(untitled) (Contemporary Mathematics, 2025)
In today’s competitive and rapidly changing business landscape, organizations face significant challenges such as resource limitations, fluctuating demand, and evolving customer needs. Addressing these challenges requires effective strategies, with supplier selection playing a vital role in building resilient and efficient supply chains. This study introduces an innovative framework for supplier evaluation and selection, integrating the analytic hierarchy process (AHP) and the technique for order preference by similarity to the ideal solution (TOPSIS) within a fuzzy environment. The AHP method was employed to systematically identify and prioritize key performance indicators (KPIs) critical for evaluating suppliers. Criteria such as transportation cost, flexibility in meeting product requirements, defect reduction, and effective communication and responsiveness were identified as the most significant factors. These priorities formed the foundation for applying the fuzzy TOPSIS method, which facilitated the ranking of suppliers under conditions of uncertainty. The analysis revealed Sepidar Darb, Aram Plastic Sabalan, Sanaye Plastic Markaz, and Amin Avar Plastic as the top-performing suppliers, followed by Pegah Zanjan Company. The relevance of this research is heightened by the impact of the COVID-19 pandemic, which has disrupted global supply chains and fundamentally altered supplier selection criteria. While pre-pandemic evaluations predominantly focused on cost efficiency and product quality, the pandemic has underscored the importance of additional criteria such as supplier agility, risk management capabilities, geographical proximity, and digital integration. These emerging priorities highlight the necessity of rethinking traditional approaches to supplier selection and adapting to the evolving demands of global supply chains. By incorporating these updated criteria into the AHP-TOPSIS framework, this study offers a robust and practical tool for supplier evaluation in uncertain and dynamic environments. The proposed framework not only improves upon traditional methods but also provides valuable insights for organizations striving to create resilient and adaptable supply chains capable of withstanding future disruptions.