{"title":"旅行商问题的遗传算法:改进的部分映射交叉算子","authors":"Vijendra Singh, Simran Choudhary","doi":"10.1109/MSPCT.2009.5164164","DOIUrl":null,"url":null,"abstract":"This paper addresses an attempt to evolve Genetic Algorithm by a particular modified Partially Mapped Crossover method to make it able to solve the Traveling Salesman Problem. Which is type of NP-hard combinatorial optimization problems. The main objective is to look a better GA such that solves TSP with shortest tour. First we solve the TSP by using PMX (Goldberg [1]) and then a modified PMX to evolve a GA.","PeriodicalId":179541,"journal":{"name":"2009 International Multimedia, Signal Processing and Communication Technologies","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Genetic algorithm for Traveling Salesman Problem: Using modified Partially-Mapped Crossover operator\",\"authors\":\"Vijendra Singh, Simran Choudhary\",\"doi\":\"10.1109/MSPCT.2009.5164164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses an attempt to evolve Genetic Algorithm by a particular modified Partially Mapped Crossover method to make it able to solve the Traveling Salesman Problem. Which is type of NP-hard combinatorial optimization problems. The main objective is to look a better GA such that solves TSP with shortest tour. First we solve the TSP by using PMX (Goldberg [1]) and then a modified PMX to evolve a GA.\",\"PeriodicalId\":179541,\"journal\":{\"name\":\"2009 International Multimedia, Signal Processing and Communication Technologies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Multimedia, Signal Processing and Communication Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MSPCT.2009.5164164\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Multimedia, Signal Processing and Communication Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSPCT.2009.5164164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Genetic algorithm for Traveling Salesman Problem: Using modified Partially-Mapped Crossover operator
This paper addresses an attempt to evolve Genetic Algorithm by a particular modified Partially Mapped Crossover method to make it able to solve the Traveling Salesman Problem. Which is type of NP-hard combinatorial optimization problems. The main objective is to look a better GA such that solves TSP with shortest tour. First we solve the TSP by using PMX (Goldberg [1]) and then a modified PMX to evolve a GA.
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