Dombi power partitioned Heronian mean operators of q-rung orthopair fuzzy numbers for multiple attribute group decision making

In this paper, we extend the Hamy mean (HM) operator and dual Hamy mean (DHM) operator with Pythagorean fuzzy numbers (PFNs) to propose Pythagorean fuzzy Hamy mean (PFHM) operator, weighted Pythagorean fuzzy Hamy mean (WPFHM) operator, Pythagorean fuzzy dual Hamy mean (PFDHM) operator, weighted Pythagorean fuzzy dual Hamy mean (WPFDHM) operator. Then the multiple attribute group decision making (MAGDM) methods are proposed with these operators. In the end, we utilize an applicable example for supplier selection to prove the proposed methods.

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Some q-Rung Dual Hesitant Fuzzy Heronian Mean Operators with Their Application to Multiple Attribute Group Decision-Making

Symmetry ◽

10.3390/sym10100472 ◽

2018 ◽

Vol 10 (10) ◽

pp. 472 ◽

Cited By ~ 37

Author(s):

Yuan Xu ◽

Xiaopu Shang ◽

Jun Wang ◽

Wen Wu ◽

Huiqun Huang

Keyword(s):

Decision Making ◽

Fuzzy Sets ◽

Group Decision Making ◽

Group Decision ◽

Decision Makers ◽

Hesitant Fuzzy Sets ◽

Multiple Attribute ◽

A New Technique ◽

Supplier Selection Problem ◽

Heronian Mean

The q-rung orthopair fuzzy sets (q-ROFSs), originated by Yager, are good tools to describe fuzziness in human cognitive processes. The basic elements of q-ROFSs are q-rung orthopair fuzzy numbers (q-ROFNs), which are constructed by membership and nonmembership degrees. As realistic decision-making is very complicated, decision makers (DMs) may be hesitant among several values when determining membership and nonmembership degrees. By incorporating dual hesitant fuzzy sets (DHFSs) into q-ROFSs, we propose a new technique to deal with uncertainty, called q-rung dual hesitant fuzzy sets (q-RDHFSs). Subsequently, we propose a family of q-rung dual hesitant fuzzy Heronian mean operators for q-RDHFSs. Further, the newly developed aggregation operators are utilized in multiple attribute group decision-making (MAGDM). We used the proposed method to solve a most suitable supplier selection problem to demonstrate its effectiveness and usefulness. The merits and advantages of the proposed method are highlighted via comparison with existing MAGDM methods. The main contribution of this paper is that a new method for MAGDM is proposed.

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Multiple Attribute Group Decision-Making Based on Power Heronian Aggregation Operators under Interval-Valued Dual Hesitant Fuzzy Environment

Mathematical Problems in Engineering ◽

10.1155/2020/2080413 ◽

2020 ◽

Vol 2020 ◽

pp. 1-19

Author(s):

Shenqing Jiang ◽

Wei He ◽

Fangfang Qin ◽

Qingqing Cheng

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Group Decision ◽

Aggregation Operators ◽

Fuzzy Environment ◽

Multiple Attribute ◽

Special Cases ◽

Magdm Problems ◽

Interval Valued ◽

Heronian Mean

In this paper, we focus on new methods to deal with multiple attribute group decision-making (MAGDM) problems and a new comparison law of interval-valued dual hesitant fuzzy elements (IVDHFEs). More explicitly, the interval-valued dual hesitant fuzzy 2nd-order central polymerization degree (IVDHFCP2) function is introduced, for the case that score values of different IVDHFEs are identical. This function can further compare different IVDHFEs. Then, we develop a series of interval-valued dual hesitant fuzzy power Heronian aggregation operators, i.e., the interval-valued dual hesitant fuzzy power Heronian mean (IVDHFPHM) operator, the interval-valued dual hesitant fuzzy power geometric Heronian mean (IVDHFPGHM) operator, and their weighted forms. Some desirable properties and their special cases are discussed. These proposed operators can simultaneously reflect the interrelationship of aggregated arguments and reduce the influence of unreasonable evaluation values. Finally, two approaches for interval-valued dual hesitant fuzzy MAGDM with known or unknown weight information are presented. An illustrative example and comparative studies are given to verify the advantages of our methods. A sensitivity analysis of the decision results is analyzed with different parameters.

