{"title":"遗传算法中的新交叉算子","authors":"Yi Shang, Guo-Jie Li","doi":"10.1109/TAI.1991.167090","DOIUrl":null,"url":null,"abstract":"Two new crossover operators in genetic algorithms for solving some combinatorial problems with ordering are presented. One is enhanced order crossover (EOX). The other, GREE, is a heuristic crossover for a class of combinatorial optimization problems, such as traveling salesman problems (TSPs). Genetic algorithms using GREE as unique crossover run very fast and get good solutions. Combining GREE with EOX, genetic algorithms can find optimal or very near optimal solutions in a rather short time.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"New crossover operators in genetic algorithms\",\"authors\":\"Yi Shang, Guo-Jie Li\",\"doi\":\"10.1109/TAI.1991.167090\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Two new crossover operators in genetic algorithms for solving some combinatorial problems with ordering are presented. One is enhanced order crossover (EOX). The other, GREE, is a heuristic crossover for a class of combinatorial optimization problems, such as traveling salesman problems (TSPs). Genetic algorithms using GREE as unique crossover run very fast and get good solutions. Combining GREE with EOX, genetic algorithms can find optimal or very near optimal solutions in a rather short time.<<ETX>>\",\"PeriodicalId\":371778,\"journal\":{\"name\":\"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1991.167090\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1991.167090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Two new crossover operators in genetic algorithms for solving some combinatorial problems with ordering are presented. One is enhanced order crossover (EOX). The other, GREE, is a heuristic crossover for a class of combinatorial optimization problems, such as traveling salesman problems (TSPs). Genetic algorithms using GREE as unique crossover run very fast and get good solutions. Combining GREE with EOX, genetic algorithms can find optimal or very near optimal solutions in a rather short time.<>