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An Improved Multi-granularity Interval 2-Tuple TODIM Approach and Its Application to Green Supplier Selection

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Abstract

Interval 2-tuple linguistic model is widely applied to group decision making owing to the representation capabilities.In order to deal with the problem of different labels (multi-granularity), an interval 2-tuple transformation function is developed, which is beneficial to information aggregation and fusion. In addition, a novel and flexible interval 2-tuple ranking function is introduced, which can obtain the ranking result in a single-step procedure. Based on the previous distance measures, the normalized generalized interval 2-tuple distance is proposed. Furthermore, an interval 2-tuple with the aid of TODIM method is introduced to select green suppliers. Finally, a sensitivity analysis is completed and a comparative analysis is carried out with interval 2-tuple TOPSIS and VIKOR methods to verify the validity of the proposed method.

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Acknowledgements

The work was supported by the National Natural Science Foundation of China (NSFC) under Project 71701158, MOE (Ministry of Education in China) Project of Humanities and Social Sciences (17YJC630114), Fundamental Research Funds for the Central Universities under the Projects 2015VI002, 2017VI010 and 185203010, and the Research Center for Systems Science & Enterprise Development (Grant No. Xq17B07).

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  1. Wuhan University of Technology, Wuhan, China

    Yingying Liang, Jun Liu, Jindong Qin & Yan Tu

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  1. Yingying Liang
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Correspondence to Jindong Qin.

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Liang, Y., Liu, J., Qin, J. et al. An Improved Multi-granularity Interval 2-Tuple TODIM Approach and Its Application to Green Supplier Selection. Int. J. Fuzzy Syst. 21, 129–144 (2019). https://doi.org/10.1007/s40815-018-0546-8

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