Collaborative optimization of bonded fuel supply chain based on combined swarm intelligence algorithm

Xuan Zhao; Shiyuan Xu

doi:10.1117/12.3011470

7 December 2023 Collaborative optimization of bonded fuel supply chain based on combined swarm intelligence algorithm

Xuan Zhao, Shiyuan Xu

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129410K (2023) https://doi.org/10.1117/12.3011470
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

Considering that the traditional bonded fuel supply chain has problems such as weak trust relationship and low cooperation efficiency, which affect the profits of supply chain node enterprises. To this end, a two-level supply chain game model based on suppliers and distributors is built. First, the particle swarm optimization algorithm is used to estimate the supplier's profit function, and the initial game strategy of the supplier is obtained accordingly. Add the neural network to the ant swarm intelligence algorithm to make it optimize the operation, and finally realize the optimal matching of supplier and distributor business. Finally, the effectiveness of the proposed method for improving the collaborative optimization of the bonded fuel supply chain is verified by experiments.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xuan Zhao and Shiyuan Xu "Collaborative optimization of bonded fuel supply chain based on combined swarm intelligence algorithm", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129410K (7 December 2023); https://doi.org/10.1117/12.3011470

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