Solve the following linear programming problem using the simplex method:
𝑀𝑎𝑥𝑖𝑚𝑖𝑧𝑒 𝑧 = 14𝑥 + 15𝑦
𝑠𝑢𝑏𝑗𝑒𝑐𝑡 𝑡𝑜
13𝑥 + 15𝑦 ≤ 80
−12𝑥 − 17𝑦 ≥ −120
𝑥 ≥ 0, 𝑦 ≥ 0
Replace "x" by "x_1" and "y" by "x_2."
Problem is: "\\operatorname{Max} Z=14 x_{1}+15 x_{2}"
subject to:
"\\begin{array}{rllll} \n& 13 & x_{1} & + & 15 & x_{2} & \\leq 80 \\\\\n- & 12 & x_{1} & - & 17 & x_{2} & \\leq-120\n\\end{array}"
Here, "b_{2}=-120<0"
so multiply this constraint by "-1" to make "b_{2}>0 ."
"12 x_{1}+17 \\quad x_{2} \\geq 120\n \n \\ and \\ x_{1}, x_{2} \\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 constraint-2 is of type '≥' we should subtract surplus variable "S_2" and add artificial variable "A_1."
After introducing slack, surplus,artificial variables:
"\\operatorname{Max} Z=14 x_{1}+15 x_{2}+0 S_{1}+0 S_{2}-M A_{1}"
subject to:
"13 x_{1}+15 x_{2}+S_{1} \\quad=80 \\\\ 12 x_{1}+17 x_{2} \\quad-S_{2}+A_{1}=120 \\\\ and \\ x_{1}, x_{2}, S_{1}, S_{2}, A_{1} \\geq 0"
Negative minimum Zj-Cj is -17M-15 and its column index is 2. So, the entering variable is x2.
Minimum ratio is 5.3333 and its row index is 1. So, the leaving basis variable is S1.
∴ The pivot element is 15.
Entering =x2, Departing =S1, Key Element =15
Since all Zj-Cj≥0
Hence, the optimal solution arrives with value of variables as :
x1=0,x2=5.3333
Max Z=80
But this solution is not feasible
because the final solution violates the 2nd constraint 12 x1 + 17 x2 ≥ 120.
and the artificial variable A1 appears in the basis with a positive value of 29.3333
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