{"title":"Hybridized krill herd algorithm for large-scale optimization problems","authors":"Ivana Stromberger, N. Bačanin, M. Tuba","doi":"10.1109/SAMI.2017.7880356","DOIUrl":null,"url":null,"abstract":"In this paper we applied the krill herd algorithm hybridized with the firefly algorithm to bound-constrained large-scale optimization problems. We tested basic krill herd algorithm and basic firefly algorithm on the standard set of benchmark functions. The results were acceptable. Then, we hybridized the krill herd algorithm with the firefly algorithm by applying firefly algorithm's search equation to the original krill herd algorithm implementation. We tested the robustness and effectiveness of our hybridized algorithm on the same large-scale numerical benchmarks with different dimensionality in order to make comparative analysis and to measure optimization enhancements of our approach. Testing results proved that our proposed hybridized implementation improved results almost uniformly and that it has significant potential when dealing with global optimization problems.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2017.7880356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper we applied the krill herd algorithm hybridized with the firefly algorithm to bound-constrained large-scale optimization problems. We tested basic krill herd algorithm and basic firefly algorithm on the standard set of benchmark functions. The results were acceptable. Then, we hybridized the krill herd algorithm with the firefly algorithm by applying firefly algorithm's search equation to the original krill herd algorithm implementation. We tested the robustness and effectiveness of our hybridized algorithm on the same large-scale numerical benchmarks with different dimensionality in order to make comparative analysis and to measure optimization enhancements of our approach. Testing results proved that our proposed hybridized implementation improved results almost uniformly and that it has significant potential when dealing with global optimization problems.