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。
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 for 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.
出处
《计算机工程与科学》
CSCD
2008年第10期64-66,共3页
Computer Engineering & Science
关键词
粒子群优化
旅行商问题
离散优化
particle swarm optimization
traveling salesman problem
discrete optimization
