Dual Hesitant q-Rung Orthopair Fuzzy Muirhead Mean Operators in Multiple Attribute Decision Making

On account of the indeterminacy and subjectivity of decision makers (DMs) in complexity decision-making environments, the evaluation information over alternatives presented by DMs is usually fuzzy and ambiguous. As the generalization of intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PF...

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Main Authors: Jie Wang, Guiwu Wei, Cun Wei, Yu Wei
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8718658/
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author Jie Wang
Guiwu Wei
Cun Wei
Yu Wei
author_facet Jie Wang
Guiwu Wei
Cun Wei
Yu Wei
author_sort Jie Wang
collection DOAJ
description On account of the indeterminacy and subjectivity of decision makers (DMs) in complexity decision-making environments, the evaluation information over alternatives presented by DMs is usually fuzzy and ambiguous. As the generalization of intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs), the q-rung orthopair fuzzy sets (q-ROFSs) are more useful to express more fuzzy and ambiguous information. Meanwhile, to consider human's hesitance, the dual hesitant q-rung orthopair fuzzy sets (DHq-ROFSs) are presented which can be more valid of handling real MADM problems. To fuse the information in DHq-ROFSs more effectively, in this article, some Muirhead mean (MM) operators based on DHq-ROFSs environment, which consider any number of being fused arguments, are defined and studied. Evidently, the new proposed operators can obtain more exact results than other existing methods. In addition, some precious properties of these MM operators are discussed and all the special cases of them are investigated which indicates MM operator is more powerful than others. Afterward, the defined aggregation operators are used to solve the MADM with dual hesitant q-rung orthopair fuzzy numbers (DHq-ROFNs) and the MADM decision-making model is developed. In accordance of the defined operators and built model, two operators are applied to deal with the MADM problems for supplier selection with the DHPFNs information and the availability and superiority of the proposed operators are analyzed by comparing with some existing approaches. The method presented in this paper can effectually solve the MADM problems in which the decision-making information is expressed by the DHq-ROFNs and the attributes are interactive.
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spelling doaj.art-b6ed0c2d44e14a4cbef80aa5aeb437af2022-12-21T20:29:40ZengIEEEIEEE Access2169-35362019-01-017671396716610.1109/ACCESS.2019.29176628718658Dual Hesitant q-Rung Orthopair Fuzzy Muirhead Mean Operators in Multiple Attribute Decision MakingJie Wang0https://orcid.org/0000-0001-6286-9893Guiwu Wei1https://orcid.org/0000-0001-9074-2005Cun Wei2https://orcid.org/0000-0002-6195-8699Yu Wei3School of Business, Sichuan Normal University, Chengdu, ChinaSchool of Business, Sichuan Normal University, Chengdu, ChinaSchool of Business, Sichuan Normal University, Chengdu, ChinaSchool of Finance, Yunnan University of Finance and Economics, Kunming, ChinaOn account of the indeterminacy and subjectivity of decision makers (DMs) in complexity decision-making environments, the evaluation information over alternatives presented by DMs is usually fuzzy and ambiguous. As the generalization of intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs), the q-rung orthopair fuzzy sets (q-ROFSs) are more useful to express more fuzzy and ambiguous information. Meanwhile, to consider human's hesitance, the dual hesitant q-rung orthopair fuzzy sets (DHq-ROFSs) are presented which can be more valid of handling real MADM problems. To fuse the information in DHq-ROFSs more effectively, in this article, some Muirhead mean (MM) operators based on DHq-ROFSs environment, which consider any number of being fused arguments, are defined and studied. Evidently, the new proposed operators can obtain more exact results than other existing methods. In addition, some precious properties of these MM operators are discussed and all the special cases of them are investigated which indicates MM operator is more powerful than others. Afterward, the defined aggregation operators are used to solve the MADM with dual hesitant q-rung orthopair fuzzy numbers (DHq-ROFNs) and the MADM decision-making model is developed. In accordance of the defined operators and built model, two operators are applied to deal with the MADM problems for supplier selection with the DHPFNs information and the availability and superiority of the proposed operators are analyzed by comparing with some existing approaches. The method presented in this paper can effectually solve the MADM problems in which the decision-making information is expressed by the DHq-ROFNs and the attributes are interactive.https://ieeexplore.ieee.org/document/8718658/Multiple attribute decision making (MADM)dual hesitant q-rung orthopair fuzzy sets (DHq-ROFSs)dual hesitant q-rung orthopair fuzzy weighted Muirhead mean (DHq-ROFWMM) operatordual hesitant q-rung orthopair fuzzy weighted dual Muirhead mean (DHq-ROFWDMM) operatorsupplier selection
spellingShingle Jie Wang
Guiwu Wei
Cun Wei
Yu Wei
Dual Hesitant q-Rung Orthopair Fuzzy Muirhead Mean Operators in Multiple Attribute Decision Making
IEEE Access
Multiple attribute decision making (MADM)
dual hesitant q-rung orthopair fuzzy sets (DHq-ROFSs)
dual hesitant q-rung orthopair fuzzy weighted Muirhead mean (DHq-ROFWMM) operator
dual hesitant q-rung orthopair fuzzy weighted dual Muirhead mean (DHq-ROFWDMM) operator
supplier selection
title Dual Hesitant q-Rung Orthopair Fuzzy Muirhead Mean Operators in Multiple Attribute Decision Making
title_full Dual Hesitant q-Rung Orthopair Fuzzy Muirhead Mean Operators in Multiple Attribute Decision Making
title_fullStr Dual Hesitant q-Rung Orthopair Fuzzy Muirhead Mean Operators in Multiple Attribute Decision Making
title_full_unstemmed Dual Hesitant q-Rung Orthopair Fuzzy Muirhead Mean Operators in Multiple Attribute Decision Making
title_short Dual Hesitant q-Rung Orthopair Fuzzy Muirhead Mean Operators in Multiple Attribute Decision Making
title_sort dual hesitant q rung orthopair fuzzy muirhead mean operators in multiple attribute decision making
topic Multiple attribute decision making (MADM)
dual hesitant q-rung orthopair fuzzy sets (DHq-ROFSs)
dual hesitant q-rung orthopair fuzzy weighted Muirhead mean (DHq-ROFWMM) operator
dual hesitant q-rung orthopair fuzzy weighted dual Muirhead mean (DHq-ROFWDMM) operator
supplier selection
url https://ieeexplore.ieee.org/document/8718658/
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