Use the simplex method to obtain the optimal solution of the following linear programming model
ššš„šššš§š š = 35š„1 + 50š„2
š š¢ššššš” š”š
3š„1 + š„2 ā¤ 30
š„1 + 2š„2 ā¤ 15
4š„1 + 4š„2 ā¤ 40 š„1,
š„2 ā„ 0
Problem is
MaxĀ "Z=35x_1+50x_2" subject to:
"3x_1+x_2\u226430"
"x_1+2x_2\u226415"
"4x_1+4x_2\u226440"
andĀ "x_1,x_2\u22650" ;
The problem is converted to canonical form by adding slack, surplus and artificial variables as appropiate
1. As the constraint-1 is of type 'ā¤' we should add slack variableĀ "S_1"
2. As the constraint-2 is of type 'ā¤' we should add slack variableĀ "S_2"
3. As the constraint-3 is of type 'ā¤' we should add slack variableĀ "S_3"
After introducing slack variables
"Max \\ Z=35x_1+50x_2+0S_1+0S_2+0S_3"
subject to:
"3x_1+x_2+S_1=30\\\\\nx_1+2x_2+S_2=15\\\\\n4x_1+4x_2+S_3=40\\\\"
andĀ "x_1,x_2,S_1,S_2,S_3\u22650"
Negative minimumĀ Zj-CjĀ isĀ -50Ā and its column index isĀ 2. So,Ā the entering variable isĀ "x_2" .
Minimum ratio isĀ 7.5Ā and its row index isĀ 2. So,Ā the leaving basis variable isĀ "S_2" .
ā“Ā The pivot element isĀ 2.
EnteringĀ ="x_2" , DepartingĀ ="S_2" , Key ElementĀ =2
Negative minimumĀ Zj-CjĀ isĀ -10Ā and its column index isĀ 1. So,Ā the entering variable isĀ "x_1" .
Minimum ratio isĀ 5Ā and its row index isĀ 3. So,Ā the leaving basis variable isĀ "S_3" .
ā“Ā The pivot element isĀ 2.
EnteringĀ ="x_1" , DepartingĀ ="S_3" , Key ElementĀ =2
Since allĀ Zj-Cjā„0
Hence, optimal solution is arrived with value of variables as :
"x_1" =5,"x_2" =5
MaxĀ Z=425
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