Advances in Sine Cosine Algorithm: A comprehensive survey

Laith Abualigah; Ali Diabat

doi:10.1007/s10462-020-09909-3

Advances in Sine Cosine Algorithm: A comprehensive survey

Laith Abualigah, Ali Diabat

Civil Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

The Sine Cosine Algorithm (SCA) is a population-based optimization algorithm introduced by Mirjalili in 2016, motivated by the trigonometric sine and cosine functions. After providing an overview of the SCA algorithm, we survey a number of SCA variants and applications that have appeared in the literature. We then present the results of a series of computational experiments to validate the performance of the SCA against similar algorithms.

Original language	English (US)
Journal	Artificial Intelligence Review
DOIs	https://doi.org/10.1007/s10462-020-09909-3
State	Accepted/In press - 2021

Keywords

Meta-heuristic optimization algorithms
Optimization problems
Population-based algorithms
Sine Cosine Algorithm

ASJC Scopus subject areas

Language and Linguistics
Linguistics and Language
Artificial Intelligence

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abstract = "The Sine Cosine Algorithm (SCA) is a population-based optimization algorithm introduced by Mirjalili in 2016, motivated by the trigonometric sine and cosine functions. After providing an overview of the SCA algorithm, we survey a number of SCA variants and applications that have appeared in the literature. We then present the results of a series of computational experiments to validate the performance of the SCA against similar algorithms.",

keywords = "Meta-heuristic optimization algorithms, Optimization problems, Population-based algorithms, Sine Cosine Algorithm",

author = "Laith Abualigah and Ali Diabat",

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KW - Optimization problems

KW - Population-based algorithms

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Advances in Sine Cosine Algorithm: A comprehensive survey

Abstract

Keywords

ASJC Scopus subject areas

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