Research on Pricing and Replenishment of Vegetables Based on Grey Relational Model and Seasonal Index Prediction Model

This article mainly studies the problem of automatic pricing and replenishment decisions for vegetable products in supermarkets. A grey correlation model and ARIMA time series model are comprehensively established, and based on clustering analysis and regression analysis methods, the distribution patterns of sales volume for each vegetable category and item over time, as well as the relationship with cost plus pricing and mutual correlation, are analyzed to make reasonable predictions for future sales volume. In order to make decisions on product pricing, sales combination, and replenishment, and maximize supermarket profits, the data is preprocessed through normal test and quartile method. Through screening and sorting analysis, the distribution patterns of sales volume for each vegetable category and item over time are obtained; In order to analyze the relationship between different categories of vegetables and between different single products, a grey correlation model is established to determine the analysis sequence, and the correlation coefficients between each category and each single product are calculated to analyze the mutual relationship. And combined with the hierarchical clustering analysis method, the vegetable categories were divided into three sales types: high, medium, and low, expanding the relationship between categories. At the same time, a periodic chart was drawn to determine the periodicity of sales volume distribution in each category. Then, statistical analysis was conducted on the data to determine the linear correlation between sales volume and cost plus pricing. Based on this, a linear regression model was established to analyze the linear relationship between sales volume and cost plus pricing for the six categories; In order to provide the total daily replenishment amount and pricing strategy for the next week, this article establishes a seasonal index prediction model for sales forecasting. Combining the seasonal distribution of each category, the seasonal index is used to predict the sales volume for the next week. Considering the goal of maximizing profits, the target function is listed to comprehensively analyze the replenishment and pricing strategy for the next week.