Approaches to hesitant fuzzy multiple attribute decision making with incomplete weight information

Authors:
Guiwu Wei;Hongjun Wang;Xiaofei Zhao;Rui Lin
Affiliations:
School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China;School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China;School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China;School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Year:
2014

Citing 20
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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.