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Recent Advances in Butterfly Optimization Algorithm, Its Versions and Applications.
Makhadmeh, Sharif Naser; Al-Betar, Mohammed Azmi; Abasi, Ammar Kamal; Awadallah, Mohammed A; Doush, Iyad Abu; Alyasseri, Zaid Abdi Alkareem; Alomari, Osama Ahmad.
Afiliación
  • Makhadmeh SN; Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates.
  • Al-Betar MA; Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates.
  • Abasi AK; Machine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, United Arab Emirates.
  • Awadallah MA; Department of Computer Science, Al-Aqsa University, P.O. Box 4051, Gaza, Palestine.
  • Doush IA; Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, United Arab Emirates.
  • Alyasseri ZAA; Computing Department, College of Engineering and Applied Sciences, American University of Kuwait, Salmiya, Kuwait.
  • Alomari OA; Computer Science Department, Yarmouk University, Irbid, Jordan.
Arch Comput Methods Eng ; 30(2): 1399-1420, 2023.
Article en En | MEDLINE | ID: mdl-36348702
ABSTRACT
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.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Arch Comput Methods Eng Año: 2023 Tipo del documento: Article País de afiliación: Emiratos Árabes Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Arch Comput Methods Eng Año: 2023 Tipo del documento: Article País de afiliación: Emiratos Árabes Unidos