Solve the following linear programming model using the simplex method:
maximize Z = 100x1 + 20x2 + 60x3
subject to
x3 smaller than or equal to 40
2x1 + 2x2 + 2x3 smaller than or equal to 100
3x1 + 5x2 smaller than or equal to 60
x1, x2, x3 bigger than or equal to 0
Solution:
"\\operatorname{Max} Z=100 x_{1}+20 x_{2}+60 x_{3}"
subject to
"\\begin{aligned}\nx_{3} & \\leq 40 \\\\\n2 x_{1}+2 x_{2}+2 x_{3} & \\leq 100\n\\end{aligned}"
"3 x_{1}+5 x_{2} \\quad \\geq 60\\\\\nand\\ x_{1}, x_{2}, x_{3} \\geq 0"
The problem is converted to canonical form by adding slack, surplus, and artificial variables as appropriate
1. As the constraint-1 is of type '≤' we should add slack variable "S_1"
2. As the constraint-2 is of type '≤' we should add slack variable "S_2"
3. As the constraint-3 is of type '≥' we should subtract surplus variable "S_3" and add artificial variable "A_1"
After introducing slack, surplus, artificial variables
"\\operatorname{Max} Z=100 x_{1}+20 x_{2}+60 x_{3}+0 S_{1}+0 S_{2}+0 S_{3}-M A_{1}"
subject to
"x_{3}+S_{1}\n=40\\\\\n2 x_{1}+2 x_{2}+2 x_{3}\nS\n=100\\\\\n3 x_{1}+5 x_{2} \\quad-S_{3}+A_{1}=60\\\\\nand\\ x_{1}, x_{2}, x_{3}, S_{1}, S_{2}, S_{3}, A_{1} \\geq 0"
Negative minimum "Z_{j}-C_{j}" is "-5 M-20" and its column index is 2 . So, the entering variable is "x_{2}"
The minimum ratio is 12 and its row index is 3. So, the leaving basis variable is "A_{1}" .
Therefore, the pivot element is 5 .
Entering "=x_{2}" , Departing "=A_{1}" , Key Element =5
"R_{3}(\\mathrm{new})=R_{3}(\\mathrm{old}) \\div 5"
"R_{1}( new )=R_{1}( old )"
"R_2(new)=R_2(old)-2R_3(new)"
Similarly, we have iteration 2, 3, 4, and 5 as follows:
Since all "Z_j-C_j\u22650"
Hence, optimal solution is arrived with value of variables as :
"x_1=50,x_2=0,x_3=0"
Max Z=5000
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