| Title |
An integrated group fuzzy inference and best-worst method for supplier selection in intelligent circular supply chains |
| ID_Doc |
6835 |
| Authors |
Tavana, M; Sorooshian, S; Mina, H |
| Title |
An integrated group fuzzy inference and best-worst method for supplier selection in intelligent circular supply chains |
| Year |
2023 |
| Published |
|
| DOI |
10.1007/s10479-023-05680-0 |
| 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. |
| Author Keywords |
Circular economy; Sustainable supplier selection; Industry 4.0; Artificial intelligence; Multi-criteria decision-making |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001103398200003 |
| WoS Category |
Operations Research & Management Science |
| Research Area |
Operations Research & Management Science |
| PDF |
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