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| Titre: | Grasshopper Optimization Algorithm: Theory, Variants, and Applications |
| Auteur(s): | Meraihi, Yassine
Benmessaoud Gabis, Asma
Seyedali, Mirjalili
Amar Ramdane, Cherif |
| Mots-clés: | Grasshopper optimization algorithm
GOA
Meta-heuristics
Optimization
Population- based algorithm
Swarm intelligence |
| Date de publication: | 2021 |
| Editeur: | IEEE |
| Résumé: | Grasshopper Optimization Algorithm (GOA) is a recent swarm intelligence algorithm inspired
by the foraging and swarming behavior of grasshoppers in nature. The GOA algorithm has been successfully
applied to solve various optimization problems in several domains and demonstrated its merits in the
literature. This paper proposes a comprehensive review of GOA based on more than 120 scientific articles
published by leading publishers: IEEE, Springer, Elsevier, IET, Hindawi, and others. It provides the GOA
variants, including multi-objective and hybrid variants. It also discusses the main applications of GOA in
various fields such as scheduling, economic dispatch, feature selection, load frequency control, distributed
generation, wind energy system, and other engineering problems. Finally, the paper provides some possible
future research directions in this area. |
| URI/URL: | http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/7162 |
| Collection(s) : | Publications Internationales
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