计算机与数字工程2018，Vol.46Issue(2)：218-221,235,5.DOI:10.3969/j.issn.1672-9722.2018.02.002
一种求解旅行商问题的改进混合粒子群算法
An Improved Hybrid Particle Swarm Optimization Algorithm for Solving Traveling Salesman Problem
摘要
Abstract
In order to improve the convergence speed and accuracy of the particle swarm optimization(PSO)algorithm in solv-ing the traveling salesman problem(TSP),an improved hybrid particle swarm optimization(IHPSO)algorithm is proposed.Based on existing hybrid particle swarm optimization algorithm,the greedy crossover operator is used to improve the convergence speed, and a chaotic particle is introduced into the population by using the characteristics of chaotic motion.Instead of searching for the op-timal solution in the solution space,the chaotic particle is used to implement greedy cross with other particles,and then expand the search scope of other particles,so the method can be utilized to enhance the precision of the solution.By using MATLAB,the exper-iments are carried out on the data set in TSPLIB,and the experimental results show that the improved algorithm can improve both convergence speed and accuracy.关键词
粒子群算法/贪婪交叉/混沌粒子/旅行商问题Key words
particle swarm optimization/greedy crossover/chaotic particle/traveling salesman problem分类
信息技术与安全科学引用本文复制引用
裴皓晨,娄渊胜,叶枫,黄倩..一种求解旅行商问题的改进混合粒子群算法[J].计算机与数字工程,2018,46(2):218-221,235,5.基金项目
国家自然科学基金项目(编号:61300122) （编号:61300122）
2013年江苏水利科技项目(编号:2013025)资助. （编号:2013025）
