->(2)}`

Treat it as `color{green}{3x_1+x_2=40}`

When `x_1=0` then `x_2=?`

`=>3(0)+x_2=40`

`=>x_2=40`

When `x_2=0` then `x_1=?`

`=>3x_1+(0)=40`

`=>3x_1=40`

`=>x_1=(40)/(3)=13.33`

`x_1`013.33
`x_2`400




3. To draw constraint `color{blue}{2x_1+5x_2>=44 ->(3)}`

Treat it as `color{blue}{2x_1+5x_2=44}`

When `x_1=0` then `x_2=?`

`=>2(0)+5x_2=44`

`=>5x_2=44`

`=>x_2=(44)/(5)=8.8`

When `x_2=0` then `x_1=?`

`=>2x_1+5(0)=44`

`=>2x_1=44`

`=>x_1=(44)/(2)=22`

`x_1`022
`x_2`8.80









The value of the objective function at each of these extreme points is as follows:
Extreme Point
Coordinates
(`x_1`,`x_2`)
Lines through Extreme PointObjective function value
`z=600x_1 + 400x_2`
`color{red}{A(0,40)}``color{green}{2->3x_1+x_2>=40}`
`color{black}{4->x_1>=0}`
`600(0)+400(40)=16000`
`color{green}{B(12,4)}``color{green}{2->3x_1+x_2>=40}`
`color{blue}{3->2x_1+5x_2>=44}`
`600(12)+400(4)=8800`
`color{blue}{C(22,0)}``color{blue}{3->2x_1+5x_2>=44}`
`color{black}{5->x_2>=0}`
`600(22)+400(0)=13200`


The miniimum value of the objective function `z=8800` occurs at the extreme point `(12,4)`.

Hence, the optimal solution to the given LP problem is : `x_1=12, x_2=4` and min `z=8800`.


This material is intended as a summary. Use your textbook for detail explanation.
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5. Minimization Example-4
(Previous example)
7. Mixed constraints Example-6
(Next example)





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