Comparing rankings from using TODIM and a fuzzy expert system

Detalhes bibliográficos
Autor(a) principal: Salomon, Valério Antonio Pamplona
Data de Publicação: 2015
Outros Autores: Rangel, Luís Alberto Duncan [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.procs.2015.07.019
http://hdl.handle.net/11449/168478
Resumo: TODIM is, in its original formulation, an MCDA method developed to solve ranking problems. As an MCDA method TODIM combines the use of a multi-attribute value function as well as elements of the Outranking Approach, being founded on Prospect Theory. Recent advances in TODIM incorporate concepts from Fuzzy Sets. Although modelling multicriteria decision problems with Fuzzy Sets has been utilized when the available data are imprecise, their use in MCDA is slightly controversial, because the data fuzzification can invalidate the outcome. Following a mixed qualitative-quantitative research strategy, our aim is to prove that for the ranking problems, TODIM can provide better solutions than Fuzzy Sets. Ranks from TODIM are linear, or strong, in a sense that it has no ties between the alternative solutions. The rank obtained with a Fuzzy Expert System can be weaker, that is, it may be a number of ties. The research strategy extends this result to ranking problems with the occurrence of crisp criteria.
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spelling Comparing rankings from using TODIM and a fuzzy expert systemFuzzy expert systemsRanking problemTODIMTODIM is, in its original formulation, an MCDA method developed to solve ranking problems. As an MCDA method TODIM combines the use of a multi-attribute value function as well as elements of the Outranking Approach, being founded on Prospect Theory. Recent advances in TODIM incorporate concepts from Fuzzy Sets. Although modelling multicriteria decision problems with Fuzzy Sets has been utilized when the available data are imprecise, their use in MCDA is slightly controversial, because the data fuzzification can invalidate the outcome. Following a mixed qualitative-quantitative research strategy, our aim is to prove that for the ranking problems, TODIM can provide better solutions than Fuzzy Sets. Ranks from TODIM are linear, or strong, in a sense that it has no ties between the alternative solutions. The rank obtained with a Fuzzy Expert System can be weaker, that is, it may be a number of ties. The research strategy extends this result to ranking problems with the occurrence of crisp criteria.UFF, Av. dos Trabalhadores 420UNESP, Av. Ariberto Pereira da Cunha, 333UNESP, Av. Ariberto Pereira da Cunha, 333UFFUniversidade Estadual Paulista (Unesp)Salomon, Valério Antonio PamplonaRangel, Luís Alberto Duncan [UNESP]2018-12-11T16:41:27Z2018-12-11T16:41:27Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject126-138http://dx.doi.org/10.1016/j.procs.2015.07.019Procedia Computer Science, v. 55, p. 126-138.1877-0509http://hdl.handle.net/11449/16847810.1016/j.procs.2015.07.0192-s2.0-84960879897Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProcedia Computer Science0,258info:eu-repo/semantics/openAccess2021-10-23T21:44:29Zoai:repositorio.unesp.br:11449/168478Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:34:39.133721Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Comparing rankings from using TODIM and a fuzzy expert system
title Comparing rankings from using TODIM and a fuzzy expert system
spellingShingle Comparing rankings from using TODIM and a fuzzy expert system
Salomon, Valério Antonio Pamplona
Fuzzy expert systems
Ranking problem
TODIM
title_short Comparing rankings from using TODIM and a fuzzy expert system
title_full Comparing rankings from using TODIM and a fuzzy expert system
title_fullStr Comparing rankings from using TODIM and a fuzzy expert system
title_full_unstemmed Comparing rankings from using TODIM and a fuzzy expert system
title_sort Comparing rankings from using TODIM and a fuzzy expert system
author Salomon, Valério Antonio Pamplona
author_facet Salomon, Valério Antonio Pamplona
Rangel, Luís Alberto Duncan [UNESP]
author_role author
author2 Rangel, Luís Alberto Duncan [UNESP]
author2_role author
dc.contributor.none.fl_str_mv UFF
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Salomon, Valério Antonio Pamplona
Rangel, Luís Alberto Duncan [UNESP]
dc.subject.por.fl_str_mv Fuzzy expert systems
Ranking problem
TODIM
topic Fuzzy expert systems
Ranking problem
TODIM
description TODIM is, in its original formulation, an MCDA method developed to solve ranking problems. As an MCDA method TODIM combines the use of a multi-attribute value function as well as elements of the Outranking Approach, being founded on Prospect Theory. Recent advances in TODIM incorporate concepts from Fuzzy Sets. Although modelling multicriteria decision problems with Fuzzy Sets has been utilized when the available data are imprecise, their use in MCDA is slightly controversial, because the data fuzzification can invalidate the outcome. Following a mixed qualitative-quantitative research strategy, our aim is to prove that for the ranking problems, TODIM can provide better solutions than Fuzzy Sets. Ranks from TODIM are linear, or strong, in a sense that it has no ties between the alternative solutions. The rank obtained with a Fuzzy Expert System can be weaker, that is, it may be a number of ties. The research strategy extends this result to ranking problems with the occurrence of crisp criteria.
publishDate 2015
dc.date.none.fl_str_mv 2015-01-01
2018-12-11T16:41:27Z
2018-12-11T16:41:27Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.procs.2015.07.019
Procedia Computer Science, v. 55, p. 126-138.
1877-0509
http://hdl.handle.net/11449/168478
10.1016/j.procs.2015.07.019
2-s2.0-84960879897
url http://dx.doi.org/10.1016/j.procs.2015.07.019
http://hdl.handle.net/11449/168478
identifier_str_mv Procedia Computer Science, v. 55, p. 126-138.
1877-0509
10.1016/j.procs.2015.07.019
2-s2.0-84960879897
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Procedia Computer Science
0,258
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 126-138
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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