A Hybrid Strategy for Reducing Feasible Convex Space and the Number of Variables for Solving a Conventional Large LP Model

Abstract

This paper considers a conventional linear programming model of ‘n’ variables and ‘m’ constraints. In the proposed method, we deal with n_1 number of variables, where n_1≤n and use a strategic move to reduce the feasible convex search space before embarking on the simplex method. The feasible space reduction process can be repeated, if desired.