{"title":"元胞制造问题求解的演化相似系数","authors":"C. Dimopoulos, N. Mort","doi":"10.1109/CEC.2000.870355","DOIUrl":null,"url":null,"abstract":"The cell formation problem is a classic manufacturing optimisation problem associated with the implementation of a cellular manufacturing system. A variety of hierarchical clustering procedures have been proposed for the solution of this problem. Essential for the operation of a clustering procedure is the determination of a form of similarity between the objects that are going to be grouped. The authors employ a genetic programming algorithm for the evolution of new similarity coefficients for the solution of simple cell formation problems. Evolved coefficients are tested against the well-known Jaccard's similarity coefficient on a large number of problems taken from the literature.","PeriodicalId":218136,"journal":{"name":"Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Evolving similarity coefficients for the solution of cellular manufacturing problems\",\"authors\":\"C. Dimopoulos, N. Mort\",\"doi\":\"10.1109/CEC.2000.870355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The cell formation problem is a classic manufacturing optimisation problem associated with the implementation of a cellular manufacturing system. A variety of hierarchical clustering procedures have been proposed for the solution of this problem. Essential for the operation of a clustering procedure is the determination of a form of similarity between the objects that are going to be grouped. The authors employ a genetic programming algorithm for the evolution of new similarity coefficients for the solution of simple cell formation problems. Evolved coefficients are tested against the well-known Jaccard's similarity coefficient on a large number of problems taken from the literature.\",\"PeriodicalId\":218136,\"journal\":{\"name\":\"Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEC.2000.870355\",\"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 of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2000.870355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evolving similarity coefficients for the solution of cellular manufacturing problems
The cell formation problem is a classic manufacturing optimisation problem associated with the implementation of a cellular manufacturing system. A variety of hierarchical clustering procedures have been proposed for the solution of this problem. Essential for the operation of a clustering procedure is the determination of a form of similarity between the objects that are going to be grouped. The authors employ a genetic programming algorithm for the evolution of new similarity coefficients for the solution of simple cell formation problems. Evolved coefficients are tested against the well-known Jaccard's similarity coefficient on a large number of problems taken from the literature.