关键词: 粒子群算法, 最大最小适应函数, 轮序, 罚函数

Abstract: In this paper，Max-Min fitness function and penalty function are combined together，and a practical and effective particle swarm optimization algorithm is proposed to solve multi-objectives constrained optimization problems.Non-inferior solutions are replaced according to the idea of cluster and compare.The method of selecting globally optimal solution from non-inferior solutions in turn is adopted instead of the ancient method.The experimental results show that the modified MaxMin-PSO algorithm converges more quickly and efficiently to Pareto solutions and achieve a well distribution.It also restrains the radiation of low dimension multi-objectives constrained functions.

Key words: particle swarm algorithm, MaxMin function, turn list, punish function