Hesitant Fuzzy Linguistic Possibility Degree-Based Linear Assignment Method for Multiple Criteria Decision-Making

Xunjie Gou (), Zeshui Xu and Huchang Liao ()
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Xunjie Gou: Business School, Sichuan University, Chengdu 610064, P. R. China
Zeshui Xu: Business School, Sichuan University, Chengdu 610064, P. R. China
Huchang Liao: Business School, Sichuan University, Chengdu 610064, P. R. China

International Journal of Information Technology & Decision Making (IJITDM), 2019, vol. 18, issue 01, 35-63

Abstract: Hesitant fuzzy linguistic term set (HFLTS), as a flexible tool to represent people’s uncertain cognition, has attracted lots of scholars’ research interests, and a series of methodologies have been proposed to deal with a variety of decision-making problems. In this paper, we develop a hesitant fuzzy linguistic possibility degree-based linear assignment (HFL-PDLA) method to tackle the multiple criteria decision-making (MCDM) problems under hesitant fuzzy linguistic environment. Firstly, we define the possibility degree of hesitant fuzzy linguistic element (HFLE). Additionally, some relevant concepts related to the HFL-PDLA method are proposed, such as the relative difference matrix, the rank contribution matrix, the optimal permutation matrix, etc. Furthermore, the algorithm of the HFL-PDLA method is given to deal with hesitant fuzzy linguistic MCDM problems. Moreover, we apply the HFL-PDLA method to deal with a practical case which is to select the optimal treatment technology for disposing the outspent or old medical apparatuses and instruments in West China Hospital (WCH). Finally, we show the advantages of the HFL-PDLA method by making some comparative analyses with the TOPSIS method, the VIKOR method the PROMETHEE method and the LINMAP method.

Keywords: Multiple criteria decision-making; hesitant fuzzy linguistic term set; possibility degree; hesitant fuzzy linguistic possibility degree; linear assignment method (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219622017500377

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