A study of vegetable replenishment and pricing based on ARIMA modeling

With the increasing diversification of consumer demand, price fluctuation and supply of vegetables have become key factors affecting the operation of fresh food supermarkets, but the lack of effective formulation strategies for fresh food supermarkets has led to the loss of revenue and efficiency. In this paper, the ARIMA prediction model is constructed by using the optimization of grid search theory, and combined with a large number of actual sales data for verification. The prediction results of the model are compared and analyzed with the actual data, and it is found that the two show significant consistency, thus highlighting the excellent performance of the model in the prediction of vegetable replenishment volume and sales price. This study will contribute significantly to the economic effectiveness of fresh food retailing.