{"title":"一种改进的遗传蚁群优化算法求解旅行商问题","authors":"Lanlan Kang, Wenliang Cao","doi":"10.1109/ISISE.2010.126","DOIUrl":null,"url":null,"abstract":"Ant Colony Algorithm (ACA) and Generation Algorithm (GA) are two bionic optimization algorithm, they are also two powerful and effective algorithms for solving the combination optimization problems, moreover they all were successfully used in traveling salesman problem (TSP) . This paper syncretizes two algorithms, meanwhile, a new syncretic method is put forward. The simulation results show that the new algorithm of ACA and GA is better at improving global convergence and quickening the speed of convergence.","PeriodicalId":206833,"journal":{"name":"2010 Third International Symposium on Information Science and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"An Improved Genetic & Ant Colony Optimization Algorithm for Travelling Salesman Problem\",\"authors\":\"Lanlan Kang, Wenliang Cao\",\"doi\":\"10.1109/ISISE.2010.126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ant Colony Algorithm (ACA) and Generation Algorithm (GA) are two bionic optimization algorithm, they are also two powerful and effective algorithms for solving the combination optimization problems, moreover they all were successfully used in traveling salesman problem (TSP) . This paper syncretizes two algorithms, meanwhile, a new syncretic method is put forward. The simulation results show that the new algorithm of ACA and GA is better at improving global convergence and quickening the speed of convergence.\",\"PeriodicalId\":206833,\"journal\":{\"name\":\"2010 Third International Symposium on Information Science and Engineering\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Third International Symposium on Information Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISISE.2010.126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Symposium on Information Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISISE.2010.126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Genetic & Ant Colony Optimization Algorithm for Travelling Salesman Problem
Ant Colony Algorithm (ACA) and Generation Algorithm (GA) are two bionic optimization algorithm, they are also two powerful and effective algorithms for solving the combination optimization problems, moreover they all were successfully used in traveling salesman problem (TSP) . This paper syncretizes two algorithms, meanwhile, a new syncretic method is put forward. The simulation results show that the new algorithm of ACA and GA is better at improving global convergence and quickening the speed of convergence.
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