AGV Assignment Strategy in Express Distribution Center Based on Closed Queueing Model
DOI:
https://doi.org/10.63313/JCSFT.9090Keywords:
Closed queueing model, Assignment strategy, AGV, Express distribution centerAbstract
A rational assignment strategy can effectively reduce Automated Guided Vehicle (AGV) driving distance and improve resource utilisation. Firstly, we propose a partition assignment strategy considering the driving distance of AGV. On this basis, we propose task balanced partition assignment strategy by considering the utilisation balance of the pick-up platform. And we develop a closed queueing model to evaluate the performance of the AGV system. Secondly, we design experiments to verify the effectiveness of the theoretical model. Finally, we analyse and compare the performance of random assignment strategy, partition assignment strategy and task balanced partition assignment strategy. The results show as (1) The closed queueing model can effectively evaluate system performance. (2) Task balanced partition assignment strategy can obviously improve the system throughput. (3) The partition assignment strategy caused resource congestion when parcels arrive unevenly, while the task balanced partition assignment strategy can obviously balance the utilisation rate of the pick-up platform.
References
[1] Liangyong C, Yiming Z, Zijian G, et al. Bi-level optimization model and algorithm design for joint scheduling of unmanned trucks and AGVs in automated container terminals [J]. Journal of Harbin Engineering University, 2023, 26(06): 1-14.
[2] Mingze L, Qingcheng Z, Xingchun L. Data-driven distributionally robust optimization method for AGV assignment in automated terminals [J]. Systems Engineering — Theory & Practice, 2025, 45(04): 1375-88.
[3] Jingjing L, Minghui L, Enxian L. Research on integrated scheduling method of AGV in large-scale manufacturing workshop production logistics based on hybrid discrete state transition algorithm [J]. Information Technology and Informatization, 2025, (01): 189-92.
[4] Yiming Z, Min H, Guoshuai J, et al. Collaborative optimization of task assignment and charging scheduling in RMFS based on flexible charging strategy [J]. Industrial Engineering and Management, 2025, 30(02): 200-10.
[5] Yanju Z, Qinggang Y, Jun W, et al. Optimization method for AGV picking efficiency considering order splitting strategy [J]. Application Research of Computers, 2024, 41(11): 3258-64.
[6] Kunpeng L, Tengbo L, Yanqiu R. Intelligent AGV path planning and scheduling in semiconductor manufacturing workshops [J]. Computer Integrated Manufacturing Systems, 2022, 28(09): 2970-80.
[7] Kunpeng L, Tengbo L, Bingqian H, et al. Research on AGV path planning and scheduling in "parts-to-picker" picking system [J]. Chinese Journal of Management Science, 2021, 30(04): 240-51.
[8] Teng L, Shan F. A stochastic scheduling strategy for "parts-to-picker" picking system [J]. Industrial Engineering Journal, 2020, 23(02): 59-66.
[9] Ruiping Y, Huiling W, Lirui S, et al. Research on task scheduling of "parts-to-picker" order picking system based on logistics AGV [J]. Operations Research and Management Science, 2018, 27(10): 133-8.
[10] BOYSEN N, BRISKORN D, EMDE S. Parts-to-picker based order processing in a rack-moving mobile robots environment [J]. European Journal of Operational Research, 2017, 262(2): 550-62.
[11] MERSCHFORMANN M, LAMBALLAIS T, DE KOSTER M, et al. Decision rules for robotic mobile fulfillment systems [J]. Operations Research Perspectives, 2019, 6: 100128.
[12] Xiaopeng L, Xuanrui C, Jun L, et al. Queuing network modeling and analysis for material transport systems with multi-tier AGVs [J]. Industrial Engineering Journal, 2023, 26(06): 101-8.
[13] Chengping L. Queuing network based performance analysis and resource configuration optimization for PCB drilling workshops [D]. Guangdong: Guangdong University of Technology, 2021.
[14] ZOU B, GONG Y, XU X, et al. Assignment rules in robotic mobile fulfilment systems for online retailers [J]. International Journal of Production Research, 2017, 55(20): 6175-92.
[15] LAMBALLAIS T, ROY D, DE KOSTER M. Estimating performance in a robotic mobile fulfillment system [J]. European Journal of Operational Research, 2017, 256(3): 976-90.
[16] ROY D, NIGAM S, DE KOSTER R, et al. Robot-storage zone assignment strategies in mobile fulfillment systems [J]. Transportation Research Part E: Logistics and Transportation Review, 2019, 122: 119-42.
[17] Xinyan Z, Yasheng Z. Collision-free path planning of AGV based on improved A* algorithm [J]. Systems Engineering — Theory & Practice, 2021, 41(01): 240-6.
[18] Xuecheng H, Shujing L, Yue L. Path planning for high-density AGV parcel sorting system [J]. Computer Systems & Applications, 2019, 28(04): 39-44.
[19] BUITENHEK R, VAN HOUTUM G J, ZIJM H. AMVA‐based solution procedures for open queueing networks with population constraints [J]. Annals of Operations Research, 2000, 93(1): 15-40.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 by author(s) and Erytis Publishing Limited

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.













