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Q-rung orthopair normal fuzzy aggregation operators and their application in multi-attribute decision-making

Citation

Yang, Z and Li, X and Cao, Z and Li, J, Q-rung orthopair normal fuzzy aggregation operators and their application in multi-attribute decision-making, Mathematics, 7, (12) Article 1142. ISSN 2227-7390 (2019) [Refereed Article]


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Copyright Statement

Copyright 2019 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

DOI: doi:10.3390/math7121142

Abstract

Q-rung orthopair fuzzy set (q-ROFS) is a powerful tool to describe uncertain information in the process of subjective decision-making, but not express vast objective phenomenons that obey normal distribution. For this situation, by combining the q-ROFS with the normal fuzzy number, we proposed a new concept of q-rung orthopair normal fuzzy (q-RONF) set. Firstly, we defined the conception, the operational laws, score function, and accuracy function of q-RONF set. Secondly, we presented some new aggregation operators to aggregate the q-RONF information, including the q-RONF weighted operators, the q-RONF ordered weighted operators, the q-RONF hybrid operator, and the generalized form of these operators. Furthermore, we discussed some desirable properties of the above operators, such as monotonicity, commutativity, and idempotency. Meanwhile, we applied the proposed operators to the multi-attribute decision-making (MADM) problem and established a novel MADM method. Finally, the proposed MADM method was applied in a numerical example on enterprise partner selection, the numerical result showed the proposed method can e ectively handle the objective phenomena with obeying normal distribution and complicated fuzzy information, and has high practicality. The results of comparative and sensitive analysis indicated that our proposed method based on q-RONF aggregation operators over existing methods have stronger information aggregation ability, and are more suitable and flexible for MADM problems.

Item Details

Item Type:Refereed Article
Keywords:normal fuzzy number; Q-rung orthopair normal fuzzy sets; q-RONF information aggregation operators; multi-attribute decision-making
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Neural, Evolutionary and Fuzzy Computation
Objective Division:Defence
Objective Group:Defence
Objective Field:Intelligence
UTAS Author:Cao, Z (Mr Zehong Cao)
ID Code:135980
Year Published:2019
Deposited By:Information and Communication Technology
Deposited On:2019-11-23
Last Modified:2019-12-12
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