Volume 7 Number 11 (Nov. 2012)
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Novel Methods for Intuitionistic Fuzzy Multiple Attribute Decision Making

Bing-bing Qiu1, James Nga Kwok Liu2, Wei-min Ma1
1School of Economics and Management, Tongji University, Shanghai, China
2Department of Computing, The Hong Kong Polytechnic University, Hongkong, China

Abstract—Decision makers sometimes tend to express their preferences in intuitionistic fuzzy form. Based on evidence theory and grey relational analysis (GRA) technique, this paper aims at investigating multiple attribute decision making problems, in which both attribute values and weight values take the form of intuitionistic fuzzy numbers (IFNs). To this end, each intuitionistic fuzzy evaluation rating is transformed into a corresponding belief structure. In light of the distance metric between two basic probability assignments, we derive a novel method to measure the distance between intuitionistic fuzzy evaluation ratings and develop two GRA based decision methods. In the process, intuitionitic fuzzy weight information is converted into a group of linear constraints. The point and the intervalvalued grey relational degrees are respectively derived as the basis to order potential alternatives. Finally, an example regarding air-condition system selection is adopted to illustrate the proposed decision procedures.

Index Terms—Multiple attribute decision making, grey relational analysis, evidence theory, intuitionistic fuzzy number

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Cite: Bing-bing Qiu, James Nga Kwok Liu, Wei-min Ma, "Novel Methods for Intuitionistic Fuzzy Multiple Attribute Decision Making," Journal of Software vol. 7, no. 11, pp. 2553-2559, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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