Multi-Attribute Decision-Making Method Based on Interval-Valued <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula>-Rung Orthopair Fuzzy Archimedean Muirhead Mean Operators

Interval-valued q-rung orthopair fuzzy sets (IVq-ROFSs), as a generalization of q-rung orthopair fuzzy sets (q-ROFSs), are the powerful tool for mastering the fuzziness of information. Archimedean t-conorm and t-norm (ATT) consist of t-conorm and t-norm families, which is an important tool for fuzzy...

Full description

Bibliographic Details
Main Authors: Hengxia Gao, Yanbing Ju, Wenkai Zhang, Dawei Ju
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8723046/
Description
Summary:Interval-valued q-rung orthopair fuzzy sets (IVq-ROFSs), as a generalization of q-rung orthopair fuzzy sets (q-ROFSs), are the powerful tool for mastering the fuzziness of information. Archimedean t-conorm and t-norm (ATT) consist of t-conorm and t-norm families, which is an important tool for fuzzy sets to generate general operational laws. Meanwhile, the Muirhead mean (MM) operator is a useful aggregation operator that considers the interdependent phenomena among the aggregated arguments. Motivated by those primary characteristics, in this paper, the MM operator to the interval-valued q-rung orthopair fuzzy numbers (IVq-ROFNs) based on the ATT is studied. First, some interval-valued q-rung orthopair fuzzy operational rules are proposed based on ATT. Second, the interval-valued q-rung orthopair fuzzy Archimedean Muirhead mean (IVq-ROFAMM) operator and the interval-valued q-rung orthopair fuzzy weighted Archimedean Muirhead mean (IVq-ROFWAMM) operator are proposed. Third, some desirable properties of the two operators are discussed, and some special cases of the developed operators are investigated. Furthermore, a novel approach based on the IVq-ROFWAMM operator is developed to solve multiple attribute decision-making problem with the interval-valued q-rung orthopair fuzzy information. Finally, a numerical example is given to illustrate the validity of the proposed method and a comparative analysis is conducted to show the superiorities of the method.
ISSN:2169-3536