Intuitionistic Fuzzy Multi-objective Programming Based On Improved Particle Swarm Optimization

In this paper,we are base on intuitionistic fuzzy sets and interval fuzzy sets isomorphic,through linear weighting method and the main objective method of intuitionistic fuzzy multi-objective programming problem is transformed into intuitionistic fuzzy single objective programming problem respectively, Then“max- min”operator to obtain a solution of the model contains two parameters and particle swarm algorithm,then ”max- min” operator, solving the model were obtained containing parameters and with particle swarm algorithm.In particle swarm algorithm, through the introduction of hybrid probability of particles variation process, thus increasing the dynamic range of the particles. In addition,in an iterative process to store the particles in best position after M iterations by setting a variable, and the position and velocity of the particle initialization algorithm to avoid premature.Specific arrangements are as follows:The first chapter mainly introduces the research background and research status of Intuition fuzzy multi- objective programming and particle swarm algorithm.The second chapter describes the general intuition fuzzy multi-objective programming problems and traditional solutions,Introduced PSO and paper use to the knowledge points.The third chapter describes the use of linear weighting method for solving multi-objective approach to function and gives a numerical example.The fourth chapter describes the process more objective method for solving the problem and gives a numerical example using the main objective method.The fifth chapter summarizes the conclusions obtained in this paper and puts forward problem remaining to be solved.