{"title":"基于林登迈尔系统的分层遗传策略建模","authors":"J. Kolodziej","doi":"10.1109/PCEE.2002.1115312","DOIUrl":null,"url":null,"abstract":"A hierarchical genetic strategy is an effective tool in solving ill posed global optimization problems. We use a context-sensitive stochastic Lindenmayer system to describe the structure of HGS. The results of simple numerical experiments are reported. We try to use this strategy in robot motion planning.","PeriodicalId":444003,"journal":{"name":"Proceedings. International Conference on Parallel Computing in Electrical Engineering","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Modeling hierarchical genetic strategy as a Lindenmayer system\",\"authors\":\"J. Kolodziej\",\"doi\":\"10.1109/PCEE.2002.1115312\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A hierarchical genetic strategy is an effective tool in solving ill posed global optimization problems. We use a context-sensitive stochastic Lindenmayer system to describe the structure of HGS. The results of simple numerical experiments are reported. We try to use this strategy in robot motion planning.\",\"PeriodicalId\":444003,\"journal\":{\"name\":\"Proceedings. International Conference on Parallel Computing in Electrical Engineering\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. International Conference on Parallel Computing in Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PCEE.2002.1115312\",\"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. International Conference on Parallel Computing in Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCEE.2002.1115312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling hierarchical genetic strategy as a Lindenmayer system
A hierarchical genetic strategy is an effective tool in solving ill posed global optimization problems. We use a context-sensitive stochastic Lindenmayer system to describe the structure of HGS. The results of simple numerical experiments are reported. We try to use this strategy in robot motion planning.