Improved Particle Swarm Optimization for Multi-object Traveling Salesman Problems

摘要：

an improved particle swarm optimization algorithm is proposed in this paper. The algorithm draws on the thinking of the greedy algorithm to initialize the particle swarm. Two swarms are used to optimize synchronously, and crossover and mutation operators in genetic algorithm are introduced into the new algorithm. The algorithm is used to solve multiobject Traveling Salesman Problem. We also use this algorithm to solve multi-object TSP often scattered attractions in Shan Xi Province. The results show that the algorithm has high convergence speed and convergence ratio. More Pareto optimal are found with this algorithm.

关键词： particle swarm optimization traveling salesman problem Greedy algorithm multi-object optimization Pareto optimal

作者: Su Jin-rong

作者单位: Department of information Business College of Shan Xi University Tai Yuan, China

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 1201-1205

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）