An integrated group fuzzy best-worst method and combined compromise solution with Bonferroni functions for supplier selection in reverse supply chains

Choosing the right supplier has a significant impact on efficiency and productivity of supply chain (SC). Different selection models approaches have been developed for reverse SCs. The lean, agile, resilient, green (LARG) strategy is an innovative paradigm competitiveness sustainability. This study proposes fuzzy-based methodology that integrates fuzzy group best-worst method (FG-BWM) combined compromise solution (FCoCoSo) in SCs within LARG strategic paradigm. FG-BWM used to measure importance weights criteria. Subsequently, FCoCoSo coupled with normalized weighted geometric Bonferroni mean functions select most suitable supplier. BWM its simplicity efficacy. CoCoSo model unique ability produce solution. are capture interrelationships among decision attributes eliminate influence extreme data. main proposed framework aims at providing easy-to-implement but reliable help manufacturers active recycling concerned sustainability issues rank suppliers. We present real-world case whose results demonstrate applicability integrated SCs, focusing particular wood paper industry.