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.

正余弦算法 (SCA) 是一种最近的元启发式算法，其灵感来自于三角正弦函数和余弦函数的特性。自 2016 年 Mirjalili 提出以来，SCA 引起了研究人员的极大关注，并被广泛用于解决多个领域的不同优化问题。与文献中可用的几种备受推崇的优化算法相比，这种关注是由于其合理的执行时间、良好的收敛加速率和高效率。本文简要概述了基本 SCA 及其变体，分为修改版、多目标版和混合版。此外，描述了SCA在分类、图像处理、机器人路径规划、调度、辐射分布网络和其他工程问题等多个领域的应用。