Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/317747 
Year of Publication: 
2023
Citation: 
[Journal:] Annals of Operations Research [ISSN:] 1572-9338 [Volume:] 342 [Issue:] 1 [Publisher:] Springer US [Place:] New York [Year:] 2023 [Pages:] 803-844
Publisher: 
Springer US, New York
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.
Subjects: 
Circular economy
Sustainable supplier selection
Industry 4.0
Artificial intelligence
Multi-criteria decision-making
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version
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