A comprehensive survey of sine cosine algorithm: variants and applications

被引：74

作者：

Gabis, Asma Benmessaoud ^{[1
]}

Meraihi, Yassine ^{[2
]}

Mirjalili, Seyedali ^{[3
]}

Ramdane-Cherif, Amar ^{[4
]}

机构：

[1] Ecole Natl Super Informat, Lab Methodes Concept Syst, BP 68M, Oued Smar 16309, Alger, Algeria

[2] Univ MHamed Bougara Boumerdes, LIST Lab, Ave Independence, Boumerdes 35000, Algeria

[3] Torrens Univ Australia, Ctr Artificial Intelligence Res & Optimisat, Brisbane, Qld 4006, Australia

[4] Univ Versailles St Quentin En Yvelines, LISV Lab, 10-12 Ave Europe, F-78140 Velizy Villacoublay, France

来源：

ARTIFICIAL INTELLIGENCE REVIEW | 2021年 / 54卷 / 07期

关键词：

Sine Cosine Algorithm; Optimization; Population-based Algorithm; Meta-heuristics; META-HEURISTIC OPTIMIZATION; CENTRAL FORCE OPTIMIZATION; EXTREME LEARNING-MACHINE; SALP SWARM ALGORITHM; GLOBAL OPTIMIZATION; LOCAL SEARCH; LEVY FLIGHT; DIFFERENTIAL EVOLUTION; PARTICLE SWARM; HYBRID;

D O I：

10.1007/s10462-021-10026-y

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：5469 / 5540

页数：72

共 259 条

[1] An improved Opposition-Based Sine Cosine Algorithm for global optimization [J].

Abd Elaziz, Mohamed ;

Oliva, Diego ;

Xiong, Shengwu .

EXPERT SYSTEMS WITH APPLICATIONS, 2017, 90 :484-500

[2] A Hybrid Method of Sine Cosine Algorithm and Differential Evolution for Feature Selection [J].

Abd Elaziz, Mohamed E. ;

Ewees, Ahmed A. ;

Oliva, Diego ;

Duan, Pengfei ;

Xiong, Shengwu .

NEURAL INFORMATION PROCESSING, ICONIP 2017, PT V, 2017, 10638 :145-155

[3] Handwritten Arabic Manuscript Image Binarization Using Sine Cosine Optimization Algorithm [J].

Abd Elfattah, Mohamed ;

Abuelenin, Sherihan ;

Hassanien, Aboul Ella ;

Pan, Jeng-Shyang .

GENETIC AND EVOLUTIONARY COMPUTING, 2017, 536 :273-280

[4]

Abdel-Baset M., 2019, INT J MATH OPERATION, V14, P307, DOI [DOI 10.1504/IJMOR.2019.099381, 10.1504/IJMOR.2019.099381]

[5] EA-MSCA: An effective energy-aware multi-objective modified sine-cosine algorithm for real-time task scheduling in multiprocessor systems: Methods and analysis [J].

Abdel-Basset, Mohamed ;

Mohamed, Reda ;

Abouhawwash, Mohamed ;

Chakrabortty, Ripon K. ;

Ryan, Michael J. .

EXPERT SYSTEMS WITH APPLICATIONS, 2021, 173

[6]

Abdel-Fatah S, 2019, PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON INNOVATIVE TRENDS IN COMPUTER ENGINEERING (ITCE 2019), P510, DOI [10.1109/ITCE.2019.8646460, 10.1109/itce.2019.8646460]

[7] Optimal Distributed Energy Resources Allocation for Enriching Reliability and Economic Benefits Using Sine-Cosine Algorithm [J].

Abdelsalam, Abdelazeem A. .

TECHNOLOGY AND ECONOMICS OF SMART GRIDS AND SUSTAINABLE ENERGY, 2020, 5 (01)

[8] Optimal Allocation and Hourly Scheduling of Capacitor Banks Using Sine Cosine Algorithm for Maximizing Technical and Economic Benefits [J].

Abdelsalam, Abdelazeem A. ;

Mansour, Hany S. E. .

ELECTRIC POWER COMPONENTS AND SYSTEMS, 2019, 47 (11-12) :1025-1039

[9] Electromagnetic field optimization: A physics-inspired metaheuristic optimization algorithm [J].

Abedinpourshotorban, Hosein ;

Shamsuddin, Siti Mariyam ;

Beheshti, Zahra ;

Jawawi, Dayang N. A. .

SWARM AND EVOLUTIONARY COMPUTATION, 2016, 26 :8-22

[10] A novel feature selection method for data mining tasks using hybrid Sine Cosine Algorithm and Genetic Algorithm [J].

Abualigah, Laith ;

Dulaimi, Akram Jamal .

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2021, 24 (03) :2161-2176

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