Welcome to Francis Academic Press

Academic Journal of Business & Management, 2023, 5(22); doi: 10.25236/AJBM.2023.052222.

Cross-border E-commerce Inventory Multi-agent System Construction


Dong Shuyan, Zou Anquan, Zhou Yuling, Peng Yue

Corresponding Author:
Dong Shuyan

Business School, Foshan University, Foshan, Guangdong, China


Focusing on the analysis of the problems existing in traditional cross-border e-commerce, a multi-agent system model based on machine learning is proposed, and it is applied in cross-border e-commerce inventory. The results show that the system model can better improve the efficiency of inventory management.


Cross-border E-commerce, Machine Learning, Multi-agent System Model

Cite This Paper

Dong Shuyan, Zou Anquan, Zhou Yuling, Peng Yue. Cross-border E-commerce Inventory Multi-agent System Construction. Academic Journal of Business & Management (2023) Vol. 5, Issue 22: 157-163. https://doi.org/10.25236/AJBM.2023.052222.


[1] Yang Jijun, Ai Weiwei, Fan Zhaojuan. Scenarios, governance and responses to the digital economy-enabled division of labor in the global industrial chain supply chain[J]. The Economist, 2022, 1(9): 49-58.

[2] Zang Jiyuan, Liu Yufei, Wang Baicun, et al. Research on intelligent manufacturing technology foresight and roadmap for 2035[J]. Journal of Mechanical Engineering, 2022, 58(4): 285-304.

[3] Rolf B, Jackson I, Müller M, et al. A review on reinforcement learning algorithms and applications in supply chain management [J]. International Journal of Production Research, 2022: 1-29.

[4] Lu Shaojun, Cui Longqing, Zhao T, et al. A review and outlook of artificial intelligence methods for collaborative optimization of high-end equipment manufacturing [J]. Computer Integrated Manufacturing Systems, 2022, 28(7): 1940.

[5] Liu Pingfeng, Chen Kun. Construction of manufacturing service-oriented value creation system based on multidimensional industrial big data [J]. Journal of Beijing University of Posts and Telecommunications (Social Science Edition), 2022, 24(3): 78.

[6] Wang Han, Yu Yang, Jiang Yuan. A review on the progress of communication-based multi-intelligence reinforcement learning[J]. Science in China: Information Science, 2022.

[7] Jing Mu, Jing Li. Research on inventory control strategy of fresh food supply disruption considering epidemic risk and double timeliness[J]. Operations Research and Management, 2023, 32(1): 108.

[8] Ma Xiangguo, Wang Shifeng, Xu Fengbin. Planning and simulation of emergency logistics distribution center[J]. Logistics Technology, 2023, 42(03): 72-77.

[9] Jarray R, Al-Dhaifallah M, Rezk H, et al. Parallel cooperative coevolutionary grey wolf optimizer for path planning problem of unmanned aerial vehicles[J]. Sensors, 2022, 22(5): 1826.

[10] Chen G, Su Luan, Li Huifang. Optimization of material transportation path in the context of normalized epidemic prevention and control[J]. Transportation Research, 2023, 9(1): 96.

[11] Hu Hu, Tang Ziqi, Liu Fuxin. Optimization of "No-touch" Distribution of Medical Protective Materials under Epidemic Situation[J]. China Management Science, 2023, 31(5): 152-163.

[12] Yan Liping, Guo Chengyuan, Song Kai. Real-time path selection for urban road networks based on road risk assessment[J]. Journal of Software, 2022, 34(2): 899-914.

[13] Li Shaobo, Ma Wang, Fu Guang. Application of intelligence-based supply chain network in manufacturing industry[J]. Science, Technology and Engineering, 2023, 23(13):5412-5420.

[14] Jarašūnienė A, Čižiūnienė K, Čereška A. Research on Impact of IoT on Warehouse Management[J]. Sensors, 2023, 23(4): 2213.

[15] Li JB, Wang YY, Li MK. Optimization of order reallocation in pharmaceutical e-commerce considering dynamic information updating and minimizing order splitting rate[J]. China Management Science, 2023, 31(3): 38-47.

[16] Wang Pengfei, Wang Weikang. Research on cross-domain joint operation information interaction technology based on blockchain [J]. Ship Electronic Engineering, 2023, 43(1): 106-111.

[17] Wang Liwei, Wang Nan. Digital intelligence-driven emergency intelligence management for major emergencies: new opportunities, new challenges, new trends[J]. Library and Intelligence Work, 2022, 66(16): 4