A hybrid group decision-making approach involving Pythagorean fuzzy uncertainty for green supplier selection

Green supplier selection is a significant issue in green supply chain management field and has drawn worldwide attention from academia, industry, and governments. Numerous methodological models have emerged for correctly choosing an appropriate green supplier, but some inadequate aspects of these models, such as the use of high-order fuzzy uncertainty, incompatible designed criteria, the weight methods used by decision experts, and consensus on distinct ranks, should be improved. This research propounds a hybrid approach that combines the analytic hierarchy process (AHP), technique for order preference by similarity to ideal solutions (TOPSIS), and linear assignment method (LAM) under Pythagorean fuzzy (PF) uncertainty to assess candidate suppliers. A new hierarchical evaluative criteria system with green factors that run throughout procurement, production, and transaction is built. The ordered weighted averaging operation predicated on a normal distribution is adopted to figure out the significance of the relevant decision experts, and the PF-AHP technique is exploited to recognize relevant criteria significance. To find the best green supplier, the PF-TOPSIS technique employs the most recent generalized distance measure and magnitudes. The LAM is exploited to arrive at a consensus on distinct ranks depending on differentiated distance parameter values in the distance formula for the PF sets, and then the optimal green supplier can be obtained. Additionally, the presented PF-AHP-TOPSIS-LAM approach was applied to an illustrative case, and the outcomes were shown to be more beneficial and efficacious than the solutions by other existing techniques. Hence, our presented hybrid approach provides a better methodological framework, establishes a critical foundation for artificial intelligence applications within a decision support field, and contributes to such competitiveness of microenterprises and the long-term development of society.

Automated summary

Green supplier selection is a crucial issue in the field of green supply chain management and has gained global attention. Existing methodological models have some shortcomings that need to be improved, such as the use of high-order fuzzy uncertainty and incompatible designed criteria. This study proposes a hybrid approach that combines AHP, TOPSIS, and LAM under PF uncertainty to assess candidate suppliers. The presented approach provides a better methodological framework for decision support and contributes to the competitiveness of microenterprises and the long-term development of society.