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On Intuitionistic Fuzzy Copula Aggregation Operators in Multiple- Attribute Decision Making

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Abstract

Operations of intuitionistic fuzzy values have been widely studied and have attracted significant interest. In this paper, some other operations on intuitionistic fuzzy values on the basis of Archimedean copulas and corresponding co-copulas are introduced. Such novel operations can show the relevance between intuitionistic fuzzy values. A family of weighted aggregation operators are developed according to the proposed operations, i.e., the intuitionistic fuzzy copula aggregation operator. The properties of the novel operations and the weighted aggregation operators are also considered. In the end, we provide a modified maximizing deviation decision procedure for multiple attributes decision making under intuitionistic fuzzy environment, and show a case study to illustrate the application of the proposed approach.

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Acknowledgements

The authors first want to thank the Editor-in-Chief Professor Amir Hussain, the associate Editor and four anonymous referees for their constructive and valuable comments, which have much improved the paper.

Funding

The work was supported by National Natural Science Foundation of China (Nos. 71771001, 71701001, 71301001, 71371011, 71501002), the Anhui Provincial Philosophy and Social Science Planning Youth Foundation (No. AHSKQ2016D13), the Doctoral Scientific Research Foundation of Anhui University, the Provincial Natural Science Research Project of Anhui Colleges (No. KJ2015A379), and the Scientific Research Foundation of Hebei Education Department (QN2017060).

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Authors and Affiliations

  1. School of Economics, Anhui University, Hefei, Anhui, 230601, China

    Zhifu Tao

  2. School of Mathematical Sciences, Anhui University, Hefei, Anhui, 230601, China

    Bing Han & Huayou Chen

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  1. Zhifu Tao
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  2. Bing Han
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Correspondence to Huayou Chen.

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Tao, Z., Han, B. & Chen, H. On Intuitionistic Fuzzy Copula Aggregation Operators in Multiple- Attribute Decision Making. Cogn Comput 10, 610–624 (2018). https://doi.org/10.1007/s12559-018-9545-1

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