{"title":"基于多维搜索的混合矢量人工物理优化方法","authors":"Gangjun Yang, Liping Xie, Ying Tan, J. Zeng","doi":"10.1109/CASoN.2010.12","DOIUrl":null,"url":null,"abstract":"Artificial physics optimization algorithm (APO) is a new swarm intelligence algorithm to solve global optimization problem based on Physicomimetics framework. An n order diagonal matrix of shrinkage coefficient is introduced to ensure that each individual is within the decision space. Multi-dimensional search method is merged into the vector model of APO to improve the local exploitation capability of vector APO. The simulation results confirm that the performance of the hybrid vector APO with multi-dimensional search method is effective.","PeriodicalId":158080,"journal":{"name":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","volume":"599 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"A Hybrid Vector Artificial Physics Optimization with Multi-dimensional Search Method\",\"authors\":\"Gangjun Yang, Liping Xie, Ying Tan, J. Zeng\",\"doi\":\"10.1109/CASoN.2010.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial physics optimization algorithm (APO) is a new swarm intelligence algorithm to solve global optimization problem based on Physicomimetics framework. An n order diagonal matrix of shrinkage coefficient is introduced to ensure that each individual is within the decision space. Multi-dimensional search method is merged into the vector model of APO to improve the local exploitation capability of vector APO. The simulation results confirm that the performance of the hybrid vector APO with multi-dimensional search method is effective.\",\"PeriodicalId\":158080,\"journal\":{\"name\":\"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications\",\"volume\":\"599 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CASoN.2010.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Second International Conference on Innovations in Bio-inspired Computing and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CASoN.2010.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Hybrid Vector Artificial Physics Optimization with Multi-dimensional Search Method
Artificial physics optimization algorithm (APO) is a new swarm intelligence algorithm to solve global optimization problem based on Physicomimetics framework. An n order diagonal matrix of shrinkage coefficient is introduced to ensure that each individual is within the decision space. Multi-dimensional search method is merged into the vector model of APO to improve the local exploitation capability of vector APO. The simulation results confirm that the performance of the hybrid vector APO with multi-dimensional search method is effective.
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