Recent advances in Grey Wolf Optimizer, its versions and applications: Review
The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO’s appeal lies in its remarkable characteristics: it is parameter-free, derivative-free, conceptually simple, user-friendly, adaptable,...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , , , |
| منشور في: |
2023
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://depot.sorbonne.ae/handle/20.500.12458/1433 |
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| _version_ | 1857415063536664576 |
|---|---|
| author | Abu Zitar, Raed |
| author2 | Makhadmeh, Sharif Naser Al-Betar, Mohammed Azmi Abu Doush, Iyad Awadallah, Mohammed A. Kassaymeh, Sofian Mirjalili, Seyedali |
| author2_role | author author author author author author |
| author_facet | Abu Zitar, Raed Makhadmeh, Sharif Naser Al-Betar, Mohammed Azmi Abu Doush, Iyad Awadallah, Mohammed A. Kassaymeh, Sofian Mirjalili, Seyedali |
| author_role | author |
| dc.creator.none.fl_str_mv | Abu Zitar, Raed Makhadmeh, Sharif Naser Al-Betar, Mohammed Azmi Abu Doush, Iyad Awadallah, Mohammed A. Kassaymeh, Sofian Mirjalili, Seyedali |
| dc.date.none.fl_str_mv | 2023-08-15T09:37:04Z 2023-08-15T09:37:04Z 2023 |
| dc.identifier.none.fl_str_mv | 2169-3536 https://depot.sorbonne.ae/handle/20.500.12458/1433 10.1109/ACCESS.2023.3304889 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | IEEE Access |
| dc.subject.none.fl_str_mv | Grey wolf Optimizer Swarm Intelligence Optimization Evolutionary Computation |
| dc.title.none.fl_str_mv | Recent advances in Grey Wolf Optimizer, its versions and applications: Review |
| dc.type.none.fl_str_mv | Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal article |
| description | The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO’s appeal lies in its remarkable characteristics: it is parameter-free, derivative-free, conceptually simple, user-friendly, adaptable, flexible, and robust. Its efficacy has been demonstrated across a wide range of optimization problems in diverse domains, including engineering, bioinformatics, biomedical, scheduling and planning, and business. Given the substantial growth and effectiveness of GWO, it is essential to conduct a recent review to provide updated insights. This review delves into the GWO-related research conducted between 2019 and 2022, encompassing over 200 research articles. It explores the growth of GWO in terms of publications, citations, and the domains that leverage its potential. The review thoroughly examines the latest versions of GWO, categorizing them based on their contributions. Additionally, it highlights the primary applications of GWO, with computer science and engineering emerging as the dominant research domains. A critical analysis of the accomplishments and limitations of GWO is presented, offering valuable insights. Finally, the review concludes with a brief summary and outlines potential future developments in GWO theory and applications. Researchers seeking to employ GWO as a problem-solving tool will find this comprehensive review immensely beneficial in advancing their research endeavors. |
| id | sorbonner_3e87baba8f3923be784566b6d2bd7123 |
| identifier_str_mv | 2169-3536 10.1109/ACCESS.2023.3304889 |
| language_invalid_str_mv | en |
| network_acronym_str | sorbonner |
| network_name_str | Sorbonne University Abu Dhabi repository |
| oai_identifier_str | oai:depot.sorbonne.ae:20.500.12458/1433 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Recent advances in Grey Wolf Optimizer, its versions and applications: ReviewAbu Zitar, RaedMakhadmeh, Sharif NaserAl-Betar, Mohammed AzmiAbu Doush, IyadAwadallah, Mohammed A.Kassaymeh, SofianMirjalili, SeyedaliGrey wolf OptimizerSwarm IntelligenceOptimizationEvolutionary ComputationThe Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO’s appeal lies in its remarkable characteristics: it is parameter-free, derivative-free, conceptually simple, user-friendly, adaptable, flexible, and robust. Its efficacy has been demonstrated across a wide range of optimization problems in diverse domains, including engineering, bioinformatics, biomedical, scheduling and planning, and business. Given the substantial growth and effectiveness of GWO, it is essential to conduct a recent review to provide updated insights. This review delves into the GWO-related research conducted between 2019 and 2022, encompassing over 200 research articles. It explores the growth of GWO in terms of publications, citations, and the domains that leverage its potential. The review thoroughly examines the latest versions of GWO, categorizing them based on their contributions. Additionally, it highlights the primary applications of GWO, with computer science and engineering emerging as the dominant research domains. A critical analysis of the accomplishments and limitations of GWO is presented, offering valuable insights. Finally, the review concludes with a brief summary and outlines potential future developments in GWO theory and applications. Researchers seeking to employ GWO as a problem-solving tool will find this comprehensive review immensely beneficial in advancing their research endeavors.2023-08-15T09:37:04Z2023-08-15T09:37:04Z2023Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal article2169-3536https://depot.sorbonne.ae/handle/20.500.12458/143310.1109/ACCESS.2023.3304889enIEEE Accessoai:depot.sorbonne.ae:20.500.12458/14332023-11-28T15:34:41Z |
| spellingShingle | Recent advances in Grey Wolf Optimizer, its versions and applications: Review Abu Zitar, Raed Grey wolf Optimizer Swarm Intelligence Optimization Evolutionary Computation |
| title | Recent advances in Grey Wolf Optimizer, its versions and applications: Review |
| title_full | Recent advances in Grey Wolf Optimizer, its versions and applications: Review |
| title_fullStr | Recent advances in Grey Wolf Optimizer, its versions and applications: Review |
| title_full_unstemmed | Recent advances in Grey Wolf Optimizer, its versions and applications: Review |
| title_short | Recent advances in Grey Wolf Optimizer, its versions and applications: Review |
| title_sort | Recent advances in Grey Wolf Optimizer, its versions and applications: Review |
| topic | Grey wolf Optimizer Swarm Intelligence Optimization Evolutionary Computation |
| url | https://depot.sorbonne.ae/handle/20.500.12458/1433 |