Research Article
Optimization of Metal Commodity Purchasing Plan for E-commerce Platform
@INPROCEEDINGS{10.4108/eai.17-11-2023.2342696, author={Anran Li and Liang Zhang and Cong Cheng}, title={Optimization of Metal Commodity Purchasing Plan for E-commerce Platform}, proceedings={Proceedings of the 5th International Conference on Economic Management and Model Engineering, ICEMME 2023, November 17--19, 2023, Beijing, China}, publisher={EAI}, proceedings_a={ICEMME}, year={2024}, month={2}, keywords={procurement plan; bayesian linear regression; multi-objective optimization}, doi={10.4108/eai.17-11-2023.2342696} }- Anran Li
Liang Zhang
Cong Cheng
Year: 2024
Optimization of Metal Commodity Purchasing Plan for E-commerce Platform
ICEMME
EAI
DOI: 10.4108/eai.17-11-2023.2342696
Abstract
It is crucial for e-commerce platform operators to improve operational efficiency. The e-commerce platform selected in this paper is a functional platform implements centralized procurement, however, the platform's procurement plan for metal commodities does not match the demand for the commodities. In this paper, we optimize the metal commodity procurement plan in the platform. Activity based classification is used to classify metal commodities into three categories, and Bayesian linear regression prediction model considering promotion factors and sales season factors is set up. On this basis, the optimized procurement plan for metal commodities was carried out, and a multi-objective procurement quantity allocation model with cost, quality and delivery time as the optimization objectives, and minimum order quantity and maximum supply quantity as the constraints was established. Meanwhile, the NSGA-Ⅱ algorithm was applied to solve the problem. With the typical commodity, the A class commodity 4.0 model electrodes, a comparative analysis of the optimization scheme with the original scheme was carried out, which proves the validity of the optimization model.