مسعود طاهری

Due to the imprecision of data, a fuzzy inference approach can be suitable for resolving imprecise data and evaluating the LARG supply chain. This study was conducted to evaluate and rank the suppliers of Firooz detergent industries, one of the largest Iranian companies specializing in the design, production, and distribution of baby care products. In this research, eight suppliers (S۱ to S۸) were considered, and fuzzy inference and fuzzy TOPSIS techniques were utilized to evaluate and rank the suppliers and select the strategic supplier. The panel of experts consisted of ۱۰ experienced professionals (each with more than ۱۰ years of experience in this field), purposefully selected from supply chain experts and specialists within the Firooz Health Group. The calculations were performed using MATLAB software. Initially, an FIS (Fuzzy Inference System) model was employed to map a given input to an output. The Mamdani fuzzy inference technique was used in this study. The output of the fuzzy inference technique was a ranking of the suppliers in the detergent industry based on five LARG supply chain criteria. Overall, the use of the FIS method to address real-world challenges, including ambiguity and uncertainty—especially the nature of the LARG supply chain in the detergent industry—is aimed at overcoming uncertainty and obtaining clear and appropriate results. This helps managers allocate their limited financial, temporal, and human resources to the implementation of higher-priority criteria while planning effectively for other priorities. This translation preserves the technical terms and specialized context of the original text, ensuring clarity and professionalism.