{"title":"改进的实编码遗传算法","authors":"J. An, Hai-juan Jin, Chaohun Liu","doi":"10.1109/NSWCTC.2009.335","DOIUrl":null,"url":null,"abstract":"To solve the slow convergence rate and local convergence of Simple Genetic Algorithm, an improved genetic algorithm (IGA) with real-coding, elite reservation, 2/4competitive choosing and adaptive genetic strategy is proposed. The experiment shows that the improved algorithm is more effective in realizing the global optimization and promoting evolution efficiency.","PeriodicalId":433291,"journal":{"name":"2009 International Conference on Networks Security, Wireless Communications and Trusted Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Improved Real-coding Genetic Algorithm\",\"authors\":\"J. An, Hai-juan Jin, Chaohun Liu\",\"doi\":\"10.1109/NSWCTC.2009.335\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the slow convergence rate and local convergence of Simple Genetic Algorithm, an improved genetic algorithm (IGA) with real-coding, elite reservation, 2/4competitive choosing and adaptive genetic strategy is proposed. The experiment shows that the improved algorithm is more effective in realizing the global optimization and promoting evolution efficiency.\",\"PeriodicalId\":433291,\"journal\":{\"name\":\"2009 International Conference on Networks Security, Wireless Communications and Trusted Computing\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Networks Security, Wireless Communications and Trusted Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NSWCTC.2009.335\",\"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 Conference on Networks Security, Wireless Communications and Trusted Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSWCTC.2009.335","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
To solve the slow convergence rate and local convergence of Simple Genetic Algorithm, an improved genetic algorithm (IGA) with real-coding, elite reservation, 2/4competitive choosing and adaptive genetic strategy is proposed. The experiment shows that the improved algorithm is more effective in realizing the global optimization and promoting evolution efficiency.