Supplier selection is a key issue in supply chain management. Today’s intense competition has forced organizations to adopt effective improvement paradigms, including lean, agile, green, resilient, and sustainable (LARGS). Integrating fuzzy logic with multi-criteria decision-making models enables accurate responses to both qualitative and quantitative uncertainties. This study aims to evaluate and rank suppliers within the LARGS supply chain of the Firooz Hygienic Group. The research is qualitative–quantitative, inductive, and applied. Ten supply chain experts from the Firooz Group were selected through purposive sampling. Since decision-making involves risk and uncertainty, the Mamdani fuzzy inference system was applied, modeling each paradigm’s criteria with triangular membership functions. To optimize the rule structure, 42 effective and non-redundant rules were selected from 243 initial rules based on strength and coverage indices, reducing model complexity and improving inference accuracy. These final rules were combined with the Fuzzy TOPSIS method to rank suppliers.Results showed the performance ranking as follows: S7 > S5 > S1 > S6 > S8 > S3 > S2 > S4. Suppliers performed better in “agility” and “sustainability” and weaker in “resilience,” reflecting the current focus of the supply market in the detergent industry. The findings can assist supply chain managers in improving key LARGS indicators. Moreover, the proposed model can be adapted to other industries and service sectors by adjusting evaluation criteria and input variables according to operational conditions. Industry-specific calibration of variables, rules, and weighting schemes ensures model validity and decision accuracy across different contexts.