The Research Of Linear Programming Problem Based On Particle Swarm Optimization

Linear programming problem is a mathematical principle as basis, solving practical optimization problems. Planning is a branch of operations research, his application scope is increasing year by year, belonging to the research time early in the development speed very quickly, an important branch of more mature, it is to help people to carry out scientific management an effective mathematical method. It refers to under the conditions, use some methods to find some parameters, so that the specified function reaches a critical value.According to the objective function and constraints for constructing linear expressions, and according to whether the expression is a linear programming problem, will be divided into two types: linear programming and nonlinear programming.Particle swarm algorithm is a novel programming optimization algorithm, started by the initialization parameter and run many times iteration to gradually update efficient solution,finding optimal solutions of the planning problem, global optimal solution can solve the linear programming problem. This paper will give a can adaptive particle group optimization algorithm, this algorithm in the control model of the linear constraint condition by switching technology, and through to the objective function of weighted evaluation to make it adaptive to form to function. The experimental results show that this method is running with a real and effective, and it is important to solve practical problems.Based on the review of previous papers, this paper studies the linear programming problem based on particle swarm optimization. To this end, this paper gives the study direction for further.