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DS-VIKOR: A New Multi-criteria Decision-Making Method for Supplier Selection

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Abstract

How to select the optimal supplier is an open and important issue in supply chain management, which can be considered as a multi-criteria decision-making (MCDM) problem. The assessment of experts plays a very important role in the process of supplier selection, while their subjective judgment could produce unpredictable uncertainty. However, existing methods cannot represent and deal with the uncertainty effectively. Dempster–Shafer evidence theory (D–S theory) is widely used in uncertainty modeling, decision-making and conflicts management due to its advantages of handling uncertain information. The VIKOR method has a great advantage to handle MCDM problems with non-commensurable and even conflicting criteria, and to obtain the compromised optimal solution. In this paper, the DS-VIKOR method is proposed for supplier selection problem, which expends the VIKOR method by D–S theory. In the proposed method, the basic probability assignment is used to denote the assessment of domain experts for alternatives, Deng entropy weight-based method is defined and applied to determine the weights of multi-criteria, and VIKOR method is used to get the final ranking results. A numerical example for supplier selection is conducted to analyze and demonstrate the practicality and effectiveness of the proposed DS-VIKOR method.

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Acknowledgements

The authors greatly appreciate the reviews’ suggestions and the editor’s encouragement. The work is partially supported by National Natural Science Foundation of China (Grant Nos. 61573290, 61503237).

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  1. Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Liguo Fei & Yong Deng

  2. Big Data Decision Institute, Jinan University, Tianhe, Guangzhou, 510632, China

    Yong Hu

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  1. Liguo Fei
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Fei, L., Deng, Y. & Hu, Y. DS-VIKOR: A New Multi-criteria Decision-Making Method for Supplier Selection. Int. J. Fuzzy Syst. 21, 157–175 (2019). https://doi.org/10.1007/s40815-018-0543-y

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