ARIMA-Xgboost Based Pricing and Replenishment Strategy for Perishable Goods

Abstract

Based on the enterprise sales data, the study analyzes the correlation between sales of commodities, taking vegetable products as an example, and takes into account the impact of replenishment, pricing, and sales of perishable products, and considers the joint decision-making problem of pricing and dynamic replenishment of perishable products, and designs the ARIMA-XGBoost joint decision-making model. The results show that there is a sales correlation between different commodities, and through sales, big data can be a more accurate prediction of the replenishment amount in the future period, so based on the pricing and the maximization of the revenue model set up by the study can achieve more accurate replenishment and pricing decisions.