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

Madjid Tavana (), Shahryar Sorooshian () and Hassan Mina ()
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Madjid Tavana: La Salle University
Shahryar Sorooshian: University of Gothenburg
Hassan Mina: Saito University College

Annals of Operations Research, 2024, vol. 342, issue 1, No 24, 803-844

Abstract: 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.

Keywords: Circular economy; Sustainable supplier selection; Industry 4.0; Artificial intelligence; Multi-criteria decision-making (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-023-05680-0

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