{"title":"基于混合差分进化和粒子群优化算法的几何约束求解","authors":"Wan Yi, C. Cao, Changsheng Zhang","doi":"10.1109/ICICIP.2010.5565290","DOIUrl":null,"url":null,"abstract":"Geometric constraint problem is equivalent to the problem of solving a set of nonlinear equations substantially. The constraint problem can be transformed to an optimization problem. We can solve the problem with a novel hybrid algorithm DE-PSO, which is proposed combining the particle swarm optimization (PSO) algorithm with differential evolution (DE) operators. It incorporates concepts from DE and PSO, updating particle not only by DE operators but also by mechanisms of PSO. The experiment shows that it can solve geometric constraint problems efficiently.","PeriodicalId":152024,"journal":{"name":"2010 International Conference on Intelligent Control and Information Processing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The geometric constraint solving based on hybrid differential evolution and particle swarm optimization algorithm\",\"authors\":\"Wan Yi, C. Cao, Changsheng Zhang\",\"doi\":\"10.1109/ICICIP.2010.5565290\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Geometric constraint problem is equivalent to the problem of solving a set of nonlinear equations substantially. The constraint problem can be transformed to an optimization problem. We can solve the problem with a novel hybrid algorithm DE-PSO, which is proposed combining the particle swarm optimization (PSO) algorithm with differential evolution (DE) operators. It incorporates concepts from DE and PSO, updating particle not only by DE operators but also by mechanisms of PSO. The experiment shows that it can solve geometric constraint problems efficiently.\",\"PeriodicalId\":152024,\"journal\":{\"name\":\"2010 International Conference on Intelligent Control and Information Processing\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Intelligent Control and Information Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICIP.2010.5565290\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Intelligent Control and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP.2010.5565290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The geometric constraint solving based on hybrid differential evolution and particle swarm optimization algorithm
Geometric constraint problem is equivalent to the problem of solving a set of nonlinear equations substantially. The constraint problem can be transformed to an optimization problem. We can solve the problem with a novel hybrid algorithm DE-PSO, which is proposed combining the particle swarm optimization (PSO) algorithm with differential evolution (DE) operators. It incorporates concepts from DE and PSO, updating particle not only by DE operators but also by mechanisms of PSO. The experiment shows that it can solve geometric constraint problems efficiently.