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Implementation of the two phase simplex method within linear programming using Bland's rule

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simplex_method

Python implementation of the two phase simplex method within linear programming using Bland's rule

The algorithm will provide one of three solutions - a bounded solution, no solution, or an infinite (unbounded) solution.

The program takes the following variables:
int n: number of inequality equations
int m: total variables
list a: coefficients of inequality equations in a list of list
list b: maximums for each of the inqualities
list c: coefficients of the optimization function

Example Problem:
x + y - 3z <= 10
5x + 10y <= -50
3x - 2y -4z <= 9
Maximize: -x - 6y - 3z

You would enter the following within the input prompt:
3 3
1 1 -3
-5 10 0
3 -2 -4
10 -50 9
-1 -6 -3

Bounded Solution: 10.000 0.000 5.250

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Implementation of the two phase simplex method within linear programming using Bland's rule

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