A comprehensive survey of sine cosine algorithm: variants and applications

Sine 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 SCA.

Automated summary

The Sine Cosine Algorithm (SCA) is a meta-heuristic algorithm inspired by trigonometric functions, known for its efficient execution time, good convergence rate, and high effectiveness in solving optimization problems. It has various variants including modified, multi-objective, and hybridized versions, and has been applied in diverse fields such as classification, image processing, robot path planning, scheduling, and radial distribution networks.