{"title":"基于布谷鸟-宿主协同进化元启发式的复杂基准函数全局优化","authors":"Sudhanshu K. Mishra","doi":"10.2139/SSRN.2128079","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel method of global optimization based on cuckoo-host co-evaluation. It also develops a Fortran-77 code for the algorithm. The algorithm has been tested on 96 benchmark functions (of which the results of 30 relatively harder problems have been reported). The proposed method is comparable to the Differential Evolution method of global optimization.","PeriodicalId":10688,"journal":{"name":"Computing Technologies eJournal","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Global Optimization of Some Difficult Benchmark Functions by Cuckoo-Host Co-Evolution Meta-Heuristics\",\"authors\":\"Sudhanshu K. Mishra\",\"doi\":\"10.2139/SSRN.2128079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel method of global optimization based on cuckoo-host co-evaluation. It also develops a Fortran-77 code for the algorithm. The algorithm has been tested on 96 benchmark functions (of which the results of 30 relatively harder problems have been reported). The proposed method is comparable to the Differential Evolution method of global optimization.\",\"PeriodicalId\":10688,\"journal\":{\"name\":\"Computing Technologies eJournal\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computing Technologies eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/SSRN.2128079\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computing Technologies eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/SSRN.2128079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Global Optimization of Some Difficult Benchmark Functions by Cuckoo-Host Co-Evolution Meta-Heuristics
This paper proposes a novel method of global optimization based on cuckoo-host co-evaluation. It also develops a Fortran-77 code for the algorithm. The algorithm has been tested on 96 benchmark functions (of which the results of 30 relatively harder problems have been reported). The proposed method is comparable to the Differential Evolution method of global optimization.
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