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| Titre: | Advances in coyote optimization algorithm : variants and applications |
| Auteur(s): | Meraihi, Yassine
Gabis, Asma Benmessaoud
Ramdane-Cherif, Amar
Acheli, Dalila |
| Mots-clés: | Algorithm optimization
Coyote Optimization Algorithm (COA)
Meta-heuristics
Population-based |
| Date de publication: | 2023 |
| Editeur: | Springer |
| Collection/Numéro: | EAI/Springer Innovations in Communication and Computing/ (2023);pp. 99-113 |
| Résumé: | Coyote Optimization Algorithm (COA) is a recent population-based technique inspired by the attitude of coyotes in nature. COA has been widely applied to tackle different optimization issues in several areas and has proved its successfulness compared to several methods found in the literature. In this paper, we describe a brief overview of COA and its variants including adjusted and hybridized versions. Additionally, we present COA applications in various fields such as image segmentation, wireless mesh networks, economic dispatch, electric power systems, distributed generation, and other engineering issues. Finally, we recommend some interesting future research areas directions for COA |
| URI/URL: | DOI 10.1007/978-3-031-19523-5_7
https://link.springer.com/chapter/10.1007/978-3-031-19523-5_7
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/11267 |
| ISBN: | 978-303119522-8 |
| ISSN: | 25228595 |
| Collection(s) : | Communications Internationales
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