← 2023 Paper 2

UPSC 2023 Maths Optional Paper 2 Q3c — Step-by-Step Solution

20 marks · Section A

Big-M / two-phase method (artificial variables) · Linear Programming · asked 5× in 14 yrs · Read the full method →

Question

Solve the following linear programming problem by Big M method:

Minimize Z=2x1+3x2\text{Minimize }Z=2x_1+3x_2

subject to

x1+x2≥9,  x1+2x2≥15,  2x1−3x2≤9,  x1,x2≥0.x_1+x_2\ge 9,\;x_1+2x_2\ge 15,\;2x_1-3x_2\le 9,\;x_1,x_2\ge 0.

Is the optimal solution unique? Justify your answer.

Technique

Big-M simplex; two iterations sufficed because both artificials left the basis with positive penalties.

Solution

Step 1 — Standard form

Introduce surplus s1,s2s_1,s_2 for the ≥\ge constraints, slack s3s_3 for the ≤\le, and artificials a1,a2a_1,a_2 for the ≥\ge constraints to obtain a starting BFS:

x1+x2−s1+a1=9,x1+2x2−s2+a2=15,2x1−3x2+s3=9,all variables≥0.\begin{aligned}x_1+x_2-s_1+a_1&=9,\\ x_1+2x_2-s_2+a_2&=15,\\ 2x_1-3x_2+s_3&=9,\\ \text{all variables}&\ge 0.\end{aligned}

Big-M objective (minimisation; artificials carry large penalty MM):

min⁡  Z=2x1+3x2+0⋅s1+0⋅s2+0⋅s3+M a1+M a2.\min\;Z=2x_1+3x_2+0\cdot s_1+0\cdot s_2+0\cdot s_3+M\,a_1+M\,a_2.

Step 2 — Initial simplex tableau

Initial basis B(0)={a1,a2,s3}B^{(0)}=\{a_1,a_2,s_3\} with a1=9,  a2=15,  s3=9a_1=9,\;a_2=15,\;s_3=9, Z(0)=24MZ^{(0)}=24M. Cost row cB=(M,M,0)Tc_B=(M,M,0)^{T}.

zj−cjz_j-c_j values (recall: for a min problem, enter the variable with the largest positive zj−cjz_j-c_j; optimal when all zj−cj≤0z_j-c_j\le 0):

Variablezjz_jcjc_jzj−cjz_j-c_j
x1x_1M+M+0=2MM+M+0=2M222M−22M-2
x2x_2M+2M+0=3MM+2M+0=3M333M−3\mathbf{3M-3}
s1s_1−M-M00−M-M
s2s_2−M-M00−M-M
s3s_3000000

Largest positive: x2x_2 column. Min-ratio: min⁡{9/1,15/2}=15/2=7.5\min\{9/1,15/2\}=15/2=7.5 → a2a_2 leaves. Pivot on entry (row2,x2)(\text{row}_2,x_2).

Step 3 — Iteration 1: x2x_2 in, a2a_2 out

Divide row 2 by 2; eliminate x2x_2 from rows 1 and 3.

Basisx1x_1x2x_2s1s_1s2s_2s3s_3a1a_1RHS
a1a_10.50.500−1-10.50.500111.51.5
x2x_20.50.51100−0.5-0.500007.57.5
s3s_33.53.50000−1.5-1.5110031.531.5

(a2a_2 column is dropped; it has left and won’t re-enter.)

New cB=(M,3,0)Tc_B=(M,3,0)^{T}.

Variablezjz_jcjc_jzj−cjz_j-c_j
x1x_10.5M+1.5+0=0.5M+1.50.5M+1.5+0=0.5M+1.5220.5M−0.5\mathbf{0.5M-0.5}
s1s_1−M+0+0=−M-M+0+0=-M00−M-M
s2s_20.5M−1.5+0=0.5M−1.50.5M-1.5+0=0.5M-1.5000.5M−1.50.5M-1.5
s3s_3000000

Largest positive: x1x_1 (0.5M−0.50.5M-0.5). Min-ratio: min⁡{1.5/0.5,  7.5/0.5,  31.5/3.5}=min⁡{3,15,9}=3\min\{1.5/0.5,\;7.5/0.5,\;31.5/3.5\}=\min\{3,15,9\}=3 → a1a_1 leaves. Pivot on entry (row1,x1)(\text{row}_1,x_1).

Step 4 — Iteration 2: x1x_1 in, a1a_1 out

Divide row 1 by 0.50.5; eliminate x1x_1 from rows 2, 3.

Basisx1x_1x2x_2s1s_1s2s_2s3s_3RHS
x1x_11100−2-2110033
x2x_2001111−1-10066
s3s_3000077−5-5112121

(a1a_1 column dropped.)

New cB=(2,3,0)Tc_B=(2,3,0)^{T}, Z=2(3)+3(6)+0=24Z=2(3)+3(6)+0=24.

zj−cjz_j-c_j:

Variablezjz_jcjc_jzj−cjz_j-c_j
s1s_12(−2)+3(1)+0(7)=−12(-2)+3(1)+0(7)=-100−1-1
s2s_22(1)+3(−1)+0(−5)=−12(1)+3(-1)+0(-5)=-100−1-1

All zj−cj≤0z_j-c_j\le 0 → optimal.

Step 5 — Optimum and uniqueness

Answer

  x1=3,  x2=6,  Zmin⁡=24.  \boxed{\;x_1=3,\;x_2=6,\;Z_{\min}=24.\;}
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