Research on the optimization of bulk material centralized procurement cost based on adaptive optimization algorithm
Year: 2025
Type: conference-paper
Abstract: It is a key problem to optimize the purchase cost of bulk materials in the supply chain management. How to make rational purchasing decisions in the ever-changing market environment has become the focal point of academic and practical research. In this paper, an optimization model for the cost of bulk material purchase is presented based on APSO. Through the improvement of traditional PSO and the introduction of adaptive adjusting mechanism, the PSO can adjust the search strategy automatically in different purchasing environments, thus improving the global search capability and optimizing efficiency. In this paper, a number of purchase scenarios are used to validate the project. The results indicate that the APSO algorithm is effective in decreasing the purchase cost and delivery time. Compared with the conventional GA and SA, APSO reduces the total purchase cost by 12%, the delivery time is reduced by 8%, and the stability of the supply chain is greatly improved. Finally, it is proved that the model is feasible and effective in mass procurement.
Authors: Zhenyu Tian, Rui Wang
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4412790154