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Research on pricing and replenishment of vegetable products based on particle group algorithms

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DOI: 10.23977/ferm.2024.070118 | Downloads: 5 | Views: 163


Yixin Qin 1, Jiaxin Xie 1, Zi Ye 1


1 School of Economics, CUEB, Capital University of Economics and Business, Beijing, 100070, China

Corresponding Author

Yixin Qin


In the superiority of freshmen, formulating reasonable replenishment and pricing strategies is a necessary measure to achieve high -quality operations and refined management. Based on the background of the fresh market and the current status of fresh retailers, the current domestic large -scale fresh products retailer H is selected to analyze the retail status of various types of fresh products for three years of H retail dealers to obtain the decline and trend of the decline in order to formulate appropriate. The pricing strategy has obtained the optimal profit. At the same time, this article is based on the relationship between Pilson's relationship digital method to dig the correlation between core elements, and obtains the correlation between different categories of vegetables at different levels; uses wavelet analysis to capture the changes in different data under different data, and obtain sales in different periods of time periods. At the peak period of quantity; use heat maps to visualize the relationship between different categories; use rose maps to directly display different category sales distribution. Through the non -linear regression model as the constraints of the ARMA time sequence prediction model, the sales and pricing of each category in each category in the next week will be obtained to formulate the best daily replenishment decision.


Related Agreement, Time Series Model, Price Problem, Replenishment Decision, Fresh Supermarket


Yixin Qin, Jiaxin Xie, Zi Ye, Research on pricing and replenishment of vegetable products based on particle group algorithms. Financial Engineering and Risk Management (2024) Vol. 7: 119-126. DOI:


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