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Methods for Multiple Attribute Group Decision Making Based on Intuitionistic Fuzzy Dombi Hamy Mean Operators

Symmetry ◽

10.3390/sym10110574 ◽

2018 ◽

Vol 10 (11) ◽

pp. 574 ◽

Cited By ~ 63

Author(s):

Zengxian Li ◽

Hui Gao ◽

Guiwu Wei

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Fuzzy Numbers ◽

Group Decision ◽

Intuitionistic Fuzzy Numbers ◽

Intuitionistic Fuzzy ◽

Multiple Attribute ◽

Selection Of

In this paper, we extended the Hamy mean (HM) operator, the Dombi Hamy mean (DHM) operator, the Dombi dual Hamy mean (DDHM), with the intuitionistic fuzzy numbers (IFNs) to propose the intuitionistic fuzzy Dombi Hamy mean (IFDHM) operator, intuitionistic fuzzy weighted Dombi Hamy mean (IFWDHM) operator, intuitionistic fuzzy Dombi dual Hamy mean (IFDDHM) operator, and intuitionistic fuzzy weighted Dombi dual Hamy mean (IFWDDHM) operator. Following this, the multiple attribute group decision-making (MAGDM) methods are proposed with these operators. To conclude, we utilized an applicable example for the selection of a car supplier to prove the proposed methods.

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Group Decision Making Based on Triangular Neutrosophic Cubic Fuzzy Einstein Hybrid Weighted Averaging Operators

Symmetry ◽

10.3390/sym11020180 ◽

2019 ◽

Vol 11 (2) ◽

pp. 180 ◽

Cited By ~ 8

Author(s):

Aliya Fahmi ◽

Fazli Amin ◽

Madad Khan ◽

Florentin Smarandache

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Fuzzy Numbers ◽

Group Decision ◽

Multiple Attribute Decision Making ◽

Aggregation Operators ◽

Weighted Averaging ◽

Averaging Operators ◽

Ordered Weighted Averaging ◽

Multiple Attribute

In this paper, a new concept of the triangular neutrosophic cubic fuzzy numbers (TNCFNs), their score and accuracy functions are introduced. Based on TNCFNs, some new Einstein aggregation operators, such as the triangular neutrosophic cubic fuzzy Einstein weighted averaging (TNCFEWA), triangular neutrosophic cubic fuzzy Einstein ordered weighted averaging (TNCFEOWA) and triangular neutrosophic cubic fuzzy Einstein hybrid weighted averaging (TNCFEHWA) operators are developed. Furthermore, their application to multiple-attribute decision-making with triangular neutrosophic cubic fuzzy (TNCF) information is discussed. Finally, a practical example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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Power Geometric Operators of Hesitant Multiplicative Fuzzy Numbers and Their Application to Multiple Attribute Group Decision Making

Mathematical Problems in Engineering ◽

10.1155/2014/186502 ◽

2014 ◽

Vol 2014 ◽

pp. 1-16 ◽

Cited By ~ 3

Author(s):

Lei Wang ◽

Mingfang Ni ◽

Zhanke Yu ◽

Lei Zhu

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Fuzzy Numbers ◽

Group Decision ◽

Fuzzy Information ◽

Support Measures ◽

Aggregation Techniques ◽

Multiple Attribute ◽

Wide Range ◽

Magdm Problems

Multiplicative relations are one of most powerful techniques to express the preferences over alternatives (or criteria). In this paper, we propose a wide range of hesitant multiplicative fuzzy power aggregation geometric operators on multiattribute group decision making (MAGDM) problems for hesitant multiplicative information. In this paper, we first develop some compatibility measures for hesitant multiplicative fuzzy numbers, based on which the corresponding support measures can be obtained. Then we propose several aggregation techniques, and investigate their properties. In the end, we develop two approaches for multiple attribute group decision making with hesitant multiplicative fuzzy information and illustrate a real world example to show the behavior of the proposed operators.

