Research on Pricing and Replenishment Strategies for Supermarkets Based on Revenue Maximization

Based on the perspectives of time series and the supply chain, this paper investigates pricing and replenishment strategies for fresh supermarkets with the aim of maximizing profits. Through visual analysis, the vegetable category is thoroughly examined, revealing seasonal sales patterns. Furthermore, the correlation between different categories is explored using ADF tests and the DPCCA model. To optimize the replenishment quantity for the upcoming week, sales data from the past month is employed for nonlinear fitting. Assuming a fixed purchase price, the ARIMA model is utilized to forecast pricing, and optimal pricing and daily replenishment strategies for the next seven days are formulated through nonlinear programming methods.