Recent Advances in Butterfly Optimization Algorithm, Its Versions and Applications Recent Advances in Butterfly Optimization Algorithm, Its Versions and Applications

The butterfly optimization algorithm (BOA) is a recent successful metaheuristic swarm-based optimization algorithm. The BOA has attracted scholars’ attention due to its extraordinary features. Such as the few adaptive parameters to handle and the high balance between exploration and exploitation. Ac...

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Published inArchives of computational methods in engineering Vol. 30; no. 2; pp. 1399 - 1420
Main Authors Makhadmeh, Sharif Naser, Al-Betar, Mohammed Azmi, Abasi, Ammar Kamal, Awadallah, Mohammed A., Doush, Iyad Abu, Alyasseri, Zaid Abdi Alkareem, Alomari, Osama Ahmad
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.03.2023
Springer Nature B.V
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Summary:The butterfly optimization algorithm (BOA) is a recent successful metaheuristic swarm-based optimization algorithm. The BOA has attracted scholars’ attention due to its extraordinary features. Such as the few adaptive parameters to handle and the high balance between exploration and exploitation. Accordingly, the BOA has been extensively adapted for various optimization problems in different domains in a short period. Therefore, this paper reviews and summarizes the recently published studies that utilized the BOA for optimization problems. Initially, introductory information about the BOA is presented to illustrate the essential foundation and its relevant optimization concepts. In addition, the BOA inspiration and its mathematical model are provided with an illustrative example to prove its high capabilities. Subsequently, all reviewed studies are classified into three main classes based on the adaptation form, including original, modified, and hybridized. The main BOA applications are also thoroughly explained. Furthermore, the BOA advantages and drawbacks in dealing with optimization problems are analyzed. Finally, the paper is summarized in conclusion with the future directions that can be investigated further.
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ISSN:1134-3060
1886-1784
1886-1784
DOI:10.1007/s11831-022-09843-3