Linear Programming in Industry pp 65-89 | Cite as

# Computational Procedures for Solving Linear Programming Problems

## Abstract

As we have seen in Ch. II^{2}, the simplex procedure can be described as a systematic method of examining the set of basic feasible solutions, starting in an arbitrary initial basis of *m* variables (activities) where *m* is the number of linear restrictions. If the initial basic solution does not satisfy the simplex criterion, we move to a neighboring basis by replacing one of the basic variables, and so forth, until a basic feasible solution is attained in which all of the simplex coefficients are non-positive (in a minimization problem, non-negative). By the Fundamental Theorem, such a solution will be an optimal solution.

## Keywords

Basic Solution Linear Programming Problem Basic Variable Transportation Problem Slack Variable## Preview

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