Models for Multiple Attribute Decision Making with Some 2-Tuple Linguistic Pythagorean Fuzzy Hamy Mean Operators

Deng, Xia; Wang, Jie; Wei, Guiwu; Lu, Mingyue

doi:10.3390/math6110236

Cited by 84 publications

(30 citation statements)

References 103 publications

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“…However, our developed methods can only deal with MADMs with dual hesitant Pythagorean fuzzy information, and it is clear that these operators cannot handle more complicated decision making problems, such as when the sum square of the membership and non-membership is more than 1. In the future, we shall continue studying MADM problems with the application and extension of the developed operators to other domains [67,68] and proposed more suitable methods [69][70][71][72][73][74][75].…”

Section: Resultsmentioning

confidence: 99%

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

Tang

Wang

et al. 2019

Mathematics

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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.

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Section: Resultsmentioning

confidence: 99%

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

Tang

Wang

et al. 2019

Mathematics

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“…Low‐carbon economy and circular economy have become the mainstream of Chinese society for the sustainable development . The consciousness of environmental protection is improving among the public, so the business operators should not only create the economic benefits, but also need to consider the impact of the green image for the enterprise in the market competition . At the same time, green supplier selection in green supply chain management is a classical MAGDM problem .…”

Section: Application Of Green Supplier Selectionmentioning

confidence: 99%

Some q‐rung interval‐valued orthopair fuzzy Maclaurin symmetric mean operators and their applications to multiple attribute group decision making

et al. 2019

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In this paper, according to the Maclaurin symmetric mean (MSM) operator, the dual MSM (DMSM) operator and the q-rung interval-valued orthopair fuzzy set (q-RIVOFS), we develop some novel MSM operators under the q-rung interval-valued orthopair fuzzy environment, such as, the q-rung interval-valued orthopair fuzzy MSM operator, the q-rung interval-valued orthopair fuzzy weighted MSM (q-RIVOFWMSM) operator, the q-rung interval-valued orthopair fuzzy DMSM operator, and the q-rung interval-valued orthopair fuzzy weighted DMSM operator. In addition, some precious properties and numerical examples of these new operators are given in detail. These new operators have the advantages of considering the interrelationship of arguments and can deal with multiple attribute group decision-making problems with q-rung interval-valued orthopair fuzzy information. Finally, a reality example for green suppliers selection in green supply chain management is provided to demonstrate the proposed approach and to verify its rationality and scientific. green suppliers selection, multiple attribute group decision making (MAGDM), q-RIVOFWDMSM operator, q-RIVOFWMSM operator, q-rung interval-valued orthopair fuzzy sets (q-RIVOFSs) | INTRODUCTIONIn the study of fuzzy sets (FSs) 1 fields, finding the suitable way to express evaluation information is a hot topic. Although the intuitionistic FSs (IFSs) 2-7 and Pythagorean FSs (PFSs) [8][9][10][11][12][13][14][15][16] have emerged as useful tools to deal with actual decision-making problems, however, the scope of their assessment information remains limited. Thus, to overcome this limitation, the q-rung orthopair fuzzy set (q-ROFS), 17 which is characterized by the sum of q-th power of membership and nonmembership is less or equal to 1, was proposed for MADM problems. Since that, the q-ROFS has aroused the attention of a large number of scholars since its appearance. 18-21 Based on the weighted average (WA) operator and the weighted geometric (WG) operator, [22][23][24][25][26] Liu and Wang 27 developed two q-rung orthopair fuzzy aggregation operator to fuse q-rung orthopair fuzzy numbers. Combined q-rung orthopair fuzzy information and MSM operators, Wei, Wei, Wang, Gao, and Wei 28 proposed some new q-rung orthopair fuzzy aggregation operators and studied their applications to potential evaluation of emerging technology commercialization. Liu, Wang and Liu 29 proposed some q-rung orthopair fuzzy Heronian mean operators and q-rung orthopair fuzzy partitioned Heronian mean operators for MADM, and then some special cases about these operators were discussed. Based on the cosine similarity measure and cotangent similarity measure, Wang, Wang, Wei, and Wei 30 defined some novel q-rung orthopair fuzzy cosine and cotangent similarity measures. Bai, Zhu, Wang, and Zhang 31 defined some q-rung orthopair fuzzy partitioned Maclaurin symmetric mean (MSM) operators for MADM. Xu, Shang, Wang, Wu, and Huang 32 combined the q-ROFS and the dual hesitant fuzzy set to propose the q-rung dual hesitant orthopair fuzz...

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“…Thus, how to aggregate these q‐ ROFNs on the basis of the HM and DHM is an interesting topic. To solve this issue, in this paper, we shall develop some q‐ rung orthopair fuzzy aggregation operators on the basis of the traditional HM and DHM . To do so, the remainder of this paper is set out as follows.…”

Section: Introductionmentioning

confidence: 99%

“…To solve this issue, in this paper, we shall develop some q-rung orthopair fuzzy aggregation operators on the basis of the traditional HM and DHM. [48][49][50][51][52] To do so, the remainder of this paper is set out as follows. In the next section, we introduce some basic concepts related to q-ROFSs.…”

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confidence: 99%

Some q ‐rung orthopair fuzzy Hamy mean operators in multiple attribute decision‐making and their application to enterprise resource planning systems selection

Wang

Wei

et al. 2019

Int J Intell Syst

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In this paper, the Hamy mean (HM) operator, weighted HM (WHM), dual HM (DHM) operator, and dual WHM (WDHM) operator under the q‐rung orthopair fuzzy sets (q‐ROFSs) is studied to propose the q‐rung orthopair fuzzy HM (q‐ROFHM) operator, q‐rung orthopair fuzzy WHM (q‐ROFWHM) operator, q‐rung orthopair fuzzy DHM (q‐ROFDHM) operator, and q‐rung orthopair fuzzy weighted DHM (q‐ROFWDHM) operator and some of their desirable properties are investigated in detail. Then, we apply these operators to multiple attribute decision‐making problems. Finally, a practical example for enterprise resource planning system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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Models for Multiple Attribute Decision Making with Some 2-Tuple Linguistic Pythagorean Fuzzy Hamy Mean Operators

Cited by 84 publications

References 103 publications

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

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

Some q‐rung interval‐valued orthopair fuzzy Maclaurin symmetric mean operators and their applications to multiple attribute group decision making

Some q ‐rung orthopair fuzzy Hamy mean operators in multiple attribute decision‐making and their application to enterprise resource planning systems selection

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