lpPSO - New optimization strategy inspired by PSO

Autores
Hasperué, Waldo; Corbalán, Leonardo César
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Given the large number of optimization problems that mankind faces, metaheuristics are very important strategies for the resolution of these problems. These strategies assess the suitability of the individuals, which represent solutions to the problem, a large number of times throughout the search for an optimal solution. When the assessment of an individual takes significant time or resources, the assessment of hundreds or thousands of individuals is a problem to be taken into consideration. In this paper, a strategy based on PSO that considerably reduces the number of individual assessments is presented, which is of great help for complex problems. The method proposed was compared with the classical version of PSO using classic functions in the space and a real case with a simulation model, and satisfactory results were obtained.
Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Optimization
Heuristic methods
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/18624
Acceder
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network_name_str SEDICI (UNLP)
spelling lpPSO - New optimization strategy inspired by PSOHasperué, WaldoCorbalán, Leonardo CésarCiencias InformáticasOptimizationHeuristic methodsGiven the large number of optimization problems that mankind faces, metaheuristics are very important strategies for the resolution of these problems. These strategies assess the suitability of the individuals, which represent solutions to the problem, a large number of times throughout the search for an optimal solution. When the assessment of an individual takes significant time or resources, the assessment of hundreds or thousands of individuals is a problem to be taken into consideration. In this paper, a strategy based on PSO that considerably reduces the number of individual assessments is presented, which is of great help for complex problems. The method proposed was compared with the classical version of PSO using classic functions in the space and a real case with a simulation model, and satisfactory results were obtained.Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2011-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf131-140http://sedici.unlp.edu.ar/handle/10915/18624enginfo: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:UNLP2025-09-10T11:56:57Zoai:sedici.unlp.edu.ar:10915/18624Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-10 11:56:58.148SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv lpPSO - New optimization strategy inspired by PSO
title lpPSO - New optimization strategy inspired by PSO
spellingShingle lpPSO - New optimization strategy inspired by PSO
Hasperué, Waldo
Ciencias Informáticas
Optimization
Heuristic methods
title_short lpPSO - New optimization strategy inspired by PSO
title_full lpPSO - New optimization strategy inspired by PSO
title_fullStr lpPSO - New optimization strategy inspired by PSO
title_full_unstemmed lpPSO - New optimization strategy inspired by PSO
title_sort lpPSO - New optimization strategy inspired by PSO
dc.creator.none.fl_str_mv Hasperué, Waldo
Corbalán, Leonardo César
author Hasperué, Waldo
author_facet Hasperué, Waldo
Corbalán, Leonardo César
author_role author
author2 Corbalán, Leonardo César
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Optimization
Heuristic methods
topic Ciencias Informáticas
Optimization
Heuristic methods
dc.description.none.fl_txt_mv Given the large number of optimization problems that mankind faces, metaheuristics are very important strategies for the resolution of these problems. These strategies assess the suitability of the individuals, which represent solutions to the problem, a large number of times throughout the search for an optimal solution. When the assessment of an individual takes significant time or resources, the assessment of hundreds or thousands of individuals is a problem to be taken into consideration. In this paper, a strategy based on PSO that considerably reduces the number of individual assessments is presented, which is of great help for complex problems. The method proposed was compared with the classical version of PSO using classic functions in the space and a real case with a simulation model, and satisfactory results were obtained.
Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description Given the large number of optimization problems that mankind faces, metaheuristics are very important strategies for the resolution of these problems. These strategies assess the suitability of the individuals, which represent solutions to the problem, a large number of times throughout the search for an optimal solution. When the assessment of an individual takes significant time or resources, the assessment of hundreds or thousands of individuals is a problem to be taken into consideration. In this paper, a strategy based on PSO that considerably reduces the number of individual assessments is presented, which is of great help for complex problems. The method proposed was compared with the classical version of PSO using classic functions in the space and a real case with a simulation model, and satisfactory results were obtained.
publishDate 2011
dc.date.none.fl_str_mv 2011-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
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info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/18624
url http://sedici.unlp.edu.ar/handle/10915/18624
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
131-140
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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reponame_str SEDICI (UNLP)
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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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