关键词: 粒子群算法, 自组织, 种群多样性, 旅行商问题（TSP）

Abstract: To alleviate the premature convergence of basic particle swarm optimization（PSO），an improved self-organized particle swarm optimization（SOPSO） algorithm is proposed，whose parameter setting are improved based on the characteristics of self-organizing criticality in the interest of the diversity of population.That is，the self-organizing inertia weight and acceleration coefficients are applied and the mutation operator is introduced.In view of the concept of “Swap operator” and“Swap sequence”，the improved SOPSO algorithm which can search in the discrete domain directly is designed to solve the traveling salesman problem（TSP）.Then compare the results of the improved algorithm with those of the basic PSO and other improved PSO algorithm.The results show that the improved SOPSO algorithm is effective.

Key words: Particle Swarm Optimization（PSO）, self-organizing, population diversity, Traveling Salesman Problem（TSP）