{"title":"一种改进的带有基准函数的遗传算法","authors":"A. L. Araújo, F. M. Assis","doi":"10.1109/SBRN.2000.889764","DOIUrl":null,"url":null,"abstract":"In a previous paper by the authors (1998) it was shown that a new genetic algorithm (GA) performed better than a basic GA. In the present paper we focus on an improved genetic algorithm which uses the theory of cosets. The new technique was tested using some benchmark functions for which the basic GA performance was not good enough. The main purpose of this paper is to suggest how to use linear codes properties to guide the GA search.","PeriodicalId":448461,"journal":{"name":"Proceedings. Vol.1. Sixth Brazilian Symposium on Neural Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An improved genetic algorithm performance with benchmark functions\",\"authors\":\"A. L. Araújo, F. M. Assis\",\"doi\":\"10.1109/SBRN.2000.889764\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a previous paper by the authors (1998) it was shown that a new genetic algorithm (GA) performed better than a basic GA. In the present paper we focus on an improved genetic algorithm which uses the theory of cosets. The new technique was tested using some benchmark functions for which the basic GA performance was not good enough. The main purpose of this paper is to suggest how to use linear codes properties to guide the GA search.\",\"PeriodicalId\":448461,\"journal\":{\"name\":\"Proceedings. Vol.1. Sixth Brazilian Symposium on Neural Networks\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-01-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. Vol.1. Sixth Brazilian Symposium on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SBRN.2000.889764\",\"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. Vol.1. Sixth Brazilian Symposium on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SBRN.2000.889764","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An improved genetic algorithm performance with benchmark functions
In a previous paper by the authors (1998) it was shown that a new genetic algorithm (GA) performed better than a basic GA. In the present paper we focus on an improved genetic algorithm which uses the theory of cosets. The new technique was tested using some benchmark functions for which the basic GA performance was not good enough. The main purpose of this paper is to suggest how to use linear codes properties to guide the GA search.
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