فهرست نشریات علمی دسترسی آزاد ایران

International online businesses face several challenges in supply chain management, including reducing customer response time and managing uncertainty in inventory levels. This study proposes a fuzzy multi-objective optimization model to improve supply chain performance in international environments. This model uses fuzzy numbers to handle demand fluctuations, transportation costs, and delivery time, and provides a flexible decision-making framework. To solve this model, four meta-heuristic algorithms, including NSGA-II, PSO, GOA, and GA, are used, and their performance in terms of reducing supply chain costs, optimizing delivery time, and increasing inventory stability is investigated. The results show that PSO and GOA provide the shortest response time, while NSGA-II significantly reduces overall costs. Also, sensitivity analysis showed that NSGA-II and GOA are more stable regarding demand fluctuations, while GA has the least flexibility. This research presents a novel framework for supply chain optimization in international digital businesses that can help increase competitiveness and improve service levels in global markets.