Multiple crossover per couple and fitness proportional couple selection in genetic algorithms
- Autores
- Esquivel, Susana Cecilia; Leiva, Héctor Ariel; Gallard, Raúl Hector
- Año de publicación
- 1997
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Contrasting with conventional approaches to crossover, Multiple Crossover Per Couple (MCPC) is an alternative, recently proposed [1], approach under which more than one crossover operation for each mating pair is allowed. In genetic algorithms, Proportional Selection (PS) is a popular method to select individuals for mating based on their fitness values. The Fitness Proportional Couple Selection (FPCS) approach, is a new selection method which creates an intermediate population of couples from where, subsequently, couples are selected for crossing-over based on couple fitness. This paper proposes the combined use of MCPC and FPCS. Outstanding performance was achieved by joining both methods when optimising hard testing multimodal and unimodal functions. Some of these results and their comparison against results from conventional approaches are shown.
Eje: Procesamiento distribuido y paralelo. Tratamiento de señales
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
genetic algorithms
selection
crossover
function optimisation
Algorithms
Parallel processing
Distributed - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23895
Ver los metadatos del registro completo
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Multiple crossover per couple and fitness proportional couple selection in genetic algorithmsEsquivel, Susana CeciliaLeiva, Héctor ArielGallard, Raúl HectorCiencias Informáticasgenetic algorithmsselectioncrossoverfunction optimisationAlgorithmsParallel processingDistributedContrasting with conventional approaches to crossover, Multiple Crossover Per Couple (MCPC) is an alternative, recently proposed [1], approach under which more than one crossover operation for each mating pair is allowed. In genetic algorithms, Proportional Selection (PS) is a popular method to select individuals for mating based on their fitness values. The Fitness Proportional Couple Selection (FPCS) approach, is a new selection method which creates an intermediate population of couples from where, subsequently, couples are selected for crossing-over based on couple fitness. This paper proposes the combined use of MCPC and FPCS. Outstanding performance was achieved by joining both methods when optimising hard testing multimodal and unimodal functions. Some of these results and their comparison against results from conventional approaches are shown.Eje: Procesamiento distribuido y paralelo. Tratamiento de señalesRed de Universidades con Carreras en Informática (RedUNCI)1997info: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/10915/23895enginfo: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:UNLP2025-10-15T10:48:14Zoai:sedici.unlp.edu.ar:10915/23895Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 10:48:15.272SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Multiple crossover per couple and fitness proportional couple selection in genetic algorithms |
title |
Multiple crossover per couple and fitness proportional couple selection in genetic algorithms |
spellingShingle |
Multiple crossover per couple and fitness proportional couple selection in genetic algorithms Esquivel, Susana Cecilia Ciencias Informáticas genetic algorithms selection crossover function optimisation Algorithms Parallel processing Distributed |
title_short |
Multiple crossover per couple and fitness proportional couple selection in genetic algorithms |
title_full |
Multiple crossover per couple and fitness proportional couple selection in genetic algorithms |
title_fullStr |
Multiple crossover per couple and fitness proportional couple selection in genetic algorithms |
title_full_unstemmed |
Multiple crossover per couple and fitness proportional couple selection in genetic algorithms |
title_sort |
Multiple crossover per couple and fitness proportional couple selection in genetic algorithms |
dc.creator.none.fl_str_mv |
Esquivel, Susana Cecilia Leiva, Héctor Ariel Gallard, Raúl Hector |
author |
Esquivel, Susana Cecilia |
author_facet |
Esquivel, Susana Cecilia Leiva, Héctor Ariel Gallard, Raúl Hector |
author_role |
author |
author2 |
Leiva, Héctor Ariel Gallard, Raúl Hector |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas genetic algorithms selection crossover function optimisation Algorithms Parallel processing Distributed |
topic |
Ciencias Informáticas genetic algorithms selection crossover function optimisation Algorithms Parallel processing Distributed |
dc.description.none.fl_txt_mv |
Contrasting with conventional approaches to crossover, Multiple Crossover Per Couple (MCPC) is an alternative, recently proposed [1], approach under which more than one crossover operation for each mating pair is allowed. In genetic algorithms, Proportional Selection (PS) is a popular method to select individuals for mating based on their fitness values. The Fitness Proportional Couple Selection (FPCS) approach, is a new selection method which creates an intermediate population of couples from where, subsequently, couples are selected for crossing-over based on couple fitness. This paper proposes the combined use of MCPC and FPCS. Outstanding performance was achieved by joining both methods when optimising hard testing multimodal and unimodal functions. Some of these results and their comparison against results from conventional approaches are shown. Eje: Procesamiento distribuido y paralelo. Tratamiento de señales Red de Universidades con Carreras en Informática (RedUNCI) |
description |
Contrasting with conventional approaches to crossover, Multiple Crossover Per Couple (MCPC) is an alternative, recently proposed [1], approach under which more than one crossover operation for each mating pair is allowed. In genetic algorithms, Proportional Selection (PS) is a popular method to select individuals for mating based on their fitness values. The Fitness Proportional Couple Selection (FPCS) approach, is a new selection method which creates an intermediate population of couples from where, subsequently, couples are selected for crossing-over based on couple fitness. This paper proposes the combined use of MCPC and FPCS. Outstanding performance was achieved by joining both methods when optimising hard testing multimodal and unimodal functions. Some of these results and their comparison against results from conventional approaches are shown. |
publishDate |
1997 |
dc.date.none.fl_str_mv |
1997 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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conferenceObject |
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publishedVersion |
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http://sedici.unlp.edu.ar/handle/10915/23895 |
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dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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