{"title":"异种变长基因型的进化优化","authors":"S. Sakka","doi":"10.1109/ROMOCO.2004.240570","DOIUrl":null,"url":null,"abstract":"This paper deals with evolutionary programming for optimization problems. The algorithm manipulates chromosomes of which genotypes contains heterogeneous data (integer and float numbers), depending on each other. Moreover, length of the chromosomes is different within a common evolution. The evolutionary algorithm is described and optimization results are compared to the previously implemented methodology. Stability of the algorithm facing a change of problem dimensions is also tested and discussed.","PeriodicalId":176081,"journal":{"name":"Proceedings of the Fourth International Workshop on Robot Motion and Control (IEEE Cat. No.04EX891)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Heterogeneous variable-length genotypes for evolutionary optimization\",\"authors\":\"S. Sakka\",\"doi\":\"10.1109/ROMOCO.2004.240570\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with evolutionary programming for optimization problems. The algorithm manipulates chromosomes of which genotypes contains heterogeneous data (integer and float numbers), depending on each other. Moreover, length of the chromosomes is different within a common evolution. The evolutionary algorithm is described and optimization results are compared to the previously implemented methodology. Stability of the algorithm facing a change of problem dimensions is also tested and discussed.\",\"PeriodicalId\":176081,\"journal\":{\"name\":\"Proceedings of the Fourth International Workshop on Robot Motion and Control (IEEE Cat. No.04EX891)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fourth International Workshop on Robot Motion and Control (IEEE Cat. No.04EX891)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROMOCO.2004.240570\",\"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 Fourth International Workshop on Robot Motion and Control (IEEE Cat. No.04EX891)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROMOCO.2004.240570","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Heterogeneous variable-length genotypes for evolutionary optimization
This paper deals with evolutionary programming for optimization problems. The algorithm manipulates chromosomes of which genotypes contains heterogeneous data (integer and float numbers), depending on each other. Moreover, length of the chromosomes is different within a common evolution. The evolutionary algorithm is described and optimization results are compared to the previously implemented methodology. Stability of the algorithm facing a change of problem dimensions is also tested and discussed.