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Automatic Pricing and Replenishment Decision Analysis of Vegetable Products Based on ARIMA Optimization Model

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DOI: 10.23977/agrfem.2023.060310 | Downloads: 33 | Views: 404

Author(s)

Junyan Li 1

Affiliation(s)

1 School of Shipping and Naval Architecture, Chongqing Jiaotong University, Chongqing, China

Corresponding Author

Junyan Li

ABSTRACT

Due to its short shelf life, the pricing and replenishment decision of vegetables in fresh food supermarkets is often the focus of supermarkets. In this paper, we first establish and solve the Pearson correlation model between vegetable categories and sales distribution, and obtain the correlation relationship between each category and each item. Then, we establish the ARIMA prediction model to predict the replenishment quantity and pricing strategy of each vegetable category in the coming week in the fresh food superstore, and finally, we use linear programming to optimize the ARIMA prediction model to solve the automatic pricing and replenishment decision of vegetable items when the maximum revenue is obtained under the demand of the market. Finally, the ARIMA prediction model was optimized using a linear programming method to solve the automatic pricing and replenishment decision of vegetable items when meeting the market demand and maximizing the revenue. The ARIMA optimization model used in this paper can effectively predict and optimize the automatic pricing and replenishment decision of vegetable products, which is of great significance to ensure the normal operation and profit of fresh food superstores.

KEYWORDS

Vegetable Commodities, Correlation Analysis, ARIMA Model, Linear Programming Analysis

CITE THIS PAPER

Junyan Li, Automatic Pricing and Replenishment Decision Analysis of Vegetable Products Based on ARIMA Optimization Model. Agricultural & Forestry Economics and Management (2023) Vol. 6: 64-72. DOI: http://dx.doi.org/10.23977/agrfem.2023.060310.

REFERENCES

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