Searching for the dimension of valued preference relations

The more information a preference structure gives, the more sophisticated representation techniques are necessary, so decision makers can have a global view of data and therefore a comprehensive understanding of the problem they are faced with. In this paper we propose to explore valued preference r...

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Detalhes bibliográficos
Autores: González Pachón, J., Gómez González, Daniel, Montero De Juan, Francisco Javier, Yáñez Gestoso, Francisco Javier
Formato: artículo
Fecha de publicación:2003
País:España
Recursos:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/57598
Acesso em linha:https://hdl.handle.net/20.500.14352/57598
Access Level:acceso abierto
Palavra-chave:004.8
Multicriteria decision analysis
Valued relations
Dimension theory
Inteligencia artificial (Informática)
1203.04 Inteligencia Artificial
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spelling Searching for the dimension of valued preference relationsGonzález Pachón, J.Gómez González, DanielMontero De Juan, Francisco JavierYáñez Gestoso, Francisco Javier004.8Multicriteria decision analysisValued relationsDimension theoryInteligencia artificial (Informática)1203.04 Inteligencia ArtificialThe more information a preference structure gives, the more sophisticated representation techniques are necessary, so decision makers can have a global view of data and therefore a comprehensive understanding of the problem they are faced with. In this paper we propose to explore valued preference relations by means of a search for the number of underlying criteria allowing its representation in real space. A general representation theorem for arbitrary crisp binary relations is obtained, showing the difference in representation between incomparability-related to the intersection operator-and other inconsistencies-related to the union operator. A new concept of dimension is therefore proposed, taking into account inconsistencies in source of information. Such a result is then applied to each alpha-cut of valued preference relations. (C) 2002 Elsevier Science Inc. All rights reserved.Elsevier Science INCUniversidad Complutense de Madrid20032003-01-0120032003-01-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/57598reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/575982026-06-02T12:44:21Z
dc.title.none.fl_str_mv Searching for the dimension of valued preference relations
title Searching for the dimension of valued preference relations
spellingShingle Searching for the dimension of valued preference relations
González Pachón, J.
004.8
Multicriteria decision analysis
Valued relations
Dimension theory
Inteligencia artificial (Informática)
1203.04 Inteligencia Artificial
title_short Searching for the dimension of valued preference relations
title_full Searching for the dimension of valued preference relations
title_fullStr Searching for the dimension of valued preference relations
title_full_unstemmed Searching for the dimension of valued preference relations
title_sort Searching for the dimension of valued preference relations
dc.creator.none.fl_str_mv González Pachón, J.
Gómez González, Daniel
Montero De Juan, Francisco Javier
Yáñez Gestoso, Francisco Javier
author González Pachón, J.
author_facet González Pachón, J.
Gómez González, Daniel
Montero De Juan, Francisco Javier
Yáñez Gestoso, Francisco Javier
author_role author
author2 Gómez González, Daniel
Montero De Juan, Francisco Javier
Yáñez Gestoso, Francisco Javier
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 004.8
Multicriteria decision analysis
Valued relations
Dimension theory
Inteligencia artificial (Informática)
1203.04 Inteligencia Artificial
topic 004.8
Multicriteria decision analysis
Valued relations
Dimension theory
Inteligencia artificial (Informática)
1203.04 Inteligencia Artificial
description The more information a preference structure gives, the more sophisticated representation techniques are necessary, so decision makers can have a global view of data and therefore a comprehensive understanding of the problem they are faced with. In this paper we propose to explore valued preference relations by means of a search for the number of underlying criteria allowing its representation in real space. A general representation theorem for arbitrary crisp binary relations is obtained, showing the difference in representation between incomparability-related to the intersection operator-and other inconsistencies-related to the union operator. A new concept of dimension is therefore proposed, taking into account inconsistencies in source of information. Such a result is then applied to each alpha-cut of valued preference relations. (C) 2002 Elsevier Science Inc. All rights reserved.
publishDate 2003
dc.date.none.fl_str_mv 2003
2003-01-01
2003
2003-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/57598
url https://hdl.handle.net/20.500.14352/57598
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.publisher.none.fl_str_mv Elsevier Science INC
publisher.none.fl_str_mv Elsevier Science INC
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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