Meraihi, YassineGabis, Asma BenmessaoudRamdane-Cherif, AmarAcheli, Dalila2023-04-032023-04-032023978-303119522-825228595DOI 10.1007/978-3-031-19523-5_7https://link.springer.com/chapter/10.1007/978-3-031-19523-5_7https://dspace.univ-boumerdes.dz/handle/123456789/11267Coyote 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 COAenAlgorithm optimizationCoyote Optimization Algorithm (COA)Meta-heuristicsPopulation-basedOther