A hybrid strategy for reducing feasible convex space and the number of variables for solving a conventional large LP model

This paper considers a conventional linear programming model of 'n' variables and 'm' constraints. In the proposed method, we deal with n1 number of variables, where n1≤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.