{"title":"大规模全局优化的自适应协同进化","authors":"Yu Wang, Bin Li, Zhengdong Li","doi":"10.1109/YCICT.2010.5713074","DOIUrl":null,"url":null,"abstract":"Large-scale global optimization (LSGO) is a very important and challenging task in optimization domain, which is embedded in many scientific and engineering applications. Previously, the cooperative co-evolution (CC) is a usual and effective choice for LSGO problems. In this paper, aim at more fully exploring the flexibility and potential of CC strategy, an adaptive CC (ACC) is designed to handle LSGO problems. The advantages of ACC compared with the classical CC strategies are experimentally verified on a set of widely used large scale function optimization problems.","PeriodicalId":179847,"journal":{"name":"2010 IEEE Youth Conference on Information, Computing and Telecommunications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Adaptive cooperative co-evolution for large scale global optimization\",\"authors\":\"Yu Wang, Bin Li, Zhengdong Li\",\"doi\":\"10.1109/YCICT.2010.5713074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Large-scale global optimization (LSGO) is a very important and challenging task in optimization domain, which is embedded in many scientific and engineering applications. Previously, the cooperative co-evolution (CC) is a usual and effective choice for LSGO problems. In this paper, aim at more fully exploring the flexibility and potential of CC strategy, an adaptive CC (ACC) is designed to handle LSGO problems. The advantages of ACC compared with the classical CC strategies are experimentally verified on a set of widely used large scale function optimization problems.\",\"PeriodicalId\":179847,\"journal\":{\"name\":\"2010 IEEE Youth Conference on Information, Computing and Telecommunications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Youth Conference on Information, Computing and Telecommunications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/YCICT.2010.5713074\",\"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 IEEE Youth Conference on Information, Computing and Telecommunications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YCICT.2010.5713074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
摘要
大规模全局优化(Large-scale global optimization, LSGO)是优化领域中一项非常重要且具有挑战性的任务，在许多科学和工程应用中都有广泛的应用。以往，合作协同进化(CC)是解决LSGO问题的一种常用而有效的选择。为了更充分地挖掘CC策略的灵活性和潜力，本文设计了一种自适应CC (ACC)来处理LSGO问题。在一组广泛应用的大规模函数优化问题上，实验验证了ACC策略相对于经典CC策略的优势。
Adaptive cooperative co-evolution for large scale global optimization
Large-scale global optimization (LSGO) is a very important and challenging task in optimization domain, which is embedded in many scientific and engineering applications. Previously, the cooperative co-evolution (CC) is a usual and effective choice for LSGO problems. In this paper, aim at more fully exploring the flexibility and potential of CC strategy, an adaptive CC (ACC) is designed to handle LSGO problems. The advantages of ACC compared with the classical CC strategies are experimentally verified on a set of widely used large scale function optimization problems.
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