Developing New Model of Constraints Management in Linear Programming problems with reference to optimizing objective function

Linear programs (LP) play an important role in the theory and practice of optimization problems. Linear programming deals with problems such as maximising profits, minimising costs or ensuring you make the best use of available resources. While formulating a linear programming model, system analyst and researchers often tend to include all the possible constraints, although some of them may not be binding at the optimal solution. It is well known that, for most of the large scale LP problems, only a relatively small percentage of constraints are binding at the optimal solutions. Researchers have proposed methods which identify those constraints most likely to be tight at optimality. This paper proposes a new approach for finding solutions to LP problems by using a part of the constraints with the help of intercept and projection values of the each constraint. This method is more efficient when compared with the existing method. The developed algorithm is implemented by programming language Java and the computational results are presented. It shows that the proposed method reflects a significant decrease in the computational effort and is one of the best alternatives to select the necessary constraints prior to solving an LP problem.