计算机工程与应用2009，Vol.45Issue(31)：30-33,4.DOI:10.3778/j.issn.1002-8331.2009.31.010
求解TSP的改进自组织PSO算法
Improved self-organizing particle swarm optimization for Traveling Salesman Problem
摘要
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.关键词
粒子群算法/自组织/种群多样性/旅行商问题(TSP)Key words
Particle Swarm Optimization (PSO)/ self-organizing/ population diversity/ Traveling Salesman Problem(TSP)分类
信息技术与安全科学引用本文复制引用
孙晶晶,雷秀娟..求解TSP的改进自组织PSO算法[J].计算机工程与应用,2009,45(31):30-33,4.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60773224) （the National Natural Science Foundation of China under Grant No.60773224）
陕西师范大学研究生创新基金(the Innovation Funds of Graduate Programs of Shaanxi Normal University,No.2009CXS020). （the Innovation Funds of Graduate Programs of Shaanxi Normal University,No.2009CXS020）
