Gabis Asma Benmessaoud, Meraihi Yassine, Mirjalili Seyedali, Ramdane-Cherif Amar
Ecole nationale Supérieure d'Informatique, Laboratoire des Méthodes de Conception des Systèmes, BP 68M, 16309 Oued-Smar, Alger Algeria.
LIST Laboratory, University of M'Hamed Bougara Boumerdes, Avenue of Independence, 35000 Boumerdes, Algeria.
Artif Intell Rev. 2021;54(7):5469-5540. doi: 10.1007/s10462-021-10026-y. Epub 2021 Jun 2.
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.
正弦余弦算法(SCA)是一种最近受到三角函数正弦和余弦函数特性启发的元启发式算法。自2016年米尔贾利利提出以来,SCA已引起研究人员的极大关注,并已广泛用于解决多个领域中的不同优化问题。这种关注归因于其合理的执行时间、良好的收敛加速率以及与文献中几种备受关注的优化算法相比的高效率。本文简要概述了基本的SCA及其变体,分为改进版、多目标版和杂交版。此外,还描述了SCA在分类、图像处理、机器人路径规划、调度、径向配电网以及其他工程问题等多个领域的应用。最后,本文为SCA推荐了一些潜在的未来研究方向。