{"title":"图划分问题的遗传算法编码表示","authors":"M. Boulif","doi":"10.1109/ICMWI.2010.5648133","DOIUrl":null,"url":null,"abstract":"This paper presents an insight on genetic algorithm (GA) encoding representations applied to graph partitioning problems. Redundancy and blindness, two important features that have a direct impact on the performance of the method, are theoretically investigated and some conclusions are drawn.","PeriodicalId":404577,"journal":{"name":"2010 International Conference on Machine and Web Intelligence","volume":"191 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Genetic algorithm encoding representations for graph partitioning problems\",\"authors\":\"M. Boulif\",\"doi\":\"10.1109/ICMWI.2010.5648133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an insight on genetic algorithm (GA) encoding representations applied to graph partitioning problems. Redundancy and blindness, two important features that have a direct impact on the performance of the method, are theoretically investigated and some conclusions are drawn.\",\"PeriodicalId\":404577,\"journal\":{\"name\":\"2010 International Conference on Machine and Web Intelligence\",\"volume\":\"191 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Machine and Web Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMWI.2010.5648133\",\"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 International Conference on Machine and Web Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMWI.2010.5648133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Genetic algorithm encoding representations for graph partitioning problems
This paper presents an insight on genetic algorithm (GA) encoding representations applied to graph partitioning problems. Redundancy and blindness, two important features that have a direct impact on the performance of the method, are theoretically investigated and some conclusions are drawn.