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A TODIM· SIR method for multiple attribute decision making with interval grey uncertain linguistic based on a new distance measure1.

Authors :
Wang, Fang
Li, Xiao-Tong
Zhao, Jin
Chen, Shao-Hua
Source :
Journal of Intelligent & Fuzzy Systems. 2019, Vol. 37 Issue 1, p1569-1581. 13p.
Publication Year :
2019

Abstract

The multiple attribute decision making (MADM) with interval grey uncertain linguistic (IGUL) is a topic of current interest, and various methods have been developed. However, few approaches taking the behavioral characteristics of the decision maker into account. In this paper, an extension of TODIM (i.e., an acronym in Portuguese of interactive and multiple attribute decision making) method, in which three behavioral characteristics of the decision maker (i.e., risk aversion, reference dependence and loss aversion) are considered, is proposed. First, the δ-Hamming distance is defined to deal with the interval grey uncertain linguistic variables by considering the level of the decision maker's risk aversion, and its distinguish ability is validated by compared to the classical Hamming distance. Then, the details of the TODIM· SIR method is demonstrated: (i) considering the reference dependence behaviour of the decision maker, the positive-ideal alternative (i.e., PIA) and the negative-ideal alternative (i.e., NIA) are defined, and the gain and loss degrees of each alternative relative to NIA and PIA are computed based on the δ-Hamming distance; (ii) taking the loss aversion behaviour of the decision maker into account, the perceived dominance degree of the decision maker for the gain and the loss is calculated; (iii) according to the idea of the Superiority and Inferiority Ranking method (i.e., SIR, an outranking method), the Gain-flow and the Loss-flow are defined, and the partial ranking orders and the complete ranking order are obtained. Finally, two numerical examples are given to illustrate the robustness and validity of the method, and a comparative analysis is also conducted to compare the TODIM· SIR method with both the classical TODIM method and the classical SIR method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Volume :
37
Issue :
1
Database :
Academic Search Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
137413910
Full Text :
https://doi.org/10.3233/JIFS-18654