Comparative analysis of the method of assignment by classes in GAVaPS

Autores
Lanzarini, Laura Cristina; Sanz, Cecilia Verónica; Naiouf, Marcelo; Romero, Fernando
Año de publicación
2000
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Three alternatives within the method of assignment by classes are presented for the calculation of individuals lifetime in genetic algorithms with varying population size. (GAVaPS). In the proposed strategy (assignment by classes) individuals are grouped according to their fitness. The purpose is to use the allowed range of lifetime values in a way which is more suitable to search the optimum than proportional, linear and bilinear strategies. A comparative study of three possibilities of assignment by classes as related to the traditional methods is carried out, and results are shown over five functions. Finally, some conclusions are presented, along with possible future lines of work.
Facultad de Informática
Materia
Ciencias Informáticas
Algorithms
Heuristic methods
evolutive computation; genetic algorithms; genetic algorithms with varying population size
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9389
Acceder
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Comparative analysis of the method of assignment by classes in GAVaPSLanzarini, Laura CristinaSanz, Cecilia VerónicaNaiouf, MarceloRomero, FernandoCiencias InformáticasAlgorithmsHeuristic methodsevolutive computation; genetic algorithms; genetic algorithms with varying population sizeThree alternatives within the method of assignment by classes are presented for the calculation of individuals lifetime in genetic algorithms with varying population size. (GAVaPS). In the proposed strategy (assignment by classes) individuals are grouped according to their fitness. The purpose is to use the allowed range of lifetime values in a way which is more suitable to search the optimum than proportional, linear and bilinear strategies. A comparative study of three possibilities of assignment by classes as related to the traditional methods is carried out, and results are shown over five functions. Finally, some conclusions are presented, along with possible future lines of work.Facultad de Informática2000info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/9389enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/2015/papers_02/Comparative.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:UNLP2025-09-29T10:50:40Zoai:sedici.unlp.edu.ar:10915/9389Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:50:40.234SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Comparative analysis of the method of assignment by classes in GAVaPS
title Comparative analysis of the method of assignment by classes in GAVaPS
spellingShingle Comparative analysis of the method of assignment by classes in GAVaPS
Lanzarini, Laura Cristina
Ciencias Informáticas
Algorithms
Heuristic methods
evolutive computation; genetic algorithms; genetic algorithms with varying population size
title_short Comparative analysis of the method of assignment by classes in GAVaPS
title_full Comparative analysis of the method of assignment by classes in GAVaPS
title_fullStr Comparative analysis of the method of assignment by classes in GAVaPS
title_full_unstemmed Comparative analysis of the method of assignment by classes in GAVaPS
title_sort Comparative analysis of the method of assignment by classes in GAVaPS
dc.creator.none.fl_str_mv Lanzarini, Laura Cristina
Sanz, Cecilia Verónica
Naiouf, Marcelo
Romero, Fernando
author Lanzarini, Laura Cristina
author_facet Lanzarini, Laura Cristina
Sanz, Cecilia Verónica
Naiouf, Marcelo
Romero, Fernando
author_role author
author2 Sanz, Cecilia Verónica
Naiouf, Marcelo
Romero, Fernando
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Algorithms
Heuristic methods
evolutive computation; genetic algorithms; genetic algorithms with varying population size
topic Ciencias Informáticas
Algorithms
Heuristic methods
evolutive computation; genetic algorithms; genetic algorithms with varying population size
dc.description.none.fl_txt_mv Three alternatives within the method of assignment by classes are presented for the calculation of individuals lifetime in genetic algorithms with varying population size. (GAVaPS). In the proposed strategy (assignment by classes) individuals are grouped according to their fitness. The purpose is to use the allowed range of lifetime values in a way which is more suitable to search the optimum than proportional, linear and bilinear strategies. A comparative study of three possibilities of assignment by classes as related to the traditional methods is carried out, and results are shown over five functions. Finally, some conclusions are presented, along with possible future lines of work.
Facultad de Informática
description Three alternatives within the method of assignment by classes are presented for the calculation of individuals lifetime in genetic algorithms with varying population size. (GAVaPS). In the proposed strategy (assignment by classes) individuals are grouped according to their fitness. The purpose is to use the allowed range of lifetime values in a way which is more suitable to search the optimum than proportional, linear and bilinear strategies. A comparative study of three possibilities of assignment by classes as related to the traditional methods is carried out, and results are shown over five functions. Finally, some conclusions are presented, along with possible future lines of work.
publishDate 2000
dc.date.none.fl_str_mv 2000
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/9389
url http://sedici.unlp.edu.ar/handle/10915/9389
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/2015/papers_02/Comparative.pdf
info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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