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Article type: Research Article
Authors: Wei, Guiwu | Wang, Hongjun | Zhao, Xiaofei | Lin, Rui
Affiliations: School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China
Note: [] Corresponding author. Guiwu Wei, School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan 402160, China. Tel.: +86 2349891872; Fax: +86 2349891872; E-mail: weiguiwu@163.com
Abstract: In this paper, we investigate the hesitant fuzzy multiple attribute decision making with incomplete weight information. An optimization model based on the maximizing deviation method, by which the attribute weights can be determined, is established. For the special situations where the information about attribute weights is completely unknown, we establish another optimization model. By solving this model, we get a simple and exact formula, which can be used to determine the attribute weights. We utilize the hesitant fuzzy weighted averaging (HFWA) operator to aggregate the hesitant fuzzy information corresponding to each alternative, and then rank the alternatives and select the most desirable one (s) according to the score function. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Keywords: Multiple attribute decision making, hesitant fuzzy information, hesitant fuzzy weighted averaging (HFWA) operator, weight information
DOI: 10.3233/IFS-120734
Journal: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 259-266, 2014
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