Particle Swarm Optimization Algorithm For Multi-Objective Programming And Its Application

The multi-objective programming problem can fully reflect the wishes of decision makers,so the model has shown more and more extensive application prospects.However,compared with the widespread application of multi-objective programming,the research on the algorithm of this problem is relatively lagging behind.The lag of the algorithm is mainly due to two points.One is that the global convergence and convergence efficiency of the algorithm are difficult to balance,and the other is that the performance of the function in the model is highly demanded.However,particle swarm optimization has five advantages,such as loose functional requirements,population as operation unit,fast convergence speed,natural real number coding,simple operation,and so on.It has a high matching with multi-objective programming problem.Therefore,this paper studies the algorithm of multi-objective programming problem by means of particle swarm optimization.The main contents of this paper are as follows:In chapter I,we review the literature on multi-objective programming,introduces the research of numerical algorithm,intelligent algorithm and application of multiobjective programming,and gives the main contents of this paper.In chapter II,the principle of particle swarm optimization(PSO)is presented,the steps of standard PSO and the parameters of PSO are introduced,and several classical improved PSO algorithms for single objective programming are introduced.In chapter III,we introduce the model and related definitions of multi-objective programming,and proposes a multi-objective particle swarm optimization algorithm based on Pareto optimal solution.The strategies involved are: sorting method of uncontrolled rank values of particles,updating rules of elite set,computing method of particle crowding distance,selection method of global optimal individual particles and selection method of individual optimal particles,etc.The experimental results show that the algorithm has good convergence and distribution.Finally,this paper summarizes the full text and puts forward some questions to be further studied.