A Time Series Forecasting Based Model for Vegetable Inventory and Pricing in Supermarkets

In the current vegetable supply chain of supermarkets, reasonable pricing and replenishment strategies are crucial to reduce waste and increase profitability. Based on actual data, this paper proposes a time series forecasting model for optimizing vegetable pricing and replenishment. By constructing demand, cost and profit functions, considering price, time, demand changes and other factors, the optimal pricing and replenishment can be determined in different time periods through the Stackelberg game model. We verified the validity of the model by comparing simulation with actual data, and the results show that the model can significantly improve supermarket profits while reducing inventory backlogs. This study provides a theoretical basis for supermarkets to develop efficient vegetable management strategies and has a wide potential for practical application. This research not only contributes to the existing literature on supply chain optimization but also demonstrates the potential for integrating advanced forecasting techniques with game theory in practical decision-making for perishable goods.