• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2008, Vol. 30 ›› Issue (10): 64-66.

• 论文 • 上一篇    下一篇

离散粒子群优化算法求解旅行商问题

刘伯颖[1] 吴敬松[1] 镡铁春[2] 李世杰[1]   

  • 出版日期:2008-10-01 发布日期:2010-05-19

  • Online:2008-10-01 Published:2010-05-19

摘要:

在优化领域,粒子群算法适用于求解连续优化问题,而在离散优化上的应用还相对较少。本文在介绍基本粒子群优化算法的基础上,分析了粒子群优化算法在经典旅行商问题  中的应用性能及粒子群算法求解旅行商问题的相关操作。使用Ulysses等标准TSP测试数据进行了相关实验,并通过不同的参数设置对实验结果进行了性能分析和比较。

关键词: 粒子群优化 旅行商问题 离散优化

Abstract:

The paper introduces basic particle swarm optimization and analyses its use in the traveling salesman problena. Particle Swarm Optimization (PSO) is  a new kind of evolutionary computation, which has been proved to be a powerful global optimization method. In the optimization field, PSO is suitable f   or continuous optimization, and it is rarely used in discrete optimization Therefore, the paper studies how to use PSO in solving discrete optimization    problems. And some experiments are done and the results of the experiments are analyzed.

Key words: particle swarm optimization, traveling salesman problem;discrete optimization