Analysis and Research on the Problem of Automatic Pricing and Replenishment Decision for Vegetable Categories

This paper addresses the complex problem of how to develop reasonable replenishment and pricing strategy under the dual challenges of vegetable supply and demand change and quality loss, and analyzes and forecasts it based on the sales data of a batch of vegetable commodities. First is the analyzation of the historical sales and demand rules of vegetable commodities from the two dimensions of time and space, followed by the discovery that vegetable sales have seasonal characteristics and category correlation. Then, this article establishes a polynomial regression model to explore the relationship between total sales and the prices, and concludes that the correlation between the two is low. Then, the LSTM-GRU model is established to obtain the relationship between the changes of sales volume and the wholesale prices, so as to predict the daily sales volume and the wholesale prices in the coming week. Finally, based on the prediction results, a linear planning model is established to solve the optimal daily replenishment volume and pricing strategy.