A novel defuzzifying approach to car evaluation and selection under fuzzy environment

Authors:
Ta-Chung Chu;Chung-Tsen Tsao
Affiliations:
Department of Industrial Management, Southern Taiwan University of Technology, 1, Nan-Tai Street, Yung-Kang City, Tainan County, Taiwan 710, Republic of China;Department of Finance, National Pingtung Institute of Commerce, 51, Min-Sheng E. Road, Pingtung, Taiwan 900, Republic of China
Venue:
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Year:
2002

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Abstract

This paper proposes a new method for ranking fuzzy numbers by difference between relative areas. Comparative examples illustrate the advantage of the proposed method. The ranking method is further applied to help establish a defuzzified multiple level FMADM model, which avoids the complicated aggregation of fuzzy numbers so that the multiple level FMADM problem can be efficiently solved. A numerical example of car evaluation and selection illustrates the feasibility of the proposed model.