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International Journal of Fuzzy Systems

, Volume 20, Issue 4, pp 1321–1333 | Cite as

Evidential Supplier Selection Based on DEMATEL and Game Theory

  • Tianyu Liu
  • Yong DengEmail author
  • Felix Chan
Article

Abstract

The supplier selection plays an important role in supplier chain management. How to evaluate the performance of suppliers is still an open issue. Multi-criteria decision-making (MCDM), due to its ability of solving multi-source information problem, has become a quite effective tool. Currently, the analytic network process (ANP) and Entropy weight are employed to solved MCDM problems. However, these techniques ignore the one-sidedness of the single weighting method and cannot deal with the uncertainties of input data. In this paper, a new evidential ANP methodology based on game theory is proposed to efficiently address supplier management under uncertain environment. First, ANP and entropy weight are employed to obtain the subjective and objective weights of criteria. Second, based on decision-making trial and evaluation laboratory (DEMATEL) and game theory, the comprehensive weight of ANP and entropy weight can be determined. Game theory is employed to combine the merits of subjective weight and objective weight, and DEMATEL is adopted to adjust the weight of criteria to make the result more reasonable. Finally, evidence theory is adopted to deal with the uncertainties of input data and get the supplier selection result. A case study is given to demonstrate the proposed modeling process. By comparing with the existing methods, we demonstrate that the proposed model has many advantages and it shows the efficiency and rationality in supplier selection problem.

Keywords

Supplier selection MCDM Dempster–Shafer evidence theory Game theory DEMATEL ANP Entropy weight 

Notes

Acknowledgements

The work is partially supported by National Natural Science Foundation of China (Grant Nos. 61573290, 61503237).

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Copyright information

© Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Institute of Fundamental and Frontier ScienceUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.School of Mechanical EngineeringXi’an Jiaotong UniversityXi’anChina
  3. 3.Institute of Integrated Automation, School of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’anChina
  4. 4.Big Data Decision InstituteJinan UniversityGuangzhouChina
  5. 5.Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityKowloonHong Kong

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