A comprehensive survey of sine cosine algorithm : variants and applications

dc.contributor.authorBenmessaoud Gabis, Asma
dc.contributor.authorMeraihi, Yassine
dc.contributor.authorMirjalili, Seyedali
dc.contributor.authorRamdane‑Cherif, Amar
dc.date.accessioned2021-06-29T08:16:09Z
dc.date.available2021-06-29T08:16:09Z
dc.date.issued2021
dc.description.abstractSine Cosine Algorithm (SCA) is a recent meta-heuristic algorithm inspired by the proprieties of trigonometric sine and cosine functions. Since its introduction by Mirjalili in 2016, SCA has attracted great attention from researchers and has been widely used to solve different optimization problems in several fields. This attention is due to its reasonable execution time, good convergence acceleration rate, and high efficiency compared to several well-regarded optimization algorithms available in the literature. This paper presents a brief overview of the basic SCA and its variants divided into modified, multi-objective, and hybridized versions. Furthermore, the applications of SCA in several domains such as classification, image processing, robot path planning, scheduling, radial distribution networks, and other engineering problems are described. Finally, the paper recommended some potential future research directions for SCAen_US
dc.identifier.issn0269-2821
dc.identifier.issn1573-7462 Electronic
dc.identifier.urihttps://link.springer.com/article/10.1007/s10462-021-10026-y
dc.identifier.urihttps://doi.org/10.1007/s10462-021-10026-y
dc.identifier.urihttps://dspace.univ-boumerdes.dz/handle/123456789/7057
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofseriesArtificial Intelligence Review/ (2021);pp. 1-72
dc.subjectMeta-heuristicsen_US
dc.subjectOptimizationen_US
dc.subjectPopulation-based Algorithmen_US
dc.subjectSine Cosine Algorithmen_US
dc.titleA comprehensive survey of sine cosine algorithm : variants and applicationsen_US
dc.typeArticleen_US

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