Research on pricing and stocking of fresh goods based on nonlinear programming

Abstract

In the fresh supermarket, due to the particularity of fresh goods, the fresh-keeping time of vegetable goods is relatively short, generally the wholesale goods of the same day need to be sold on the same day, if the day is not sold, it will produce waste phenomenon. Therefore, fresh supermarkets generally choose to price and replenish goods every day according to their experience and sales status. By establishing the relevant mathematical model, this paper gives the replenishment and pricing decision of vegetable commodities after the supermarket optimization, so as to maximize the profit of the supermarket. First, the box chart is used to pre-process the data, and then the distribution law of the sales volume of each vegetable category and single product over time is analyzed by data analysis and visualization technology. Then the Pearson correlation coefficient of the sales volume of each vegetable category and each single product is obtained by heat map analysis, and the correlation relationship between them is inferred. Then, by calculating the average daily sales pricing of various vegetable varieties as the cost plus pricing of dishes, using linear function and logarithmic function to fit the sales volume and sales price of each vegetable category to get the functional relationship between the two. Finally, ARIMA model is used to predict the wholesale price of each dish within seven days, and then the equation model is established. Finally, SLSQP method is used to predict the total amount of replenishment and pricing strategy of six vegetable categories in the next week.