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An integrated multi-criteria decision-making framework for sustainable supplier selection under picture fuzzy environment

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  • معلومة اضافية
    • بيانات النشر:
      Vilnius Gediminas Technical University
    • الموضوع:
      2020
    • Collection:
      Directory of Open Access Journals: DOAJ Articles
    • نبذة مختصرة :
      Sustainable supplier selection (SSS) is an important part of sustainable supply chain management (SSCM). In this paper, an integrated multi-criteria decision-making (MCDM) framework, based on the picture fuzzy exponential entropy, and the VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method, is proposed to manage SSS problems. Firstly, the evaluation criteria of SSS, including economic, environmental and social, is established. This can be evaluated in the form of the actual data or linguistic terms provided by suppliers and experts respectively in an actual decision-making process. Then, according to the translated scales, all the evaluation information can be converted into picture fuzzy numbers (PFNs). Secondly, the picture fuzzy exponential entropy is defined. Moreover, based on the entropy’s minimization principle, the defined picture fuzzy exponential entropy is used to determine the weight of the SSS’s criteria. Thirdly, the extended VIKOR method, which combines the grey correlation coefficient, is utilized to select a suitable supplier. This method avoids the shortcomings of the traditional VIKOR method in data mining and solves the conflict between SSS criteria. Finally, the feasibility and effectiveness of the proposed integrated decision framework are verified by an experiment, as well as a sensitivity analysis and comparative analysis. First published online 28 February 2020
    • ISSN:
      2029-4913
      2029-4921
    • Relation:
      https://journals.vgtu.lt/index.php/TEDE/article/view/12110; https://doaj.org/toc/2029-4913; https://doaj.org/toc/2029-4921; https://doaj.org/article/cb7b6fcdb1c74d55b4d89474a814a7e8
    • الرقم المعرف:
      10.3846/tede.2020.12110
    • الرقم المعرف:
      edsbas.E0F001B5