Research on the Profit Maximization Model for Automatic Pricing and Restocking of Vegetable Commodities

Abstract

 Due to the perishable nature of fresh agricultural products and the uncertainty of the types and prices of individual items before daily procurement in supermarkets, these establishments typically need to determine daily replenishment and pricing strategies based on the historical sales and demand for various goods. This paper starts from the perspective of maximizing supermarket revenue, predicting the sales of various product categories through seasonal indices. Under the constraints of the sales space for goods, the paper further uses ARIMA time series forecasting for the sales volume and procurement prices of individual items during the corresponding time period. Cost markup equivalent coefficients, daily replenishment quantities, and discount coefficients are considered as decision variables. Based on the demand curve model in economics, the paper takes into account the counteraction of cost markup pricing coefficients on sales volume and the counteraction of discount coefficients on the discounted portion of sales. The objective functions include maximizing supermarket revenue and satisfying the market demand for various categories of vegetable products. The paper adopts a novel sales model of offering discounts on predicted perishable vegetables and establishes a multi-objective programming model, providing the optimal strategies for replenishment quantities and pricing for each item on July 1st.