关键词: 粒子群算法, 拥挤距离, 竞标赛选择方法, 动态变异算子

Abstract: The crowing distance proposed in NSGA-II is adopted to calculate the crowing degree of the nondominated solutions in the external archive in this paper.The globally optimal position of each particle is predicted according to tournament selection scheme，and each particle is then guided to a sparse region of nondominated solutions.As a result，it is helpful for an algorithm to find a better distribution of the nondominated solutions.Moreover，the adoption of the dynamic mutation operator is beneficial to avoid the premature convergence.Based on all these，a novel particle swarm optimization algorithm is proposed and the simulations are made.The results indicate the effectiveness of the proposed algorithm.

Key words: Particle Swarm Optimization（PSO）, crowding distance, tounament selection, dynamic mutation operator