Evolutionaty algorithms with clustering for dynamic fitness landscapes

Autores
Esquivel, Susana Cecilia; Aragón, Victoria S.
Año de publicación
2005
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Interest of dynamic multimodal functions risen over the last year since many real problems have this feature. On these problems, the goal is no longer to find the global optimal, but to track their progression through the space as closely as possible. This paper presents three evolutionary algorithms for dynamic fitness landscapes. In order to mantain diversity in the population they use two clustering techniques and a macromutation operator. Besides, this paper compares two crossover operators: arithmetic and multiparents two points, respectively. Effectiveness and limitations of each algorithm are discuss and analyzed
Eje: VI Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Algorithms
Clustering
dynamic multimodal functions
macromutation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/22904
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/22904
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Evolutionaty algorithms with clustering for dynamic fitness landscapesEsquivel, Susana CeciliaAragón, Victoria S.Ciencias InformáticasAlgorithmsClusteringdynamic multimodal functionsmacromutationInterest of dynamic multimodal functions risen over the last year since many real problems have this feature. On these problems, the goal is no longer to find the global optimal, but to track their progression through the space as closely as possible. This paper presents three evolutionary algorithms for dynamic fitness landscapes. In order to mantain diversity in the population they use two clustering techniques and a macromutation operator. Besides, this paper compares two crossover operators: arithmetic and multiparents two points, respectively. Effectiveness and limitations of each algorithm are discuss and analyzedEje: VI Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2005-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/22904enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:36:46Zoai:sedici.unlp.edu.ar:10915/22904Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:36:46.829SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Evolutionaty algorithms with clustering for dynamic fitness landscapes
title Evolutionaty algorithms with clustering for dynamic fitness landscapes
spellingShingle Evolutionaty algorithms with clustering for dynamic fitness landscapes
Esquivel, Susana Cecilia
Ciencias Informáticas
Algorithms
Clustering
dynamic multimodal functions
macromutation
title_short Evolutionaty algorithms with clustering for dynamic fitness landscapes
title_full Evolutionaty algorithms with clustering for dynamic fitness landscapes
title_fullStr Evolutionaty algorithms with clustering for dynamic fitness landscapes
title_full_unstemmed Evolutionaty algorithms with clustering for dynamic fitness landscapes
title_sort Evolutionaty algorithms with clustering for dynamic fitness landscapes
dc.creator.none.fl_str_mv Esquivel, Susana Cecilia
Aragón, Victoria S.
author Esquivel, Susana Cecilia
author_facet Esquivel, Susana Cecilia
Aragón, Victoria S.
author_role author
author2 Aragón, Victoria S.
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Algorithms
Clustering
dynamic multimodal functions
macromutation
topic Ciencias Informáticas
Algorithms
Clustering
dynamic multimodal functions
macromutation
dc.description.none.fl_txt_mv Interest of dynamic multimodal functions risen over the last year since many real problems have this feature. On these problems, the goal is no longer to find the global optimal, but to track their progression through the space as closely as possible. This paper presents three evolutionary algorithms for dynamic fitness landscapes. In order to mantain diversity in the population they use two clustering techniques and a macromutation operator. Besides, this paper compares two crossover operators: arithmetic and multiparents two points, respectively. Effectiveness and limitations of each algorithm are discuss and analyzed
Eje: VI Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description Interest of dynamic multimodal functions risen over the last year since many real problems have this feature. On these problems, the goal is no longer to find the global optimal, but to track their progression through the space as closely as possible. This paper presents three evolutionary algorithms for dynamic fitness landscapes. In order to mantain diversity in the population they use two clustering techniques and a macromutation operator. Besides, this paper compares two crossover operators: arithmetic and multiparents two points, respectively. Effectiveness and limitations of each algorithm are discuss and analyzed
publishDate 2005
dc.date.none.fl_str_mv 2005-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/22904
url http://sedici.unlp.edu.ar/handle/10915/22904
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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