Circle Search Algorithm: A Geometry-Based Metaheuristic Optimization Algorithm

This paper presents a novel metaheuristic optimization algorithm inspired by the geometrical features of circles, called the circle search algorithm (CSA). The circle is the most well-known geometric object, with various features including diameter, center, perimeter, and tangent lines. The ratio be...

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Detalles Bibliográficos
Autores: Qais, Mohammed H., Hasanien, Hany M., Turky, Rania A., Alghuwainem, Saad, Tostado-Véliz, Marcos, Jurado-Melguizo, Francisco
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2022
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/3587
Acceso en línea:https://www.mdpi.com/2227-7390/10/10/1626
https://hdl.handle.net/10953/3587
Access Level:acceso abierto
Palabra clave:Algorithms
Circle search algorithm
Metaheuristics
Numerical optimization
Optimization methods
id ES_b956df9ea1bbcb2ced8e6b69745e0620
oai_identifier_str oai:ruja.ujaen.es:10953/3587
network_acronym_str ES
network_name_str España
repository_id_str
spelling Circle Search Algorithm: A Geometry-Based Metaheuristic Optimization AlgorithmQais, Mohammed H.Hasanien, Hany M.Turky, Rania A.Alghuwainem, SaadTostado-Véliz, MarcosJurado-Melguizo, FranciscoAlgorithmsCircle search algorithmMetaheuristicsNumerical optimizationOptimization methodsThis paper presents a novel metaheuristic optimization algorithm inspired by the geometrical features of circles, called the circle search algorithm (CSA). The circle is the most well-known geometric object, with various features including diameter, center, perimeter, and tangent lines. The ratio between the radius and the tangent line segment is the orthogonal function of the angle opposite to the orthogonal radius. This angle plays an important role in the exploration and exploitation behavior of the CSA. To evaluate the robustness of the CSA in comparison to other algorithms, many independent experiments employing 23 famous functions and 3 real engineering problems were carried out. The statistical results revealed that the CSA succeeded in achieving the minimum fitness values for 21 out of the tested 23 functions, and the p-value was less than 0.05. The results evidence that the CSA converged to the minimum results faster than the comparative algorithms. Furthermore, high-dimensional functions were used to assess the CSA’s robustness, with statistical results revealing that the CSA is robust to high-dimensional problems. As a result, the proposed CSA is a promising algorithm that can be used to easily handle a wide range of optimization problems.MDPI202420242022info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://www.mdpi.com/2227-7390/10/10/1626https://hdl.handle.net/10953/3587reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésMathematics [2022]; [10]: [1626]Atribución-NoComercial-SinDerivadas 3.0 Españahttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:ruja.ujaen.es:10953/35872026-06-24T12:41:07Z
dc.title.none.fl_str_mv Circle Search Algorithm: A Geometry-Based Metaheuristic Optimization Algorithm
title Circle Search Algorithm: A Geometry-Based Metaheuristic Optimization Algorithm
spellingShingle Circle Search Algorithm: A Geometry-Based Metaheuristic Optimization Algorithm
Qais, Mohammed H.
Algorithms
Circle search algorithm
Metaheuristics
Numerical optimization
Optimization methods
title_short Circle Search Algorithm: A Geometry-Based Metaheuristic Optimization Algorithm
title_full Circle Search Algorithm: A Geometry-Based Metaheuristic Optimization Algorithm
title_fullStr Circle Search Algorithm: A Geometry-Based Metaheuristic Optimization Algorithm
title_full_unstemmed Circle Search Algorithm: A Geometry-Based Metaheuristic Optimization Algorithm
title_sort Circle Search Algorithm: A Geometry-Based Metaheuristic Optimization Algorithm
dc.creator.none.fl_str_mv Qais, Mohammed H.
Hasanien, Hany M.
Turky, Rania A.
Alghuwainem, Saad
Tostado-Véliz, Marcos
Jurado-Melguizo, Francisco
author Qais, Mohammed H.
author_facet Qais, Mohammed H.
Hasanien, Hany M.
Turky, Rania A.
Alghuwainem, Saad
Tostado-Véliz, Marcos
Jurado-Melguizo, Francisco
author_role author
author2 Hasanien, Hany M.
Turky, Rania A.
Alghuwainem, Saad
Tostado-Véliz, Marcos
Jurado-Melguizo, Francisco
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Algorithms
Circle search algorithm
Metaheuristics
Numerical optimization
Optimization methods
topic Algorithms
Circle search algorithm
Metaheuristics
Numerical optimization
Optimization methods
description This paper presents a novel metaheuristic optimization algorithm inspired by the geometrical features of circles, called the circle search algorithm (CSA). The circle is the most well-known geometric object, with various features including diameter, center, perimeter, and tangent lines. The ratio between the radius and the tangent line segment is the orthogonal function of the angle opposite to the orthogonal radius. This angle plays an important role in the exploration and exploitation behavior of the CSA. To evaluate the robustness of the CSA in comparison to other algorithms, many independent experiments employing 23 famous functions and 3 real engineering problems were carried out. The statistical results revealed that the CSA succeeded in achieving the minimum fitness values for 21 out of the tested 23 functions, and the p-value was less than 0.05. The results evidence that the CSA converged to the minimum results faster than the comparative algorithms. Furthermore, high-dimensional functions were used to assess the CSA’s robustness, with statistical results revealing that the CSA is robust to high-dimensional problems. As a result, the proposed CSA is a promising algorithm that can be used to easily handle a wide range of optimization problems.
publishDate 2022
dc.date.none.fl_str_mv 2022
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://www.mdpi.com/2227-7390/10/10/1626
https://hdl.handle.net/10953/3587
url https://www.mdpi.com/2227-7390/10/10/1626
https://hdl.handle.net/10953/3587
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Mathematics [2022]; [10]: [1626]
dc.rights.none.fl_str_mv Atribución-NoComercial-SinDerivadas 3.0 España
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial-SinDerivadas 3.0 España
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
instname:Universidad de Jaén
instname_str Universidad de Jaén
reponame_str RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
collection RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
repository.name.fl_str_mv
repository.mail.fl_str_mv
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