A study of alternative selection mechanisms for multiple cossover per couple in genetic algorithms

Multiple crossover per couple (MCPC) is a newly introduced crossover method which in contrast with the single crossover per couple approach (SCPC), permits more than one crossover operation for each mating pair. MCPC was applied to optimise classic testing functions and some harder (non-linear, non-...

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Detalles Bibliográficos
Autores principales: Esquivel, Susana Cecilia, Leiva, Héctor Ariel, Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 1998
Materias:
Ciencias Informáticas
Informática
Biology and genetics
Algorithms
Combinatorial algorithms
Selection process
genetic algorithms
selections mechanism
crossover
function optimization
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/24821
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-24821
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
Informática
Biology and genetics
Algorithms
Combinatorial algorithms
Selection process
genetic algorithms
selections mechanism
crossover
function optimization
spellingShingle Ciencias Informáticas
Informática
Biology and genetics
Algorithms
Combinatorial algorithms
Selection process
genetic algorithms
selections mechanism
crossover
function optimization
Esquivel, Susana Cecilia
Leiva, Héctor Ariel
Gallard, Raúl Hector
A study of alternative selection mechanisms for multiple cossover per couple in genetic algorithms
topic_facet Ciencias Informáticas
Informática
Biology and genetics
Algorithms
Combinatorial algorithms
Selection process
genetic algorithms
selections mechanism
crossover
function optimization
description Multiple crossover per couple (MCPC) is a newly introduced crossover method which in contrast with the single crossover per couple approach (SCPC), permits more than one crossover operation for each mating pair. MCPC was applied to optimise classic testing functions and some harder (non-linear, non-separable) functions. The goodness of this approach prevailed under all tests and revealed that, when MCPC is applied with 2, 3 and 4 crossovers per couple, results as good as under SCPC can be expected with an additional benefit in processing time. This performance was obtained through the ability showed by MCPC of exploiting the recombination of good, formerly found solutions. But on the other hand, those experiments also showed that, in some cases, the method increased the risk of premature convergence due to a loss of genetic diversity. This paper gives an insight of the convenience of binding the choice of a selection mechanism to the genetic operators used. Focussing on this problem experiments with MCPC under proportional, and ranking selection methods were performed. In the case of ranking, an adaptive approach was carried out to adjust selective pressure. Descriptions of the alternative selection mechanisms used, experiments and some of the results obtained under each method 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 A study of alternative selection mechanisms for multiple cossover per couple in genetic algorithms
title_short A study of alternative selection mechanisms for multiple cossover per couple in genetic algorithms
title_full A study of alternative selection mechanisms for multiple cossover per couple in genetic algorithms
title_fullStr A study of alternative selection mechanisms for multiple cossover per couple in genetic algorithms
title_full_unstemmed A study of alternative selection mechanisms for multiple cossover per couple in genetic algorithms
title_sort study of alternative selection mechanisms for multiple cossover per couple in genetic algorithms
publishDate 1998
url http://sedici.unlp.edu.ar/handle/10915/24821
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