T. Kadavy, Michal Pluhacek, Adam Viktorin, R. Šenkeřík
{"title":"探索元启发式算法中边界控制方法激活的频率","authors":"T. Kadavy, Michal Pluhacek, Adam Viktorin, R. Šenkeřík","doi":"10.1145/3583133.3596418","DOIUrl":null,"url":null,"abstract":"Recently, Boundary Control Methods (BCMs) have become increasingly relevant in the field of metaheuristic algorithms. In this study, we investigate the relationship between the activation frequency of different BCMs and the problem's dimensionality. Additionally, we analyze each problem dimension independently. Our research primarily concentrates on the top three algorithms from the IEEE CEC 2020 competition: AGSK, IMODE, and j2020, utilizing the competition benchmark set to conduct experiments. Our findings provide valuable insights into the metaheuristic domain, underlining the significance of comprehending BCM activation patterns to improve algorithm design and benchmarking practices.","PeriodicalId":422029,"journal":{"name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring the Frequency of Boundary Control Methods Activation in Metaheuristic Algorithms\",\"authors\":\"T. Kadavy, Michal Pluhacek, Adam Viktorin, R. Šenkeřík\",\"doi\":\"10.1145/3583133.3596418\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, Boundary Control Methods (BCMs) have become increasingly relevant in the field of metaheuristic algorithms. In this study, we investigate the relationship between the activation frequency of different BCMs and the problem's dimensionality. Additionally, we analyze each problem dimension independently. Our research primarily concentrates on the top three algorithms from the IEEE CEC 2020 competition: AGSK, IMODE, and j2020, utilizing the competition benchmark set to conduct experiments. Our findings provide valuable insights into the metaheuristic domain, underlining the significance of comprehending BCM activation patterns to improve algorithm design and benchmarking practices.\",\"PeriodicalId\":422029,\"journal\":{\"name\":\"Proceedings of the Companion Conference on Genetic and Evolutionary Computation\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Companion Conference on Genetic and Evolutionary Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3583133.3596418\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3583133.3596418","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exploring the Frequency of Boundary Control Methods Activation in Metaheuristic Algorithms
Recently, Boundary Control Methods (BCMs) have become increasingly relevant in the field of metaheuristic algorithms. In this study, we investigate the relationship between the activation frequency of different BCMs and the problem's dimensionality. Additionally, we analyze each problem dimension independently. Our research primarily concentrates on the top three algorithms from the IEEE CEC 2020 competition: AGSK, IMODE, and j2020, utilizing the competition benchmark set to conduct experiments. Our findings provide valuable insights into the metaheuristic domain, underlining the significance of comprehending BCM activation patterns to improve algorithm design and benchmarking practices.