Research On the Sales Law and Replenishment Decision of Vegetable Products Based on Statistical Analysis

Abstract

Through mathematical analysis and correlation model, considering the data of demand analysis and supply analysis, combined with the actual situation, formulate a reasonable replenishment strategy and pricing strategy to help supermarkets increase sales and profit margins and enhance market competitiveness. Aiming at different problems, data collation and cleaning were carried out, and correlation analysis and visualization tools were used to analyze the relationship between vegetable categories and the change law of sales volume [1-3]. For the replenishment problem, a linear regression model and an ARIMA time series model are used to explore the relationship between price and sales volume, as well as future sales forecasts, and corresponding conclusions are drawn [4-6]. Aiming at the problem of replenishment and pricing, a mathematical programming model is established and solved by genetic algorithm, and the optimal replenishment quantity and pricing strategy are obtained [7]. Finally, a comprehensive analysis of the results and the actual situation, the integration of relevant data and reasons for the development of vegetable products replenishment and pricing decisions to provide support [8]. In general, the model and analysis in this paper can effectively improve the economic benefits and competitiveness of the supermarket, and provide a scientific basis for decision-making [9-10].