Research on Optimal Replenishment and Pricing Decision of Vegetable Commodities

Fangyin Lu; Yurui Wu; Yining Tian; Yaoyao He; Wei Huo

Proceedings of the 3rd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2024, March 29–31, 2024, Wuhan, China

Research Article

Research on Optimal Replenishment and Pricing Decision of Vegetable Commodities

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@INPROCEEDINGS{10.4108/eai.29-3-2024.2347451,
    author={Fangyin  Lu and Yurui  Wu and Yining  Tian and Yaoyao  He and Wei  Huo},
    title={Research on Optimal Replenishment and Pricing Decision of Vegetable Commodities},
    proceedings={Proceedings of the 3rd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2024, March 29--31, 2024, Wuhan, China},
    publisher={EAI},
    proceedings_a={ICBBEM},
    year={2024},
    month={6},
    keywords={replenishment and pricing strategies xgboost timing prediction genetic algorithms},
    doi={10.4108/eai.29-3-2024.2347451}
}

Fangyin Lu
Yurui Wu
Yining Tian
Yaoyao He
Wei Huo
Year: 2024
Research on Optimal Replenishment and Pricing Decision of Vegetable Commodities
ICBBEM
EAI
DOI: 10.4108/eai.29-3-2024.2347451

Fangyin Lu¹, Yurui Wu¹, Yining Tian¹, Yaoyao He¹, Wei Huo¹^,*

1: Northeastern University at Qinhuangdao

*Contact email: 202113675@stu.neu.edu.cn

Abstract

In the fresh food superstore, the vegetable category has a shorter freshness period and needs to make the replenishment and pricing strategy of the day according to the historical sales and demand in order to get the maximum revenue. In this paper, for the decision-making problem of maximizing the revenue of superstores, we process the data, analyze The relationship between total sales volume of vegetable categories and cost-plus pricing, construct a superstore revenue maximization model based on the unit price and sales volume, set the constraints and parameters, and give the optimal replenishment and pricing decisions.

Keywords: replenishment and pricing strategies xgboost timing prediction genetic algorithms

Published: 2024-06-07
Publisher: EAI

: http://dx.doi.org/10.4108/eai.29-3-2024.2347451