A Comprehensive Survey of Sine Cosine Algorithm: Variants and Applications

Overview

Journal Artif Intell Rev

Publisher Springer

Date 2021 Jun 7

PMID 34092884

Citations 44

Authors

Asma Benmessaoud Gabis

Yassine Meraihi

Seyedali Mirjalili

Amar Ramdane-Cherif

Affiliations

Soon will be listed here.

Abstract

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.

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References

Gabis A, Meraihi Y, Mirjalili S, Ramdane-Cherif A . A comprehensive survey of sine cosine algorithm: variants and applications. Artif Intell Rev. 2021; 54(7):5469-5540. PMC: 8171367. DOI: 10.1007/s10462-021-10026-y. View

Kirkpatrick S, Gelatt Jr C, Vecchi M . Optimization by simulated annealing. Science. 1983; 220(4598):671-80. DOI: 10.1126/science.220.4598.671. View

Elaziz M, Ewees A, Yousri D, Alwerfali H, Awad Q, Lu S . An Improved Marine Predators Algorithm With Fuzzy Entropy for Multi-Level Thresholding: Real World Example of COVID-19 CT Image Segmentation. IEEE Access. 2021; 8:125306-125330. PMC: 8043509. DOI: 10.1109/ACCESS.2020.3007928. View

Issa M . Expeditious COVID-19 similarity measure tool based on consolidated SCA algorithm with mutation and opposition operators. Appl Soft Comput. 2021; 104:107197. PMC: 7895693. DOI: 10.1016/j.asoc.2021.107197. View

Qu C, Zeng Z, Dai J, Yi Z, He W . A Modified Sine-Cosine Algorithm Based on Neighborhood Search and Greedy Levy Mutation. Comput Intell Neurosci. 2018; 2018:4231647. PMC: 6057408. DOI: 10.1155/2018/4231647. View