Research on The Replenishment Pricing Model of Data-oriented Vegetable Products

Abstract

With the rapid development of economic life and the rapid improvement of people's living standards,Consumer demand for vegetable products has changed from quantity to quality.In view of the increasing requirements of consumers for the freshness, appearance, color and other qualities of vegetable products when purchasing.Based on massive data, the relationship between various categories and single products of vegetables is speculated, find out how their sales are distributed.At the problem of large data volume and relatively unclear structure,the data will be pre-processed,choose Pearson Correlation Analysis to look at overall differences and associations.Pandas library, Numpy library and matplotlib library based on Python,perform a more detailed descriptive statistical analysis of the cleaned data,and make relevant charts to show the visualization results.For complex data relationships.social science research needs to comprehensively consider the actual situation of society.The Apripri correlation analysis algorithm was used to further analyze the correlation between categories and unit sales.Based on the available informationThe relationship between the total sales volume of vegetables and the cost-plus pricing method of each category was analyzed.In view of the problems that the purchase volume of goods is difficult to predict, the difference in consumer consumption is obvious, and the seasonal changes are present,this article uses the LSTM time series and sliding time window to predict the daily sales volume of each category in the coming week.Based on this, the purchase cost is calculated, and the regression model is substituted to predict the pricing.Based on multi-objective optimization thinking and genetic algorithm, the goal decision of "revenue-cost-loss" is used as the objective function to seek the goal decision of benefit maximization.Finally, through the application of the time series prediction model, the relationship between the sales volume of each vegetable category and the cost-plus pricing is inferred, and the daily replenishment volume and pricing strategy are formulated to maximize the benefits of supermarkets.