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An integrated group fuzzy inference and best–worst method for supplier selection in intelligent circular supply chains

Author

Listed:
  • Madjid Tavana

    (La Salle University
    University of Paderborn)

  • Shahryar Sorooshian

    (University of Gothenburg)

  • Hassan Mina

    (Saito University College)

Abstract

Circular supplier evaluation aims at selecting the most suitable suppliers with zero waste. Sustainable circular supplier selection also considers socio-economic and environmental factors in the decision process. This study proposes an integrated method for evaluating sustainable suppliers in intelligent circular supply chains using fuzzy inference and multi-criteria decision-making. In the first stage of the proposed method, supplier evaluation sub-criteria are identified and weighted from economic, social, circular, and Industry 4.0 perspectives using a fuzzy group best–worst method followed by scoring the suppliers on each criterion. In the second stage, the suppliers are ranked and selected according to an overall score determined by a fuzzy inference system. Finally, the applicability of the proposed method is demonstrated using data from a public–private partnership project at an offshore wind farm in Southeast Asia.

Suggested Citation

  • Madjid Tavana & Shahryar Sorooshian & Hassan Mina, 2024. "An integrated group fuzzy inference and best–worst method for supplier selection in intelligent circular supply chains," Annals of Operations Research, Springer, vol. 342(1), pages 803-844, November.
    • Handle: RePEc:spr:annopr:v:342:y:2024:i:1:d:10.1007_s10479-023-05680-0
    DOI: 10.1007/s10479-023-05680-0
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    References listed on IDEAS

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