New genetic algorithm approach for the min-degree constrained minimum spanning tree
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/12779 |
Resumo: | A novel approach is proposed for the NP-hard min-degree constrained minimum spanning tree (md-MST). The NP-hardness of the md-MST demands that heuristic approximations are used to tackle its intractability and thus an original genetic algorithm strategy is described using an improvement of the Martins-Souza heuristic to obtain a md-MST feasible solution, which is also presented. The genetic approach combines the latter improvement with three new approximations based on different chromosome representations for trees that employ diverse crossover operators. The genetic versions compare very favourably with the best known results in terms of both the run time and obtaining better quality solutions. In particular, new lower bounds are established for instances with higher dimensions. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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New genetic algorithm approach for the min-degree constrained minimum spanning treeCombinatorial optimizationDegree-constrained spanning treeGenetic algorithmHeuristicLower boundA novel approach is proposed for the NP-hard min-degree constrained minimum spanning tree (md-MST). The NP-hardness of the md-MST demands that heuristic approximations are used to tackle its intractability and thus an original genetic algorithm strategy is described using an improvement of the Martins-Souza heuristic to obtain a md-MST feasible solution, which is also presented. The genetic approach combines the latter improvement with three new approximations based on different chromosome representations for trees that employ diverse crossover operators. The genetic versions compare very favourably with the best known results in terms of both the run time and obtaining better quality solutions. In particular, new lower bounds are established for instances with higher dimensions.Elsevier2017-04-05T15:31:08Z2017-01-01T00:00:00Z20172019-03-21T16:42:42Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/12779eng0377-221710.1016/j.ejor.2016.11.007Salgueiro, R.de Almeida, A.Oliveira, O.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-07-07T03:35:19Zoai:repositorio.iscte-iul.pt:10071/12779Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-07-07T03:35:19Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
New genetic algorithm approach for the min-degree constrained minimum spanning tree |
title |
New genetic algorithm approach for the min-degree constrained minimum spanning tree |
spellingShingle |
New genetic algorithm approach for the min-degree constrained minimum spanning tree Salgueiro, R. Combinatorial optimization Degree-constrained spanning tree Genetic algorithm Heuristic Lower bound |
title_short |
New genetic algorithm approach for the min-degree constrained minimum spanning tree |
title_full |
New genetic algorithm approach for the min-degree constrained minimum spanning tree |
title_fullStr |
New genetic algorithm approach for the min-degree constrained minimum spanning tree |
title_full_unstemmed |
New genetic algorithm approach for the min-degree constrained minimum spanning tree |
title_sort |
New genetic algorithm approach for the min-degree constrained minimum spanning tree |
author |
Salgueiro, R. |
author_facet |
Salgueiro, R. de Almeida, A. Oliveira, O. |
author_role |
author |
author2 |
de Almeida, A. Oliveira, O. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Salgueiro, R. de Almeida, A. Oliveira, O. |
dc.subject.por.fl_str_mv |
Combinatorial optimization Degree-constrained spanning tree Genetic algorithm Heuristic Lower bound |
topic |
Combinatorial optimization Degree-constrained spanning tree Genetic algorithm Heuristic Lower bound |
description |
A novel approach is proposed for the NP-hard min-degree constrained minimum spanning tree (md-MST). The NP-hardness of the md-MST demands that heuristic approximations are used to tackle its intractability and thus an original genetic algorithm strategy is described using an improvement of the Martins-Souza heuristic to obtain a md-MST feasible solution, which is also presented. The genetic approach combines the latter improvement with three new approximations based on different chromosome representations for trees that employ diverse crossover operators. The genetic versions compare very favourably with the best known results in terms of both the run time and obtaining better quality solutions. In particular, new lower bounds are established for instances with higher dimensions. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-04-05T15:31:08Z 2017-01-01T00:00:00Z 2017 2019-03-21T16:42:42Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/12779 |
url |
http://hdl.handle.net/10071/12779 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0377-2217 10.1016/j.ejor.2016.11.007 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
_version_ |
1817546511270019072 |