关键词: 模糊集, 模糊关联熵, 多目标优化, 粒子群优化算法, 流水车间

Abstract: Aiming at the disadvantages of existing optimization methods on solving high-dimensional multi-objective optimization problem,the multi-objective solution was mapped into fuzzy set,and the relative entropy of fuzzy sets representing the similar degree between fuzzy sets were used to solve multi-objective optimization problem.A multi-objective optimization method based on relative entropy of fuzzy sets was presented,and the size of fuzzy relational entropy coefficient was used to measure similar degree between the fuzzy sets of Pareto solutions and the fuzzy set of ideal solution.The coefficient used as Particle Swarm Optimization (PSO) fitness was applied to guide algorithm evolution,therefore the multi-objective PSO based on relative entropy of fuzzy sets was established.Experiments showed that PSO based on relative entropy of fuzzy sets could solve high-dimensional multi-objective flow shop scheduling problem effectively.The optimization solution and performance indicators of the algorithm were better than PSO based on random weight.Especially in solving large-scale problems,the performance of PSO based on relative entropy of fuzzy sets was much better.

Key words: fuzzy sets, fuzzy relative entropy, multi-objective optimization, particle swarm optimization, flow shop