eCite Digital Repository
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]
 | PDF 1Mb |
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/
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: | Machine learning |
| Research Field: | Neural networks |
| Objective Division: | Defence |
| Objective Group: | Defence |
| Objective Field: | Intelligence, surveillance and space |
| UTAS Author: | Cao, Z (Dr Zehong Cao) |
| ID Code: | 135980 |
| Year Published: | 2019 |
| Web of Science® Times Cited: | 7 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2019-11-23 |
| Last Modified: | 2020-05-18 |
| Downloads: | 5 View Download Statistics |
Repository Staff Only: item control page