Multiple crossover per couple and fitness proportional couple selection in genetic algorithms

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 sele...

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Detalles Bibliográficos
Autores principales: Esquivel, Susana Cecilia, Leiva, Héctor Ariel, Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 1997
Materias:
Ciencias Informáticas
genetic algorithms
selection
crossover
function optimisation
Algorithms
Parallel processing
Distributed
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23895
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-23895
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
genetic algorithms
selection
crossover
function optimisation
Algorithms
Parallel processing
Distributed
spellingShingle Ciencias Informáticas
genetic algorithms
selection
crossover
function optimisation
Algorithms
Parallel processing
Distributed
Esquivel, Susana Cecilia
Leiva, Héctor Ariel
Gallard, Raúl Hector
Multiple crossover per couple and fitness proportional couple selection in genetic algorithms
topic_facet Ciencias Informáticas
genetic algorithms
selection
crossover
function optimisation
Algorithms
Parallel processing
Distributed
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.
format Objeto de conferencia
Objeto de conferencia
author Esquivel, Susana Cecilia
Leiva, Héctor Ariel
Gallard, Raúl Hector
author_facet Esquivel, Susana Cecilia
Leiva, Héctor Ariel
Gallard, Raúl Hector
author_sort Esquivel, Susana Cecilia
title Multiple crossover per couple and fitness proportional couple selection in genetic algorithms
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
publishDate 1997
url http://sedici.unlp.edu.ar/handle/10915/23895
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AT leivahectorariel multiplecrossoverpercoupleandfitnessproportionalcoupleselectioningeneticalgorithms
AT gallardraulhector multiplecrossoverpercoupleandfitnessproportionalcoupleselectioningeneticalgorithms
bdutipo_str Repositorios
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