A New Decision Support Model in Multi-criteria Decision Making with Intuitionistic Fuzzy Sets based on Risk Preferences and Criteria Reduction

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. © 2013 Operational Research Society Ltd.

Department(s)

Electrical and Computer Engineering

Comments

National Natural Science Foundation of China, Grant 10td128

Keywords and Phrases

criteria reduction; decision support; intuitionistic fuzzy sets; multi-criteria decision making; risk preferences

International Standard Serial Number (ISSN)

1476-9360; 0160-5682

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2025 Taylor and Francis Group; Taylor and Francis, All rights reserved.

Publication Date

01 Jan 2013

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