Evolutionary algorithms with clustering for dynamic fitness landscapes
- Autores
- Aragón, Victoria S.; Esquivel, Susana Cecilia
- Año de publicación
- 2005
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Interest on dynamic multimodal functions risen over the last years 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 maintain 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 anda analyzed.
Facultad de Informática - Materia
-
Ciencias Informáticas
Algorithms
Information Systems - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc/3.0/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/9593
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Evolutionary algorithms with clustering for dynamic fitness landscapesAragón, Victoria S.Esquivel, Susana CeciliaCiencias InformáticasAlgorithmsInformation SystemsInterest on dynamic multimodal functions risen over the last years 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 maintain 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 anda analyzed.Facultad de Informática2005-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf196-203http://sedici.unlp.edu.ar/handle/10915/9593enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Dec05-6.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:32:21Zoai:sedici.unlp.edu.ar:10915/9593Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:32:21.606SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Evolutionary algorithms with clustering for dynamic fitness landscapes |
| title |
Evolutionary algorithms with clustering for dynamic fitness landscapes |
| spellingShingle |
Evolutionary algorithms with clustering for dynamic fitness landscapes Aragón, Victoria S. Ciencias Informáticas Algorithms Information Systems |
| title_short |
Evolutionary algorithms with clustering for dynamic fitness landscapes |
| title_full |
Evolutionary algorithms with clustering for dynamic fitness landscapes |
| title_fullStr |
Evolutionary algorithms with clustering for dynamic fitness landscapes |
| title_full_unstemmed |
Evolutionary algorithms with clustering for dynamic fitness landscapes |
| title_sort |
Evolutionary algorithms with clustering for dynamic fitness landscapes |
| dc.creator.none.fl_str_mv |
Aragón, Victoria S. Esquivel, Susana Cecilia |
| author |
Aragón, Victoria S. |
| author_facet |
Aragón, Victoria S. Esquivel, Susana Cecilia |
| author_role |
author |
| author2 |
Esquivel, Susana Cecilia |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Ciencias Informáticas Algorithms Information Systems |
| topic |
Ciencias Informáticas Algorithms Information Systems |
| dc.description.none.fl_txt_mv |
Interest on dynamic multimodal functions risen over the last years 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 maintain 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 anda analyzed. Facultad de Informática |
| description |
Interest on dynamic multimodal functions risen over the last years 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 maintain 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 anda analyzed. |
| publishDate |
2005 |
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2005-12 |
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eng |
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