基于最大最小系统和粒子群优化的TSP问题混合算法

2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2018-05-18 DOI:10.1109/YAC.2018.8406459

Hao Qian, Tao Su

{"title":"基于最大最小系统和粒子群优化的TSP问题混合算法","authors":"Hao Qian, Tao Su","doi":"10.1109/YAC.2018.8406459","DOIUrl":null,"url":null,"abstract":"A hybrid algorithm which combines ant colony optimization algorithm and particle swarm optimization algorithm(ACO-PSO) is proposed to solve travelling salesman problem. Max-Min Ant System, whose parameters are optimized by PSO, is utilized to solve the problems. Massive of benchmark problems are utilized to test the performance of proposed algorithm.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"98 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Hybrid algorithm based on max and min ant system and particle swarm optimization for solving TSP problem\",\"authors\":\"Hao Qian, Tao Su\",\"doi\":\"10.1109/YAC.2018.8406459\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A hybrid algorithm which combines ant colony optimization algorithm and particle swarm optimization algorithm(ACO-PSO) is proposed to solve travelling salesman problem. Max-Min Ant System, whose parameters are optimized by PSO, is utilized to solve the problems. Massive of benchmark problems are utilized to test the performance of proposed algorithm.\",\"PeriodicalId\":226586,\"journal\":{\"name\":\"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)\",\"volume\":\"98 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/YAC.2018.8406459\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YAC.2018.8406459","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 7

摘要

提出了一种结合蚁群优化算法和粒子群优化算法(ACO-PSO)求解旅行商问题的混合算法。利用蚁群优化算法优化参数的最大最小蚁群系统来解决这一问题。利用大量的基准问题来测试算法的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Hybrid algorithm based on max and min ant system and particle swarm optimization for solving TSP problem

A hybrid algorithm which combines ant colony optimization algorithm and particle swarm optimization algorithm(ACO-PSO) is proposed to solve travelling salesman problem. Max-Min Ant System, whose parameters are optimized by PSO, is utilized to solve the problems. Massive of benchmark problems are utilized to test the performance of proposed algorithm.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)

自引率

0.00%

发文量