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A hybrid approach for multi-criteria group decision making based on interval type-2 fuzzy logic and intuitionistic fuzzy evaluation

Naim, S and Hagras, H (2012) A hybrid approach for multi-criteria group decision making based on interval type-2 fuzzy logic and intuitionistic fuzzy evaluation. In: UNSPECIFIED, ? - ?.

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Abstract

Multi-Criteria Decision Making (MCDM) aims to develop techniques that are able to make decisions and solve complex problems where the outcome is a factor of various conflicting criteria. Intuitionistic Fuzzy Sets (IFSs) have been shown to provide a suitable framework for dealing with decision-making systems involving membership, non-membership and hesitation which showed very good results when dealing with conflicting criteria. On the other hand, Group Decision Making (GDM) deals with decision-making systems which need to consider the opinions of a group of experts whose decisions and opinions are subject to linguistic uncertainties. Previous research has shown the power of interval type-2 fuzzy logic systems to handle the linguistic uncertainties in decision-making systems. In this paper, we propose a hybrid method combining interval type-2 fuzzy logic and IFSs to develop a Multi-Criteria Group Decision Making (MCGDM) system. The intuitionistic evaluation in interval type-2 membership functions has been derived from the proposed method which includes eight steps for the aggregation and ranking of the preference alternatives. We will present results from the proposed system deployment for the assessment of the postgraduate study where the evaluation involved 10 candidates. The proposed system was able to model the variation in the group decision-making process exhibited by the various decision-makers' opinions. In addition, the proposed system was able to provide a better agreement with human decisions compared to IFS, type-1 and interval type-2 fuzzy systems. © 2012 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: IEEE International Conference on Fuzzy Systems
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 25 Mar 2014 17:03
Last Modified: 23 Jan 2019 00:18
URI: http://repository.essex.ac.uk/id/eprint/9036

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