Study on the pricing and replenishment of vegetable commodities based on the optimization model

Abstract

Based on the problems of short shelf life, inventory control and pricing management, marketing, economics, operation research, and the control optimal theory, this paper establishes the regression prediction analysis model; establish the optimization model, formulate the total amount of daily replenishment; analyze the deficiencies of the model. Finally, the combination of the research results gives the replenishment and pricing decision to improve the revenue of the supermarket. In this study, the correlation degree between the two variables of each vegetable category and the single product sales volume was measured, and the time series analysis was used to identify the sales trend. Then according to the correlation analysis of descriptive statistics, using cosine similarity formula, analyze the data units, the total sales dimension normalization, using the method of standardize the correlation between item and category, using pearson correlation coefficient and Spearman correlation coefficient to study the relationship between category and sales, establish Spearman correlation coefficient to determine the final correlation coefficient, cluster analysis of each category, analysis of the correlation. By processing the relevant data, establish the ARIMA time series model, forecast on July 1,2023-July 7, the relevant data, using the adftest function time series stability test, fit the ARIMA time series model, using differential sequence to time series analysis, calculate vegetable sales and sales price of elastic demand function, finally find the optimal solution through the particle swarm algorithm.