{"title":"集群重启DM:新的全局优化算法","authors":"M. Dlapa","doi":"10.1109/INTELLISYS.2017.8324271","DOIUrl":null,"url":null,"abstract":"Global optimisation method Differential Migration (DM) with restarting is described in this paper and evaluated together with Restart Covariance Matrix Adaptation Evolution Strategy With Increasing Population Size (IPOP-CMA-ES). Differential Migration is another step in global optimisation from SOMA (Self-Organizing Migration Algorithm) combining two basic individual movement methods of SOMA — all-to-one and all-to-all, via cluster analysis and internal algorithm constant defining continuous change from one type of movement to another. The proposed algorithm implements essential ideas of Differential Evolution regardless of their original interpretation in living nature with subsequent increase of efficiency in finding global extreme which holds mainly for noisy multimodal cost functions present in the benchmarks as well as in real world applications.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Cluster restarted DM: New algorithm for global optimisation\",\"authors\":\"M. Dlapa\",\"doi\":\"10.1109/INTELLISYS.2017.8324271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Global optimisation method Differential Migration (DM) with restarting is described in this paper and evaluated together with Restart Covariance Matrix Adaptation Evolution Strategy With Increasing Population Size (IPOP-CMA-ES). Differential Migration is another step in global optimisation from SOMA (Self-Organizing Migration Algorithm) combining two basic individual movement methods of SOMA — all-to-one and all-to-all, via cluster analysis and internal algorithm constant defining continuous change from one type of movement to another. The proposed algorithm implements essential ideas of Differential Evolution regardless of their original interpretation in living nature with subsequent increase of efficiency in finding global extreme which holds mainly for noisy multimodal cost functions present in the benchmarks as well as in real world applications.\",\"PeriodicalId\":131825,\"journal\":{\"name\":\"2017 Intelligent Systems Conference (IntelliSys)\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Intelligent Systems Conference (IntelliSys)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INTELLISYS.2017.8324271\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Intelligent Systems Conference (IntelliSys)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTELLISYS.2017.8324271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cluster restarted DM: New algorithm for global optimisation
Global optimisation method Differential Migration (DM) with restarting is described in this paper and evaluated together with Restart Covariance Matrix Adaptation Evolution Strategy With Increasing Population Size (IPOP-CMA-ES). Differential Migration is another step in global optimisation from SOMA (Self-Organizing Migration Algorithm) combining two basic individual movement methods of SOMA — all-to-one and all-to-all, via cluster analysis and internal algorithm constant defining continuous change from one type of movement to another. The proposed algorithm implements essential ideas of Differential Evolution regardless of their original interpretation in living nature with subsequent increase of efficiency in finding global extreme which holds mainly for noisy multimodal cost functions present in the benchmarks as well as in real world applications.