In modern markets, demand continuously fluctuates due to seasonality, trends, and unexpected events such as natural disasters and social disruptions, causing serious supply challenges such as excess inventory and stockouts. This study proposes a product supply simulator that accounts for such demand uncertainties, visualizes the impacts of stock levels, stockouts, and economic losses, and supports the optimization of supply planning throughout the supply chain. The proposed simulator, based on a system dynamics model, enables hub managers to input supply plans, forecast demand, calculate inventory levels, estimate costs, and visualize cost differences under various supply strategies. An application case was conducted using a 30-day supply scenario for two supermarkets, analyzing transitions in total cost, shipping cost, and opportunity loss cost under different external supply intervals. The results demonstrated that a three-day supply interval effectively balances shipping cost reduction and mitigation of opportunity losses, achieving the lowest total cost. Furthermore, future extensions will consider scenarios where external supply volumes and delivery quantities to destinations dynamically fluctuate over time, enabling more realistic and flexible supply planning. Additionally, the model will be expanded to handle multiple products simultaneously, including decisions on which products to prioritize for truck loading under capacity constraints. These advancements are expected to further enhance strategic optimization in modern supply chain management.
KITA et al. (Wed,) studied this question.