Jia-Hao Zhang, Zheng-Ming Gao, Suruo Li, Juan Zhao
{"title":"Improved Mayfly Optimization Algorithm with Cooperation","authors":"Jia-Hao Zhang, Zheng-Ming Gao, Suruo Li, Juan Zhao","doi":"10.1109/icccs55155.2022.9846576","DOIUrl":null,"url":null,"abstract":"The mayfly optimization algorithm (MA) is a stochastic, population-based optimization technique that can be applied to a wide range of problems. To improve the optimization performance of mayfly optimization algorithm, a variation on the mayfly algorithm, called the improved mayfly optimization algorithm with cooperation, or MAC, was proposed in this paper, employing cooperative behavior. This is achieved by using multiple male populations to optimize different components of the solution vector cooperatively. Application of the MAC on several benchmark optimization problems shows a marked improvement in performance over the original algorithm.","PeriodicalId":121713,"journal":{"name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icccs55155.2022.9846576","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The mayfly optimization algorithm (MA) is a stochastic, population-based optimization technique that can be applied to a wide range of problems. To improve the optimization performance of mayfly optimization algorithm, a variation on the mayfly algorithm, called the improved mayfly optimization algorithm with cooperation, or MAC, was proposed in this paper, employing cooperative behavior. This is achieved by using multiple male populations to optimize different components of the solution vector cooperatively. Application of the MAC on several benchmark optimization problems shows a marked improvement in performance over the original algorithm.