A Fuzzy Approach to Control Genetic Algorithm Parameters

Autores
Houat de Brito, Felipe; Noura Teixeira, Artur; Noura Teixeira, Otávio; Oliveira, Roberto C. L.
Año de publicación
2007
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Genetic Algorithms have been successful in several practical appliances and obtained great prominence among the techniques of Evolutionary Computation. A large portion of methods and parameters adopted in its use are heuristic or random choices, which remain unchanged throughout the execution once they are set. This can lead to a certain lack of exploration of the search surface and also compromise the variability of the population. For that matter, this work introduces the implementation of an intelligent agent based on fuzzy logic, which dynamically monitors and regulates six GA parameters. The results obtained surpass the GA traditional implementation in many aspects, and open a wide new space for research and study.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Evolutionary Computation
Genetic algorithms
Fuzzy Systems
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/135731
Acceder
id SEDICI_35fa4b1282619d64cb5178cfadd75a1c
oai_identifier_str oai:sedici.unlp.edu.ar:10915/135731
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling A Fuzzy Approach to Control Genetic Algorithm ParametersHouat de Brito, FelipeNoura Teixeira, ArturNoura Teixeira, OtávioOliveira, Roberto C. L.Ciencias InformáticasEvolutionary ComputationGenetic algorithmsFuzzy SystemsGenetic Algorithms have been successful in several practical appliances and obtained great prominence among the techniques of Evolutionary Computation. A large portion of methods and parameters adopted in its use are heuristic or random choices, which remain unchanged throughout the execution once they are set. This can lead to a certain lack of exploration of the search surface and also compromise the variability of the population. For that matter, this work introduces the implementation of an intelligent agent based on fuzzy logic, which dynamically monitors and regulates six GA parameters. The results obtained surpass the GA traditional implementation in many aspects, and open a wide new space for research and study.Sociedad Argentina de Informática e Investigación Operativa2007-06-26info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf12-23http://sedici.unlp.edu.ar/handle/10915/135731enginfo:eu-repo/semantics/altIdentifier/url/https://publicaciones.sadio.org.ar/index.php/EJS/article/view/93info:eu-repo/semantics/altIdentifier/issn/1514-6774info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:25:51Zoai:sedici.unlp.edu.ar:10915/135731Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:25:51.784SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A Fuzzy Approach to Control Genetic Algorithm Parameters
title A Fuzzy Approach to Control Genetic Algorithm Parameters
spellingShingle A Fuzzy Approach to Control Genetic Algorithm Parameters
Houat de Brito, Felipe
Ciencias Informáticas
Evolutionary Computation
Genetic algorithms
Fuzzy Systems
title_short A Fuzzy Approach to Control Genetic Algorithm Parameters
title_full A Fuzzy Approach to Control Genetic Algorithm Parameters
title_fullStr A Fuzzy Approach to Control Genetic Algorithm Parameters
title_full_unstemmed A Fuzzy Approach to Control Genetic Algorithm Parameters
title_sort A Fuzzy Approach to Control Genetic Algorithm Parameters
dc.creator.none.fl_str_mv Houat de Brito, Felipe
Noura Teixeira, Artur
Noura Teixeira, Otávio
Oliveira, Roberto C. L.
author Houat de Brito, Felipe
author_facet Houat de Brito, Felipe
Noura Teixeira, Artur
Noura Teixeira, Otávio
Oliveira, Roberto C. L.
author_role author
author2 Noura Teixeira, Artur
Noura Teixeira, Otávio
Oliveira, Roberto C. L.
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Evolutionary Computation
Genetic algorithms
Fuzzy Systems
topic Ciencias Informáticas
Evolutionary Computation
Genetic algorithms
Fuzzy Systems
dc.description.none.fl_txt_mv Genetic Algorithms have been successful in several practical appliances and obtained great prominence among the techniques of Evolutionary Computation. A large portion of methods and parameters adopted in its use are heuristic or random choices, which remain unchanged throughout the execution once they are set. This can lead to a certain lack of exploration of the search surface and also compromise the variability of the population. For that matter, this work introduces the implementation of an intelligent agent based on fuzzy logic, which dynamically monitors and regulates six GA parameters. The results obtained surpass the GA traditional implementation in many aspects, and open a wide new space for research and study.
Sociedad Argentina de Informática e Investigación Operativa
description Genetic Algorithms have been successful in several practical appliances and obtained great prominence among the techniques of Evolutionary Computation. A large portion of methods and parameters adopted in its use are heuristic or random choices, which remain unchanged throughout the execution once they are set. This can lead to a certain lack of exploration of the search surface and also compromise the variability of the population. For that matter, this work introduces the implementation of an intelligent agent based on fuzzy logic, which dynamically monitors and regulates six GA parameters. The results obtained surpass the GA traditional implementation in many aspects, and open a wide new space for research and study.
publishDate 2007
dc.date.none.fl_str_mv 2007-06-26
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/135731
url http://sedici.unlp.edu.ar/handle/10915/135731
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://publicaciones.sadio.org.ar/index.php/EJS/article/view/93
info:eu-repo/semantics/altIdentifier/issn/1514-6774
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.format.none.fl_str_mv application/pdf
12-23
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1846064309706162176
score 13.22299

Publicaciones similares