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.

Keywords:

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

Acknowledgements

This research is supported by the National Natural Science Foundation of China (Project Nos. 71002046, 71071076, 71071077, 71171107, and 71171112), Major Project of Social Science Foundation of the China (Project No. 10zd&014), and the Key Project of Science Foundation of the China (Project No. 70931002). At the same time, the authors would like to acknowledge the partial support of the Foundation for outstanding teaching group of China (Project No. 10td128). We would like to thank the editors and reviewers for their detailed and constructive comments.