A new hybrid evolutionary algorithm for the k-cardinality tree problem

In recent years it has been shown that an intelligent combination of metaheuristics with other optimization techniques can significantly improve over the application of a pure metaheuristic. In this paper, we combine the evolutionary computation paradigm with dynamic programming for the application...

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Detalles Bibliográficos
Autor: Blum, Christian
Tipo de recurso: informe técnico
Fecha de publicación:2006
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/85860
Acceso en línea:https://hdl.handle.net/2117/85860
Access Level:acceso abierto
Palabra clave:Evolutionary algorithms
k-cardinality tree problem
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica
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spelling A new hybrid evolutionary algorithm for the k-cardinality tree problemBlum, ChristianEvolutionary algorithmsk-cardinality tree problemÀrees temàtiques de la UPC::Informàtica::Informàtica teòricaIn recent years it has been shown that an intelligent combination of metaheuristics with other optimization techniques can significantly improve over the application of a pure metaheuristic. In this paper, we combine the evolutionary computation paradigm with dynamic programming for the application to the NP-hard k-cardinality tree problem. Given an undirected graph G with node and edge weights, this problem consists of finding a tree in G with exactly k edges such that the sum of the weights is minimal. The genetic operators of our algorithm are based on an existing dynamic programming algorithm from the literature for finding optimal subtrees in a given tree. The simulation results show that our algorithm is able to improve the best known results for benchmark problems from the literature in 60 cases.20062006-01-0120162016-04-19reporthttp://purl.org/coar/resource_type/c_93fcVoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/reportapplication/pdfhttps://hdl.handle.net/2117/85860reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/858602026-05-27T15:37:01Z
dc.title.none.fl_str_mv A new hybrid evolutionary algorithm for the k-cardinality tree problem
title A new hybrid evolutionary algorithm for the k-cardinality tree problem
spellingShingle A new hybrid evolutionary algorithm for the k-cardinality tree problem
Blum, Christian
Evolutionary algorithms
k-cardinality tree problem
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica
title_short A new hybrid evolutionary algorithm for the k-cardinality tree problem
title_full A new hybrid evolutionary algorithm for the k-cardinality tree problem
title_fullStr A new hybrid evolutionary algorithm for the k-cardinality tree problem
title_full_unstemmed A new hybrid evolutionary algorithm for the k-cardinality tree problem
title_sort A new hybrid evolutionary algorithm for the k-cardinality tree problem
dc.creator.none.fl_str_mv Blum, Christian
author Blum, Christian
author_facet Blum, Christian
author_role author
dc.subject.none.fl_str_mv Evolutionary algorithms
k-cardinality tree problem
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica
topic Evolutionary algorithms
k-cardinality tree problem
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica
description In recent years it has been shown that an intelligent combination of metaheuristics with other optimization techniques can significantly improve over the application of a pure metaheuristic. In this paper, we combine the evolutionary computation paradigm with dynamic programming for the application to the NP-hard k-cardinality tree problem. Given an undirected graph G with node and edge weights, this problem consists of finding a tree in G with exactly k edges such that the sum of the weights is minimal. The genetic operators of our algorithm are based on an existing dynamic programming algorithm from the literature for finding optimal subtrees in a given tree. The simulation results show that our algorithm is able to improve the best known results for benchmark problems from the literature in 60 cases.
publishDate 2006
dc.date.none.fl_str_mv 2006
2006-01-01
2016
2016-04-19
dc.type.none.fl_str_mv report
http://purl.org/coar/resource_type/c_93fc
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/report
format report
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/85860
url https://hdl.handle.net/2117/85860
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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