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Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functions

International Journal of Distributed Sensor Networks ◽

10.1177/1550147719877613 ◽

2019 ◽

Vol 15 (9) ◽

pp. 155014771987761 ◽

Cited By ~ 1

Author(s):

Muhammad Gulistan ◽

Mutaz Mohammad ◽

Faruk Karaaslan ◽

Seifedine Kadry ◽

Salma Khan ◽

...

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Group Decision ◽

Cosine Similarity ◽

Similarity Function ◽

Neutrosophic Sets ◽

Similarity Functions ◽

Multiple Attribute ◽

Geometric Operator ◽

Heronian Mean

This article introduces the concept of Heronian mean operators, geometric Heronian mean operators, neutrosophic cubic number–improved generalized weighted Heronian mean operators, neutrosophic cubic number–improved generalized weighted geometric Heronian mean operators. These operators actually generalize the operators of fuzzy sets, cubic sets, and neutrosophic sets. We investigate the average weighted operator on neutrosophic cubic sets and weighted geometric operator on neutrosophic cubic sets to aggregate the neutrosophic cubic information. After this, based on average weighted and geometric weighted and cosine similarity function in neutrosophic cubic sets, we developed a multiple attribute group decision-making method. Finally, we give a mathematical example to illustrate the usefulness and application of the proposed method.

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Multiple attribute group decision making based on weighted aggregation operators of triangular neutrosophic cubic fuzzy numbers

Granular Computing ◽

10.1007/s41066-019-00205-2 ◽

2019 ◽

Cited By ~ 2

Author(s):

Aliya Fahmi ◽

Fazli Amin ◽

Hidayat Ullah

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Fuzzy Numbers ◽

Group Decision ◽

Aggregation Operators ◽

Multiple Attribute

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Some Single-Valued Neutrosophic Power Heronian Aggregation Operators and Their Application to Multiple-Attribute Group Decision-Making

Symmetry ◽

10.3390/sym11050653 ◽

2019 ◽

Vol 11 (5) ◽

pp. 653 ◽

Cited By ~ 4

Author(s):

Shuping Zhao ◽

Dong Wang ◽

Changyong Liang ◽

Yajun Leng ◽

Jian Xu

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Group Decision ◽

Comparison Method ◽

Aggregation Operators ◽

Multiple Attribute ◽

Special Cases ◽

Magdm Problems ◽

Heronian Mean

The power Heronian aggregation (PHA) operator can use the advantages of power average and the Heronian mean operator, which together could take into account the interrelationship of the aggregated arguments, and therefore alleviate the effects caused by unreasonable data through considering the support degree between input arguments. However, PHA operators cannot be used to process single-valued neutrosophic numbers (SVNNs), which is significant for extending it to SVNNs. We propose some new PHA operators for SVNNs and introduce a novel MAGDM method on the basis of the proposed operators. Firstly, the definition, properties, comparison method, and operational rules of SVNNs are introduced briefly. Then, some PHA operators are proposed, such as the single-valued neutrosophic power Heronian aggregation (SVNPHA) operator, the single-valued neutrosophic weighted power Heronian aggregation (SVNWPHA) operator, single-valued neutrosophic geometric power Heronian aggregation (SVNGPHA) operator, single-valued neutrosophic weighted geometric power Heronian aggregation (SVNWGPHA) operator. Furthermore, we discuss some properties of these new aggregation operators and several special cases. Moreover, the method to solve the MAGDM problems with SVNNs is proposed, based on the SVNWPHA and SVNWGPHA operators. Lastly, we verified the application and effectiveness of the proposed method by using an example for the MAGDM problem.

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