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Erschienen in: Neural Computing and Applications 8/2017

14.01.2016 | Original Article

Multiple attribute group decision-making method based on neutrosophic number generalized hybrid weighted averaging operator

verfasst von: Enze Zheng, Fei Teng, Peide Liu

Erschienen in: Neural Computing and Applications | Ausgabe 8/2017

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Abstract

Neutrosophic number is an important tool which is used to express indeterminate evaluation information. The purpose of the paper is to propose some aggregation operators based on neutrosophic number, which are used to handle multiple attribute group decision-making problems. Firstly, we introduce the definition, the properties and the operational laws of the neutrosophic numbers, and the possibility degree function is briefly introduced. Then, some neutrosophic number operators are proposed, such as the neutrosophic number weighted arithmetic averaging operator, the neutrosophic number ordered weighted arithmetic averaging operator, the neutrosophic number hybrid weighted arithmetic averaging operator, the neutrosophic number weighted geometric averaging operator, the neutrosophic number ordered weighted geometric averaging operator, the neutrosophic number hybrid weighted geometric averaging operator, the neutrosophic number generalized weighted averaging operator, the neutrosophic number generalized ordered weighted averaging operator, the neutrosophic number generalized hybrid weighted averaging (NNGHWA) operator. Furthermore, some properties of these operators are discussed. Moreover, a multiple attribute group decision-making method based on the NNGHWA operator is proposed. Finally, an illustrative example is proposed to demonstrate the practicality and effectiveness of the method.

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Metadaten
Titel
Multiple attribute group decision-making method based on neutrosophic number generalized hybrid weighted averaging operator
verfasst von
Enze Zheng
Fei Teng
Peide Liu
Publikationsdatum
14.01.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 8/2017
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2180-4

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