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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/135731
Ver los metadatos del registro completo
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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:UNLP2025-09-29T11:34:01Zoai: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:13292025-09-29 11:34:01.778SEDICI (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) |
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application/pdf 12-23 |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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