Research on Automatic Pricing and Replenishment Decision of Vegetable Commodities Based on Machine Learning

DOI

10.2991/978-94-6463-531-7_23How to use a DOI?

Keywords

Machine learning; Association rules; Commodity sales decision; Dynamic programming optimization

Abstract

In order to enhance the sales profit of fresh food supermarkets, a universal replenishment and pricing strategy applicable to vegetable commodities is proposed. First, multiple machine learning techniques are applied to deeply explore the potential relationship between the sales volumes of different vegetable commodities, and the intrinsic connection between the sales volumes of these commodities is revealed through data analysis and modeling. Second, considering the additional costs associated with the loss of vegetables during transportation and storage, a comprehensive analysis was conducted by combining multiple constraints such as sales, demand and order quantity. Based on these factors, an optimization model with the objective of maximizing the operating profit of the supermarket is constructed. In order to verify the effectiveness of the model, data simulation experiments were conducted on the model. The experimental results show that the model performs well in improving the revenue of fresh food supermarkets, which can significantly improve the sales profit of vegetable goods, reduce losses, and optimize the replenishment and pricing strategy. This strategy has strong practicality and promotion value, and provides scientific decision support for the operation and management of fresh food supermarkets.

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  - Junyi Hu
AU  - Jiajun Zhao
AU  - Xi Huang
AU  - Xiaoying Ye
PY  - 2024
DA  - 2024/10/01
TI  - Research on Automatic Pricing and Replenishment Decision of Vegetable Commodities Based on Machine Learning
BT  - Proceedings of the 9th International Conference on Engineering Management and the 2nd Forum on Modern Logistics and Supply Chain Management (ICEM-MLSCM 2024)
PB  - Atlantis Press
SP  - 192
EP  - 204
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-531-7_23
DO  - 10.2991/978-94-6463-531-7_23
ID  - Hu2024
ER  -