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Mathematics 2019, 7(4), 344; https://doi.org/10.3390/math7040344

Dual Hesitant Pythagorean Fuzzy Heronian Mean Operators in Multiple Attribute Decision Making

1
School of Business, Sichuan Normal University, Chengdu, 610101, China
2
School of Statistics, Southwestern University of Finance and Economics, Chengdu, 611130, China
3
School of Finance, Yunnan University of Finance and Economics, Kunming 650221, China
*
Author to whom correspondence should be addressed.
Received: 27 March 2019 / Revised: 6 April 2019 / Accepted: 6 April 2019 / Published: 10 April 2019
(This article belongs to the Special Issue Optimization for Decision Making)
PDF [596 KB, uploaded 10 April 2019]

Abstract

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), the Pythagorean fuzzy set (PFS) is more useful in expressing fuzzy and ambiguous information. Meanwhile, in order to consider human hesitance, dual hesitant Pythagorean fuzzy sets (DHPFSs) are presented, which can be more valid for handling real multiple attribute decision-making (MADM) problems. To fuse the information in DHPFSs more effectively, in this article, some dual hesitant Pythagorean fuzzy Heronian mean operators, which can consider the relationships between arguments being fused, are defined and studied. Evidently, the new proposed operators can obtain more exact results than other existing methods. In addition, some important properties of these Heronian mean (HM) operators are discussed. Subsequently, the defined aggregation operators are used in MADM with dual hesitant Pythagorean fuzzy numbers (DHPFNs), and the MADM model is developed. In accordance with the defined operators and the built model, the dual hesitant Pythagorean fuzzy generalized weighted Heronian mean (DHPFGWHM) operator and dual hesitant Pythagorean fuzzy generalized geometric weighted Heronian mean (DHPFGGWHM) operator are applied to deal with the green supplier selection in supply chain management, and the availability and superiority of the proposed operators are analyzed by comparing them with some existing approaches. The method presented in this paper can effectively solve the MADM problems in which the decision-making information is expressed by DHPFNs and the attributes are interactive.
Keywords: multiple attribute decision-making (MADM); dual hesitant Pythagorean fuzzy sets (DHPFSs); dual hesitant Pythagorean fuzzy generalized weighted Heronian mean (DHPFGWHM) operator; dual hesitant Pythagorean fuzzy generalized geometric weighted Heronian mean (DHPFGGWHM) operator; green supplier selection; supply chain management multiple attribute decision-making (MADM); dual hesitant Pythagorean fuzzy sets (DHPFSs); dual hesitant Pythagorean fuzzy generalized weighted Heronian mean (DHPFGWHM) operator; dual hesitant Pythagorean fuzzy generalized geometric weighted Heronian mean (DHPFGGWHM) operator; green supplier selection; supply chain management
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Tang, M.; Wang, J.; Lu, J.; Wei, G.; Wei, C.; Wei, Y. Dual Hesitant Pythagorean Fuzzy Heronian Mean Operators in Multiple Attribute Decision Making. Mathematics 2019, 7, 344.

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