Vegetable pricing and replenishment decisions based on the optimization model

Vegetables are one of the essential foods in human daily life. Due to the short shelf life, it is difficult to preserve, the supermarket needs to timely and reasonable purchases and pricing. This paper aims to establish a model that can predict vegetable price fluctuations and develop reasonable pricing and replenishment strategies. According to the data given from a wet market, this paper studies the pricing and replenishment decisions of supermarket vegetables. By establishing the SARIMA model and Markov forecast model, the wholesale price of the same project on July 1 is calculated based on the wholesale price forecast of the previous week, and reasonable market demand is predicted. It is found that the predicted results have a reasonable error with the actual situation, and the accuracy is relatively high. The establishment of these two models is of great significance for market regulation. The model has good predictability and practical value, with good dynamic predictive ability, suitable for a reasonable allocation of resources in supermarkets and other trading places to obtain maximum benefit.