{"title":"How to select optimal control parameters for genetic algorithms","authors":"Qi-Wen Yang, Jing-ping Jiang, Guo Chen","doi":"10.1109/ISIE.2000.930482","DOIUrl":null,"url":null,"abstract":"In order to enhance the optimization efficiency, it's important for genetic algorithms (GAs) to select optimal control parameters. But the theory behind parameter setting for a GA gives little guidance for their selection. We have being selected the control parameters for GAs only by trials so far. In this paper, we discuss the function of genetic operators and present the conception of natality of schema (NS). We put forward an approach to estimating the optimal ranges of the control parameters for GAs by utilizing the NS. The approach is proven effectively by a genetic algorithm based on Boolean operators (GABO) which is proposed in this paper.","PeriodicalId":298625,"journal":{"name":"ISIE'2000. Proceedings of the 2000 IEEE International Symposium on Industrial Electronics (Cat. No.00TH8543)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISIE'2000. Proceedings of the 2000 IEEE International Symposium on Industrial Electronics (Cat. No.00TH8543)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIE.2000.930482","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In order to enhance the optimization efficiency, it's important for genetic algorithms (GAs) to select optimal control parameters. But the theory behind parameter setting for a GA gives little guidance for their selection. We have being selected the control parameters for GAs only by trials so far. In this paper, we discuss the function of genetic operators and present the conception of natality of schema (NS). We put forward an approach to estimating the optimal ranges of the control parameters for GAs by utilizing the NS. The approach is proven effectively by a genetic algorithm based on Boolean operators (GABO) which is proposed in this paper.
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