Selection of the Set of Constraint to Solve the Linear Programming Problems by Using Weighted Average of Constraint

Abstract

Linear Programming (LP) is concerned with the determination of a maximum or a minimum point of a linear function of several variables, which has to satisfy a number of linear constraints. Linear Programming has found its major application in the oil and chemical industry, refinery production planning, transportation planning and integrated planning problems. Since, the computational efficiency of the simplex method depends on the number of constraints and a very small number of constraints are involved to determine the solution of LP problem, Preprocessing is a very important step in solving linear programming problems. In this paper, a new algorithm is proposed for selecting a set of constraint(s) to solve the LP Problems based on the weighted average of each constraint. The algorithm is coded by using a computer programming language python. The procedure, computational results and performance analysis of the proposed algorithm are presented in this paper.