Multiple parents, multiple crossovers and incest prevention in evolutionary computation

Multimodal optimization is an always present topic in Computer Systems and Networks design and implementation. - Evolutionary Computation is an emergent field which provides new heuristics to function optimization where traditional approaches make the problem computationally intractable. The presen...

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Detalles Bibliográficos
Autores principales: Alfonso, Hugo, Minetti, Gabriela F., Salto, Carolina, Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Español
Publicado: 1999
Materias:
Ciencias Informáticas
multiple crossovers
Multiple parents
incest prevention
evolutionary computation
ARTIFICIAL INTELLIGENCE
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22221
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-22221
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Español
topic Ciencias Informáticas
multiple crossovers
Multiple parents
incest prevention
evolutionary computation
ARTIFICIAL INTELLIGENCE
spellingShingle Ciencias Informáticas
multiple crossovers
Multiple parents
incest prevention
evolutionary computation
ARTIFICIAL INTELLIGENCE
Alfonso, Hugo
Minetti, Gabriela F.
Salto, Carolina
Gallard, Raúl Hector
Multiple parents, multiple crossovers and incest prevention in evolutionary computation
topic_facet Ciencias Informáticas
multiple crossovers
Multiple parents
incest prevention
evolutionary computation
ARTIFICIAL INTELLIGENCE
description Multimodal optimization is an always present topic in Computer Systems and Networks design and implementation. - Evolutionary Computation is an emergent field which provides new heuristics to function optimization where traditional approaches make the problem computationally intractable. The present contribution gives an insight of the current enhancements that can be done in evolutionary techniques, attempting to balance exploitation and explotation to avoid premature convergence during the search process. Multiple parents, multiple crossovers and incest prevention are three different techniques that when combined showed a substantial benefit: The set of suboptimal solutions are concentrated nearby the optimal solution. This paper shows the design, implementation and partial performance results when a combination of multiple crossovers on multiple parents and incest prevention is applied to an evolutionary algorithm optimizing two difficult multimodal functions.
format Objeto de conferencia
Objeto de conferencia
author Alfonso, Hugo
Minetti, Gabriela F.
Salto, Carolina
Gallard, Raúl Hector
author_facet Alfonso, Hugo
Minetti, Gabriela F.
Salto, Carolina
Gallard, Raúl Hector
author_sort Alfonso, Hugo
title Multiple parents, multiple crossovers and incest prevention in evolutionary computation
title_short Multiple parents, multiple crossovers and incest prevention in evolutionary computation
title_full Multiple parents, multiple crossovers and incest prevention in evolutionary computation
title_fullStr Multiple parents, multiple crossovers and incest prevention in evolutionary computation
title_full_unstemmed Multiple parents, multiple crossovers and incest prevention in evolutionary computation
title_sort multiple parents, multiple crossovers and incest prevention in evolutionary computation
publishDate 1999
url http://sedici.unlp.edu.ar/handle/10915/22221
work_keys_str_mv AT alfonsohugo multipleparentsmultiplecrossoversandincestpreventioninevolutionarycomputation
AT minettigabrielaf multipleparentsmultiplecrossoversandincestpreventioninevolutionarycomputation
AT saltocarolina multipleparentsmultiplecrossoversandincestpreventioninevolutionarycomputation
AT gallardraulhector multipleparentsmultiplecrossoversandincestpreventioninevolutionarycomputation
bdutipo_str Repositorios
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