Artificial Intelligence


DS-Vikor: a New Methodology for Supplier Selection

Authors: Liguo Fei, Yong Deng, Yong Hu

How to select the optimal supplier is an open and important issue in supply chain management (SCM), which needs to solve the problem of assessment and sorting the potential suppliers, and can be considered as a multi-criteria decision-making (MCDM) problem. Experts’ assessment play a very important role in the process of supplier selection, while the subjective judgment of human beings could introduce unpredictable uncertainty. However, existing methods seem powerless to represent and deal with this uncertainty effectively. Dempster-Shafer evidence theory (D- S theory) is widely used to uncertainty modeling, decision making and conflicts management due to its advantage to handle 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, a DS- VIKOR method is proposed for the supplier selection problem which expends the VIKOR method by D-S theory. In this method, the basic probability assignment (BPA) is used to denote the decision makers’ assessment for suppliers, Deng entropy weight-based method is defined and applied to determine the weights of multi-criteria, and VIKOR method is used for getting the final ranking results. An illustrative example under real life is conducted to analyze and demonstrate the practicality and effectiveness of the proposed DS-VIKOR method.

Comments: 15 Pages.

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Submission history

[v1] 2017-12-13 22:28:48

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