Title
Hesitant Fuzzy Linguistic Possibility Degree-Based Linear Assignment Method For Multiple Criteria Decision-Making
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.
Year
DOI
Venue
2019
10.1142/S0219622017500377
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
Keywords
Field
DocType
Multiple criteria decision-making, hesitant fuzzy linguistic term set, possibility degree, hesitant fuzzy linguistic possibility degree, linear assignment method
Multiple-criteria decision analysis,Multiple criteria,Matrix (mathematics),Fuzzy logic,Matrix difference equation,Permutation matrix,Artificial intelligence,Linguistics,Mathematics
Journal
Volume
Issue
ISSN
18
1
0219-6220
Citations 
PageRank 
References 
0
0.34
42
Authors
3
Name
Order
Citations
PageRank
Xunjie Gou11857.02
Zeshui Xu214310599.02
Huchang Liao3160967.71