Research on Automated Pricing and Replenishment Decision for Vegetable Products based on Optimization Model

DOI

10.2991/978-94-6463-419-8_29How to use a DOI?

Keywords

Pricing and replenishment decision; Vegetable products; Random forest prediction; XGBoost regression

Abstract

In the current retail environment, efficient and accurate pricing and replenishment strategies are particularly important for vegetable products, which typically have a short shelf life and are highly volatile in market demand. In this work, we analyzed the sales data of vegetable categories and established a decision-making model for automatic pricing and replenishment of supermarkets to maximize the sales revenue of vegetables. Specifically, we established a random forest prediction model based on historical wholesale price data, which can accurately predict the wholesale price of vegetables in the coming week. Subsequently, we utilized the XGBoost regression model based on the unit price and wholesale price to evaluate the predicted wholesale prices of 33 vegetable categories. From our extensive experiments, we can observe that the model performed well with an average R2 value of more than 0.64. This indicates that the model can explain 64% of the variance in this type of data, indicating that the model has relatively good predictive power. Then, a target planning model for maximizing the revenue of supermarkets is established. By using the particle swarm optimization algorithm to solve, we successfully obtained that the total income of 33 single products on July 1 was 3001.897512 yuan under the premise of satisfying the constraints.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Tong Yang
AU  - Shengjie Xu
AU  - Jinyu Lu
AU  - Zhiyun Yu
AU  - Xinfeng Liu
PY  - 2024
DA  - 2024/05/07
TI  - Research on Automated Pricing and Replenishment Decision for Vegetable Products based on Optimization Model
BT  - Proceedings of the 3rd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2024)
PB  - Atlantis Press
SP  - 231
EP  - 239
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-419-8_29
DO  - 10.2991/978-94-6463-419-8_29
ID  - Yang2024
ER  -