Research on supermarket pricing strategy based on deep learning and optimization model

Abstract

To carry out reliable market demand analysis and improve the profit of supermarkets, this paper studied the automatic pricing and replenishment decision-making problem of vegetable products in fresh supermarkets. Firstly, the time series-LSTM prediction model is established. Secondly, the parameters of the Adam optimization algorithm and LSTM model are adjusted by grid search, Through the trained model, the daily sales volume, wholesale price, and sales price of each category in the next week are predicted. Finally, the pricing strategy of the total daily replenishment of each vegetable category in the next week is calculated.