Capítulo de livro Acesso aberto

EMPLOYING CARDINAL RANK ORDERING OF CRITERIA IN MULTI-CRITERIA DECISION ANALYSIS

2012; World Scientific; Linguagem: Inglês

10.1142/9789814417747_0013

ISSN

1793-7868

Autores

Mona Riabacke, Mats Danielson, Aron Larsson, Love Ekenberg,

Tópico(s)

Multi-Criteria Decision Making

Resumo

World Scientific Proceedings Series on Computer Engineering and Information ScienceUncertainty Modeling in Knowledge Engineering and Decision Making, pp. 76-82 (2012) No AccessEMPLOYING CARDINAL RANK ORDERING OF CRITERIA IN MULTI-CRITERIA DECISION ANALYSISMONA RIABACKE, MATS DANIELSON, ARON LARSSON, and LOVE EKENBERGMONA RIABACKEDept. of Computer and Systems Sciences, Stockholm University, Forum 100, SE-164 40 Kista, Sweden, MATS DANIELSONDept. of Computer and Systems Sciences, Stockholm University Forum 100, SE-164 40 Kista, Sweden, ARON LARSSONDept. of Information Technology and Media, Mid Sweden University, SE-851 70 Sundsvall, Sweden, and LOVE EKENBERGDept. of Computer and Systems Sciences, Stockholm University Forum 100, SE-164 40 Kista, Swedenhttps://doi.org/10.1142/9789814417747_0013Cited by:0 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Abstract: The elicitation of preference information in multi-criteria decision analysis (MCDA) processes and the lack of practical means supporting it is a significant problem in real-life applications of MCDA. The issues at hand are problematical in a multitude of ways, but some of these issues may be remedied by accepting weaker input statements from decision-makers than what is most commonly needed, yet being able to utilize these statements for decision evaluation. In this paper, we propose a fast and practically useful weight elicitation method, which builds on the ideas of rank-order methods, but in addition take imprecise cardinal information into account. FiguresReferencesRelatedDetails Uncertainty Modeling in Knowledge Engineering and Decision MakingMetrics History PDF download

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