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
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/22904
Ver los metadatos del registro completo
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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:UNLP2025-09-29T10:55:12Zoai: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:13292025-09-29 10:55:13.118SEDICI (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 |
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2005-10 |
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eng |
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eng |
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