Pricing and replenishment decision-making of vegetable products based on time series analysis

Due to the short shelf life of vegetable products, their pricing and replenishment decisions are receiving increasing attention from supermarkets. This article first uses the Prophet model to remove time effects and provides the distribution pattern of vegetable product sales. Based on this, a double logarithmic model of vegetable product sales and cost markup pricing is established. LSTM is used to predict the cost price of vegetable products. Then, replenishment quantity and markup rate are used as decision variables, and pricing satisfying the cost markup formula is used as a constraint condition. The goal is to maximize supermarket profits, and a single objective optimization model is established. Finally, genetic algorithm is applied to solve the pricing and replenishment of vegetable products, providing optimal decisions for vegetable market management.