<![CDATA[In food industries, supplier evaluation and selection are strategic activities that influence product freshness, operational continuity, and supply chain sustainability. However, this process is often hindered by uncertainty and ambiguity in expert judgments. In response to these challenges, the present study proposes an integrated decision-making method that combines Circular Intuitionistic Fuzzy Set (CIFS), the Stepwise Weight Assessment Ratio Analysis (SWARA), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). CIFS capture uncertainty in expert opinions, SWARA determines systematic criteria weights, and TOPSIS—enhanced with the Garg et al. distance measure—ranks suppliers based on aggregated evaluations. The evaluation involves seven key criteria: flexibility, capacity, quality, service, reputation, price, and lead time, assessed across five potential suppliers. Applied to Toko Pia Cap Mangkok, a traditional snack producer in Malang, Indonesia, the method identifies lead time, capacity, and reputation as the most critical criteria. Among the alternatives, Supplier $A_1$ consistently ranks first across optimistic, pessimistic, and combined scenarios, confirming its robustness and reliability, followed by Supplier $A_2$, while others perform less competitively. This study advances fuzzy-based multi-criteria decision-making by integrating CIFS–SWARA–TOPSIS, ensuring reliable supplier selection under uncertainty and offering a replicable framework for decision-makers in the food industry.]]>
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