A note on the ϵ-indicator subset selection

Detalhes bibliográficos
Autor(a) principal: Vaz, Daniel
Data de Publicação: 2013
Outros Autores: Paquete, Luís, Ponte, Aníbal
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/27252
https://doi.org/10.1016/j.tcs.2013.05.013
Resumo: The ϵ-indicator subset selection selects a subset of a nondominated point set that is as close as possible to a reference point set with respect to the ϵ-indicator. This selection procedure is used by population-based heuristic approaches for multiobjective optimization problems. Given that this procedure is called very often during the run of the heuristic approach, efficient ways of computing the optimal subset are strongly required. In this note, we give a correctness proof of the ϵ-indicator subset selection algorithm proposed by Ponte et al. (2012) [1] for the bidimensional case as well as several algorithmic improvements in terms of time complexity. Extensions to larger dimension are also discussed.
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spelling A note on the ϵ-indicator subset selectionMultiobjective combinatorial optimizationSubset selectionϵ-IndicatorThe ϵ-indicator subset selection selects a subset of a nondominated point set that is as close as possible to a reference point set with respect to the ϵ-indicator. This selection procedure is used by population-based heuristic approaches for multiobjective optimization problems. Given that this procedure is called very often during the run of the heuristic approach, efficient ways of computing the optimal subset are strongly required. In this note, we give a correctness proof of the ϵ-indicator subset selection algorithm proposed by Ponte et al. (2012) [1] for the bidimensional case as well as several algorithmic improvements in terms of time complexity. Extensions to larger dimension are also discussed.Elsevier2013-08-12info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/27252http://hdl.handle.net/10316/27252https://doi.org/10.1016/j.tcs.2013.05.013engVAZ, Daniel; PAQUETE, Luís; PONTE, Aníbal - A note on the ϵ-indicator subset selection. "Theoretical Computer Science". ISSN 0304-3975. Vol. 499 (2013) p. 113-1160304-3975http://www.sciencedirect.com/science/article/pii/S0304397513003642Vaz, DanielPaquete, LuísPonte, Aníbalinfo: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:RCAAP2020-05-25T12:20:28Zoai:estudogeral.uc.pt:10316/27252Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:58:19.011702Repositório 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 A note on the ϵ-indicator subset selection
title A note on the ϵ-indicator subset selection
spellingShingle A note on the ϵ-indicator subset selection
Vaz, Daniel
Multiobjective combinatorial optimization
Subset selection
ϵ-Indicator
title_short A note on the ϵ-indicator subset selection
title_full A note on the ϵ-indicator subset selection
title_fullStr A note on the ϵ-indicator subset selection
title_full_unstemmed A note on the ϵ-indicator subset selection
title_sort A note on the ϵ-indicator subset selection
author Vaz, Daniel
author_facet Vaz, Daniel
Paquete, Luís
Ponte, Aníbal
author_role author
author2 Paquete, Luís
Ponte, Aníbal
author2_role author
author
dc.contributor.author.fl_str_mv Vaz, Daniel
Paquete, Luís
Ponte, Aníbal
dc.subject.por.fl_str_mv Multiobjective combinatorial optimization
Subset selection
ϵ-Indicator
topic Multiobjective combinatorial optimization
Subset selection
ϵ-Indicator
description The ϵ-indicator subset selection selects a subset of a nondominated point set that is as close as possible to a reference point set with respect to the ϵ-indicator. This selection procedure is used by population-based heuristic approaches for multiobjective optimization problems. Given that this procedure is called very often during the run of the heuristic approach, efficient ways of computing the optimal subset are strongly required. In this note, we give a correctness proof of the ϵ-indicator subset selection algorithm proposed by Ponte et al. (2012) [1] for the bidimensional case as well as several algorithmic improvements in terms of time complexity. Extensions to larger dimension are also discussed.
publishDate 2013
dc.date.none.fl_str_mv 2013-08-12
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/10316/27252
http://hdl.handle.net/10316/27252
https://doi.org/10.1016/j.tcs.2013.05.013
url http://hdl.handle.net/10316/27252
https://doi.org/10.1016/j.tcs.2013.05.013
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv VAZ, Daniel; PAQUETE, Luís; PONTE, Aníbal - A note on the ϵ-indicator subset selection. "Theoretical Computer Science". ISSN 0304-3975. Vol. 499 (2013) p. 113-116
0304-3975
http://www.sciencedirect.com/science/article/pii/S0304397513003642
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Elsevier
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