A novel fractional fuzzy SWARA-TOPSIS framework for sustainable supplier selection

The increasing global concerns about environmental degradation, resource depletion, and ethical practices have driven the food sector to prioritize sustainability in its operations. Sustainable supply chain management is crucial for ensuring resilience and long-term business value. However, traditional fuzzy methods fail to address the complexities and uncertainties inherent in sustainability assessments, especially when dealing with extreme values. This study proposes a novel fractional fuzzy multi-criteria decision-making (MCDM) framework, combining the Step-Wise Weight Assessment Ratio Analysis (SWARA) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), to evaluate sustainable food suppliers. The framework incorporates fractional fuzzy numbers and novel distances to capture human judgment and subjective data, addressing the limitations of conventional models. We apply this integrated approach to the selection of food suppliers, offering a more comprehensive decision-making model that includes expert judgment deviations, interdependent criteria, and robust sensitivity analysis. The results of the proposed hybrid method recommend “food wholesaler” with a closeness coefficient of (0.6617) as the most suitable alternative and financial capability ( $$\\mathfrak {M}_2$$ ) with weight value (0.0645) as the most influential criteria. Sensitivity and comparative analyses further confirm the robustness and adaptability of the model under various conditions. In the food industry, selection of sustainable suppliers is a complicated task, and this approach can support them in dealing with the challenges.