计算机与现代化 ›› 2011, Vol. 193 ›› Issue (9): 5-7,11.doi: 10.3969/j.issn.1006-2475.2011.09.002

• 算法设计与分析 • 上一篇    下一篇

改进的PSO在TSP中的应用

马晓慧1,王红1,2   

  1. 1.山东师范大学信息科学与工程学院, 山东 济南 250014; 2.山东省分布式计算机软件新技术重点实验室, 山东 济南 250014
  • 收稿日期:2011-04-21 修回日期:1900-01-01 出版日期:2011-09-22 发布日期:2011-09-22

Application of Improved PSO in TSP

MA Xiao-hui1, WANG Hong 1,2   

  1. 1.School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China; 2.Shandong Provincial Key Laboratory for Distributed Computer Software New Technology, Jinan 250014, China
  • Received:2011-04-21 Revised:1900-01-01 Online:2011-09-22 Published:2011-09-22

摘要: 粒子群优化算法(PSO)是Eberhart和Kennedy提出的,该算法具有思想简单、易编程实现等特点,引起了国内外相关领域众多学者的关注。本文以旅行商问题为例,提出一种离散粒子群优化算法,对粒子的位置、速度等量及运算规则进行定义,并在迭代过程中对速度引入收缩因子。实验结果表明,该算法具有很好的性能。

关键词: 粒子群算法, 离散粒子群, 组合优化, 旅行商问题

Abstract: The particle swarm optimization algorithm is proposed by Eberhart and Kennedy, thoughts of the algorithm is simple and easy to achieve by programming, so it attracts many scholars’ attention in related areas. The traveling salesman problem as an example, a discrete particle swarm optimization is proposed. The particle’s position, velocity and the operation rules are defined again. Velocity is added the shrinkage factor in the iteration process. The results show that the algorithm is of better performance.

Key words: particle swarm algorithm, discrete particle swarm, combinatorial optimization, traveling salesman problem

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