How to solve a LPP when the A of linprog does not form a square matrix? I have 5 variables and 2 constraints.

Max Z = 0.1*X1 + 0.15*X2 + 0.2*X3 + 0.5*X4 + 1.2*X5

Subject to:

2*X1 + 2*X2 + 2*X3 + 0.6*X4 + 0.3*X5 <= 750

0.04*X2 + 0.08*X3 + 0.09*X4 + 0.135*X5 <= 30.75

All variable >= zero.

Answer 1

[Stephan]

% define all constraints
A = [2, 2, 2, 0.6, 0.3;
     0 0.04, 0.08, 0.09, 0.135;
     -eye(5)]
b = [750, 30.75, zeros(1,5)]

% define obective function
Z = [0.1, 0.15, 0.2, 0.5, 1.2]

% call linprog with negative Z, due to maximization 
sol = linprog(-Z,A,b)

[BISWAJIT KAR]

This is not giving an answer. The maximization problem gives -ve vakue for objective function

[Stephan]

for me it results in - using R2020a:

A =

    2.0000    2.0000    2.0000    0.6000    0.3000
         0    0.0400    0.0800    0.0900    0.1350
   -1.0000         0         0         0         0
         0   -1.0000         0         0         0
         0         0   -1.0000         0         0
         0         0         0   -1.0000         0
         0         0         0         0   -1.0000


b =

  750.0000   30.7500         0         0         0         0         0


Z =

    0.1000    0.1500    0.2000    0.5000    1.2000


Optimal solution found.


sol =

  340.8333
         0
         0
         0
  227.7778