Vegetable Pricing and Replenishment Strategy Based on Multivariate Polynomial Regression and SARIMA Model

Fresh products are one of the important parts of the profitability of superstores, and it is very important for merchants to make effective replenishment and pricing suggestions based on historical data. In order to give a reasonable vegetable pricing and replenishment plan, this paper processes the data and then uses multivariate polynomial regression to regress the sales volume and cost-plus pricing of the category, to obtain the relationship between the sales volume of the category and the cost-plus pricing; and combines with the SARIMA model to further give the recommended replenishment quantity; considering the impact of vegetable freshness on pricing, a freshness-based pricing model is proposed, and the optimal pricing and optimal restocking quantity formula, and proved its correctness in principle. In this study, the pricing and replenishment strategies of reference vegetables are given, and future research can further explore the market forecast of other agricultural products on this basis to broaden the application scope of this model.