A new decision support model in multi-criteria decision making with intuitionistic fuzzy sets based on risk preferences and criteria reduction

J. Liu, S. F. Liu, P. Liu, X. Z. Zhou, B. Zhao

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

In this paper, we propose a new model for decision support to address the 'large decision table' (eg, many criteria) challenge in intuitionistic fuzzy sets (IFSs) multi-criteria decision-making (MCDM) problems. This new model involves risk preferences of decision makers (DMs) based on the prospect theory and criteria reduction. First, we build three relationship models based on different types of DMs' risk preferences. By building different discernibility matrices according to relationship models, we find useful criteria for IFS MCDM problems. Second, we propose a technique to obtain weights through discernibility matrix. Third, we also propose a new method to rank and select the most desirable choice(s) according to weighted combinatorial advantage values of alternatives. Finally, we use a realistic voting example to demonstrate the practicality and effectiveness of the proposed method and construct a new decision support model for IFS MCDM problems.

Original languageEnglish (US)
Pages (from-to)1205-1220
Number of pages16
JournalJournal of the Operational Research Society
Volume64
Issue number8
DOIs
StatePublished - Aug 1 2013

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Fuzzy sets
Decision making
Decision tables
Decision support model
Multicriteria decision-making
Risk preferences
Decision maker

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Strategy and Management
  • Management Science and Operations Research
  • Marketing

Cite this

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A new decision support model in multi-criteria decision making with intuitionistic fuzzy sets based on risk preferences and criteria reduction. / Liu, J.; Liu, S. F.; Liu, P.; Zhou, X. Z.; Zhao, B.

In: Journal of the Operational Research Society, Vol. 64, No. 8, 01.08.2013, p. 1205-1220.

Research output: Contribution to journalArticle

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