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Chen H. Hesitant fuzzy multi-attribute group decision making method based on weighted power operators in social network and their application. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-201859] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
This paper aims to put forward a hesitant fuzzy multi-attribute group decision making (MAGDM) method based on the weighted power aggregation operators in social network. From the point of view of social network analysis, decision makers (DMs) are interconnected in the process of MAGDM. Furthermore, the dimension of the obtained hesitant fuzzy element (HFE) by original power operators will be greater with the increasing number of attributes and alternatives and DMs, which will lead to the problem of “intermediate expression swell". This paper combines the order operation laws with the power operators to redefine two novel hesitant fuzzy power aggregation operators to simplify the involved calculation and explore new operators’ properties. Meanwhile, when two given elements have different number of values, we use the strength of social ties and social influence to develop an algorithm for extending the HFEs objectively. On the other hand, the PageRank algorithm and the deviation method are used to determine DMs’ combined weights. The feasibility of the proposed hesitant fuzzy MAGDM method based on social network is illustrated by the application to the actual issue of decision making and the comparative analysis with the existing method.
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Affiliation(s)
- Huiping Chen
- School of Economics and Management, Nantong University, Nantong, Jiangsu, China
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Farhadinia B, Chiclana F. A decision‐making methodology based on the weighted correlation coefficient in weighted extended hesitant fuzzy environments. INT J INTELL SYST 2021. [DOI: 10.1002/int.22341] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- B. Farhadinia
- Department of Mathematics Quchan University of Technology Quchan Iran
| | - F. Chiclana
- Institute of Artificial Intelligence (IAI) Faculty of Computing, Engineering and Media, De Montfort University Leicester UK
- Andalusian Research Institute on Data Science and Computational Intelligence (DaSCI) University of Granada Granada Spain
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