The ant colony metaphor for multiple knapsack problem

Autores
Cena, Marcelo Guillermo; Crespo, María Liz; Kavka, Carlos; Leguizamón, Guillermo
Año de publicación
1997
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
This paper presents an Ant Colony (AC) model for the Multiple Knapsack Problem (MKP). The ant colony metaphor, as well as other evolutionary metaphors, was applied successfully to diverse heavily constrained problems. An AC system is also considered a class of multiagent distributed algorithm for combinatorial optimisation. The principle of an AC system is adapted to the MKP. We present some results regarding its performance against known optimum for different instances of MKP. The obtained results show the potential power of this particular evolutionary approach for optimisation problems.
Eje: Workshop sobre Aspectos Teoricos de la Inteligencia Artificial
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Ant Colony (AC)
Multiple Knapsack Problem (MKP)
Intelligent agents
optimisation
algorithms
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:10915/24063
Acceder
id SEDICI_411c2ed4605e6e70f07e50e838dc5e27
oai_identifier_str oai:sedici.unlp.edu.ar:10915/24063
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling The ant colony metaphor for multiple knapsack problemCena, Marcelo GuillermoCrespo, María LizKavka, CarlosLeguizamón, GuillermoCiencias InformáticasAnt Colony (AC)Multiple Knapsack Problem (MKP)Intelligent agentsoptimisationalgorithmsThis paper presents an Ant Colony (AC) model for the Multiple Knapsack Problem (MKP). The ant colony metaphor, as well as other evolutionary metaphors, was applied successfully to diverse heavily constrained problems. An AC system is also considered a class of multiagent distributed algorithm for combinatorial optimisation. The principle of an AC system is adapted to the MKP. We present some results regarding its performance against known optimum for different instances of MKP. The obtained results show the potential power of this particular evolutionary approach for optimisation problems.Eje: Workshop sobre Aspectos Teoricos de la Inteligencia ArtificialRed de Universidades con Carreras en Informática (RedUNCI)1997info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/24063enginfo: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:UNLP2025-10-22T16:37:14Zoai:sedici.unlp.edu.ar:10915/24063Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:37:14.921SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv The ant colony metaphor for multiple knapsack problem
title The ant colony metaphor for multiple knapsack problem
spellingShingle The ant colony metaphor for multiple knapsack problem
Cena, Marcelo Guillermo
Ciencias Informáticas
Ant Colony (AC)
Multiple Knapsack Problem (MKP)
Intelligent agents
optimisation
algorithms
title_short The ant colony metaphor for multiple knapsack problem
title_full The ant colony metaphor for multiple knapsack problem
title_fullStr The ant colony metaphor for multiple knapsack problem
title_full_unstemmed The ant colony metaphor for multiple knapsack problem
title_sort The ant colony metaphor for multiple knapsack problem
dc.creator.none.fl_str_mv Cena, Marcelo Guillermo
Crespo, María Liz
Kavka, Carlos
Leguizamón, Guillermo
author Cena, Marcelo Guillermo
author_facet Cena, Marcelo Guillermo
Crespo, María Liz
Kavka, Carlos
Leguizamón, Guillermo
author_role author
author2 Crespo, María Liz
Kavka, Carlos
Leguizamón, Guillermo
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Ant Colony (AC)
Multiple Knapsack Problem (MKP)
Intelligent agents
optimisation
algorithms
topic Ciencias Informáticas
Ant Colony (AC)
Multiple Knapsack Problem (MKP)
Intelligent agents
optimisation
algorithms
dc.description.none.fl_txt_mv This paper presents an Ant Colony (AC) model for the Multiple Knapsack Problem (MKP). The ant colony metaphor, as well as other evolutionary metaphors, was applied successfully to diverse heavily constrained problems. An AC system is also considered a class of multiagent distributed algorithm for combinatorial optimisation. The principle of an AC system is adapted to the MKP. We present some results regarding its performance against known optimum for different instances of MKP. The obtained results show the potential power of this particular evolutionary approach for optimisation problems.
Eje: Workshop sobre Aspectos Teoricos de la Inteligencia Artificial
Red de Universidades con Carreras en Informática (RedUNCI)
description This paper presents an Ant Colony (AC) model for the Multiple Knapsack Problem (MKP). The ant colony metaphor, as well as other evolutionary metaphors, was applied successfully to diverse heavily constrained problems. An AC system is also considered a class of multiagent distributed algorithm for combinatorial optimisation. The principle of an AC system is adapted to the MKP. We present some results regarding its performance against known optimum for different instances of MKP. The obtained results show the potential power of this particular evolutionary approach for optimisation problems.
publishDate 1997
dc.date.none.fl_str_mv 1997
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/24063
url http://sedici.unlp.edu.ar/handle/10915/24063
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
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
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
_version_ 1846782833720295424
score 12.982451

Publicaciones similares