Techniques to model uncertain input data of multi-criteria decision-making problems: a literature review

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dc.contributor.authorPelissari R.
dc.contributor.authorOliveira M.C.
dc.contributor.authorAbackerli A.J.
dc.contributor.authorBen-Amor S.
dc.contributor.authorAssumpcao M.R.P.
dc.date.accessioned2024-03-12T19:21:15Z
dc.date.available2024-03-12T19:21:15Z
dc.date.issued2021
dc.description.abstract© 2018 The Authors. International Transactions in Operational Research © 2018 International Federation of Operational Research SocietiesThere are a few studies in the literature regarding possible types of uncertainty in input data of multi-criteria decision making (MCDM) or multi-criteria decision analysis (MCDA) problems and the techniques employed to deal with each of them. Therefore, the aim of this study is to identify the different types of uncertainty that occur in input data of MCDM/MCDA problems and the most appropriate techniques to deal with each one of these uncertainty types. In this paper, a comprehensive literature review is presented in order to meet this objective. We selected and summarized 134 international journal articles. They were analyzed based on the type of data with uncertainty, the type of uncertainty, and the technique used to model it. We identified three distinct types of uncertainty in input data of MCDM/MCDA problems, namely (i) uncertainty due to ambiguity, (ii) uncertainty due to randomness, and (iii) uncertainty due to partial information. We identified a new generation of fuzzy approaches including Type-2, intuitionistic, and hesitant fuzzy sets (FSs), which are used to model these types of uncertainty alongside other approaches such as traditional FSs theory, probability theory, evidential reasoning theory, rough set theory, and grey numbers. Finally, a framework that indicates techniques used in different decision-making contexts under uncertainty is proposed.
dc.description.firstpage523
dc.description.issuenumber2
dc.description.lastpage559
dc.description.volume28
dc.identifier.doi10.1111/itor.12598
dc.identifier.issn1475-3995
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/34701
dc.relation.ispartofInternational Transactions in Operational Research
dc.rightsAcesso Restrito
dc.subject.otherlanguageimprecision
dc.subject.otherlanguagemulticriteria analysis
dc.subject.otherlanguagepartial information
dc.subject.otherlanguagesystematic literature review
dc.subject.otherlanguageuncertainty
dc.titleTechniques to model uncertain input data of multi-criteria decision-making problems: a literature review
dc.typeArtigo
local.scopus.citations84
local.scopus.eid2-s2.0-85053730242
local.scopus.subjectimprecision
local.scopus.subjectMulti Criteria Analysis
local.scopus.subjectPartial information
local.scopus.subjectSystematic literature review
local.scopus.subjectuncertainty
local.scopus.updated2024-12-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85053730242&origin=inward
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