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Normal neutrosophic frank aggregation operators and their application in multi-attribute group decision making

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Abstract

Normal neutrosophic set (NNS) can conveniently express random and fuzzy information, and Frank operators have the properties of generalization and flexibility. In this paper, we will extend Frank operators to Normal neutrosophic numbers (NNNs), and propose some Frank aggregation Operators for NNNs, then develop two new decision methods with NNNs. Firstly, based on Frank operators, the operational laws of NNNs are redefined, and their operational properties are proved, then the normal neutrosophic Frank averaging operator (NNFWA) and normal neutrosophic Frank weighted geometric operator (NNFWG) are developed. Further, some desirable characteristics, such as idempotency, boundedness and commutativity, are discussed in detail, and some special cases are studied. Furthermore, to deal with the multiple attribute group decision making (MAGDM) problems in which attribute values take the form of NNNs, two methods on the basis of NNFWA and NNFWG operators are developed, and they are more general and more flexible by Frank operations. Finally, an example is given to illustrate the proposed methods and demonstrate their practicality and availability.

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Acknowledgements

This paper is supported by the National Natural Science Foundation of China (Nos. 71771140 and 71471172), the Special Funds of Taishan Scholars Project of Shandong Province (No. ts201511045), Shandong Provincial Social Science Planning Project (Nos. 16CGLJ31 and 16CKJJ27), the teaching reform research project of undergraduate colleges and Universities in Shandong province (No. 2015Z057) and Key research and development program of Shandong Province (No. 2016GNC110016). The authors also would like to express appreciations to the anonymous reviewers and Editors for their very helpful comments that improved this paper.

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Correspondence to Peide Liu.

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Liu, P., Wang, P. & Liu, J. Normal neutrosophic frank aggregation operators and their application in multi-attribute group decision making. Int. J. Mach. Learn. & Cyber. 10, 833–852 (2019). https://doi.org/10.1007/s13042-017-0763-8

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  • DOI: https://doi.org/10.1007/s13042-017-0763-8

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