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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

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

7. Mixed constraints Example-6





Find solution using graphical method
MIN z = 200x1 + 400x2
subject to
x1 + x2 >= 20
x1 + 3x2 >= 40
x1 + 2x2 <= 35
and x1,x2 >= 0


Solution:
Problem is
MIN `z_x``=````200``x_1`` + ``400``x_2`
subject to
`````x_1`` + ````x_2``20`
`````x_1`` + ``3``x_2``40`
`````x_1`` + ``2``x_2``35`
and `x_1,x_2 >= 0; `




Hint to draw constraints

1. To draw constraint `color{red}{x_1+x_2>=20 ->(1)}`

Treat it as `color{red}{x_1+x_2=20}`

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

`=>(0)+x_2=20`

`=>x_2=20`

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

`=>x_1+(0)=20`

`=>x_1=20`

`x_1`020
`x_2`200




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

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

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

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

`=>3x_2=40`

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

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

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

`=>x_1=40`

`x_1`040
`x_2`13.330




3. To draw constraint `color{blue}{x_1+2x_2<=35 ->(3)}`

Treat it as `color{blue}{x_1+2x_2=35}`

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

`=>(0)+2x_2=35`

`=>2x_2=35`

`=>x_2=(35)/(2)=17.5`

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

`=>x_1+2(0)=35`

`=>x_1=35`

`x_1`035
`x_2`17.50









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=200x_1 + 400x_2`
`color{red}{A(5,15)}``color{red}{1->x_1+x_2>=20}`
`color{blue}{3->x_1+2x_2<=35}`
`200(5)+400(15)=7000`
`color{green}{B(25,5)}``color{green}{2->x_1+3x_2>=40}`
`color{blue}{3->x_1+2x_2<=35}`
`200(25)+400(5)=7000`
`color{blue}{C(10,10)}``color{red}{1->x_1+x_2>=20}`
`color{green}{2->x_1+3x_2>=40}`
`200(10)+400(10)=6000`


The miniimum value of the objective function `z=6000` occurs at the extreme point `(10,10)`.

Hence, the optimal solution to the given LP problem is : `x_1=10, x_2=10` and min `z=6000`.


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





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