{"title":"遗传算法在零件参数设计中的应用","authors":"Xijun Zhu, Yawen Yan, X. Lu, Yijia Lu","doi":"10.1109/ICNC.2012.6234636","DOIUrl":null,"url":null,"abstract":"This paper investigates the application of Genetic Algorithms (GAs) in component parameters design. From the perspective of profit per unit product, we have established the nonlinear programming model to determine the machine precision and product calibration value. After that, we solve the nonlinear programming model based on GAs, which can fix out the most appropriate component parameters to optimize the result. We conduct a comparative study between GAs and the enumeration method and give relevant analysis in the end of this paper.","PeriodicalId":404981,"journal":{"name":"2012 8th International Conference on Natural Computation","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The application of Genetic Algorithms in component parameters design\",\"authors\":\"Xijun Zhu, Yawen Yan, X. Lu, Yijia Lu\",\"doi\":\"10.1109/ICNC.2012.6234636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the application of Genetic Algorithms (GAs) in component parameters design. From the perspective of profit per unit product, we have established the nonlinear programming model to determine the machine precision and product calibration value. After that, we solve the nonlinear programming model based on GAs, which can fix out the most appropriate component parameters to optimize the result. We conduct a comparative study between GAs and the enumeration method and give relevant analysis in the end of this paper.\",\"PeriodicalId\":404981,\"journal\":{\"name\":\"2012 8th International Conference on Natural Computation\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 8th International Conference on Natural Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2012.6234636\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 8th International Conference on Natural Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2012.6234636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The application of Genetic Algorithms in component parameters design
This paper investigates the application of Genetic Algorithms (GAs) in component parameters design. From the perspective of profit per unit product, we have established the nonlinear programming model to determine the machine precision and product calibration value. After that, we solve the nonlinear programming model based on GAs, which can fix out the most appropriate component parameters to optimize the result. We conduct a comparative study between GAs and the enumeration method and give relevant analysis in the end of this paper.