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Interval-Valued Intuitionistic 2-Tuple Linguistic Bonferroni Mean Operators and Their Applications in Multi-attribute Group Decision Making

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Abstract

The main purposes of this paper are to propose some new Bonferroni mean (BM) operators under the interval-valued intuitionistic 2-tuple linguistic environment and apply them to multi-attribute group decision-making (MAGDM) problems. In order to aggregate correlated IVI2TLVs, we propose some new interval-valued intuitionistic 2-tuple linguistic Bonferroni mean operators, including the interval-valued intuitionistic 2-tuple linguistic Bonferroni mean (IVI2TLBM) operator, the interval-valued intuitionistic 2-tuple linguistic weighted Bonferroni mean (IVI2TLWBM) operator, and the combined interval-valued intuitionistic 2-tuple linguistic weighted Bonferroni mean (CIVI2TLWBM) operator. Furthermore, a ranking method is presented to solve MAGDM problems. Finally, a real-life application of the proposed method is given, and the sensitivity analysis and comparative analysis are carried out to verify the effectiveness and feasibility of the method.

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Acknowledgements

This work was supported by Youth Projects of National Social Science Foundation of China (NO. 13CTJ006) and National Natural Science Foundation of China (NO. 71803001).

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  1. School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, China

    Kang Du & Hongjun Yuan

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  1. Kang Du
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  2. Hongjun Yuan
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Correspondence to Hongjun Yuan.

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Du, K., Yuan, H. Interval-Valued Intuitionistic 2-Tuple Linguistic Bonferroni Mean Operators and Their Applications in Multi-attribute Group Decision Making. Int. J. Fuzzy Syst. 21, 2373–2391 (2019). https://doi.org/10.1007/s40815-019-00720-z

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