A STUDY OF REDUNDANT CONSTRAINTS IN LINEAR PROGRAMMING MODELS

Linear Programming is a mathematical technique to help plan and to achieve the best outcome. It will make decisions relative to allocate resources and find the minimum or maximum value of the objective. While formulating a linear programming model, decision makers often tend to include all the possible constraints and variables although some of them may not be binding at the optimal solution. In fact, LP models almost contain a significant number of redundant constraints and variables. Therefore it is worthwhile to devote some efforts in solving for considerable reduction in the size of the problem. In this aspect, this paper proposes to identify which constraints and variables most likely to be tight at optimalit