Spreadsheet-Based Tool for Centralized Allocation of Empty Containers in the Domestic Container Yard Network
Article Sidebar
Main Article Content
Abstract
This study develops a spreadsheet-based decision-support tool for weekly centralized allocation of empty containers from a main port to five inland container yards under limited supply and uncertain yard-level demand. Three years of weekly operational data from a case-study shipping line (2023–2025; 156 weeks) were used. The first 52 weeks were used for parameter estimation, while the remaining 104 weeks were used for model evaluation using a rolling-horizon approach. The analysis was conducted separately for 20GP and 40HQ containers.
Three allocation policies were compared: Fair-Share, Days of Supply (DOS), and Equal Shortage Probability (ESP). Their performance was evaluated using cumulative shortages and the number of weeks with shortages, with the existing operator-judgment-based practice used as the benchmark.
The results show that all three policies reduce empty-container shortages relative to the existing practice. ESP provides the best overall performance by reducing both cumulative shortages and shortage frequency, while DOS achieves comparable results for 20GP containers with simpler analysis. The findings indicate that systematic allocation rules incorporating conditions across all yards can improve allocation efficiency, reduce inter-yard imbalances, and support more consistent weekly empty-container planning.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Abdelshafie, A., Salah, M., Kramberger, T., & Dragan, D. (2022). Repositioning and optimal re-allocation of empty containers: A review of methods, models, and applications. Sustainability, 14(11), 6655. https://doi.org/10.3390/su14116655
Braekers, K., Janssens, G. K., & Caris, A. (2011). Challenges in managing empty container movements at multiple planning levels. Transport Reviews, 31(6), 681–708. https://doi.org/10.1080/01441647.2011.584979
Chen, K., Lu, Q., Xin, X., Yang, Z., Zhu, L., & Xu, Q. (2022). Optimization of empty container allocation for inland freight stations considering stochastic demand. Ocean & Coastal Management, 230, 106366. https://doi.org/10.1016/j.ocecoaman.2022.106366
Cheung, R. K., & Chen, C.-Y. (1998). A two-stage stochastic network model and solution methods for the dynamic empty container allocation problem. Transportation Science, 32(2), 142–162.
Clark, A. J., & Scarf, H. (1960). Optimal policies for a multi-echelon inventory problem. Management Science, 6(4), 475–490. https://doi.org/10.1287/mnsc.6.4.475
Crainic, T. G., Gendreau, M., & Dejax, P. (1993). Dynamic and stochastic models for the allocation of empty containers. Operations Research, 41(1), 102–126. https://doi.org/10.1287/opre.41.1.102
Dejax, P. J., & Crainic, T. G. (1987). Survey paper: A review of empty flows and fleet management models in freight transportation. Transportation Science, 21(4), 227–248. https://doi.org/10.1287/trsc.21.4.227
Eppen, G. (1979). Effects of centralization on expected costs in a multi-location newsboy problem. Management Science, 25(5), 498–501.
https://doi.org/10.1287/mnsc.25.5.498
Federgruen, A., & Zipkin, P. (1984). Approximations of dynamic, multilocation production and inventory problems. Management Science, 30(1), 69–84. https://doi.org/10.1287/mnsc.30.1.69
Fu, F., & Ji, M. (2025). Robust inventory planning of empty containers in intermodal transportation considering port congestion. Computers & Industrial Engineering, 206, 2025, 111233
https://doi.org/10.1016/j.cie.2025.111233.
Lam, S.-W., Lee, L.-H., & Tang, L.-C. (2007). An approximate dynamic programming approach for the empty container allocation problem. Transportation Research Part C: Emerging Technologies, 15(4), 265–277.
https://doi.org/10.1016/j.trc.2007.04.005
Li, X., Yang, Z., Li, M., & Hong, W. (2026) A robust optimization approach for coordinating research vessel operations and marine experimental activities. Engineering Applications of Artificial Intelligence, 179, Part 2, 2026, 115190.
https://doi.org/10.1016/j.engappai.2026.115190.
Liang, J., Ma., Z, Wang, S., Liu, H., & Tan, Z. (2024). Dynamic container slot allocation with empty container repositioning under stochastic demand,Transportation. Research Part E: Logistics and Transportation Review, 187,2024, 103603,
https://doi.org/10.1016/j.tre.2024.103603.
Song, D., Zhang, J., Carter, J., Field, T., Marshall, J., Polak, J., & Woods, J. (2005). On cost-efficiency of the global container shipping network. Maritime Policy & Management, 32(1), 15–30. https://doi.org/10.1080/0308883042000176640
United Nations Conference on Trade and Development (UNCTAD). (2023). Review of maritime transport 2023. United Nations.
Zipkin, P. H. (2000). Foundations of inventory management. McGraw-Hill.
มรกต ภู่มรกต และกมลชนก สุทธิวาทนฤพุฒิ. (2567). แนวทางการปรับปรุงกระบวนการเคลื่อนย้ายตู้คอนเทนเนอร์เปล่าจากท่าเรือแหลมฉบัง – สถานีบรรจุและแยกสินค้ากล่อง ลาดกระบัง. วารสารปฏิบัติการโลจิสติกส์และซัพพลายเชน, 10(1), 97-113.
https://doi.org/10.53848/jlscc.v10i1.264288
สุนทร ผจญ. (2567). แนวทางการเพิ่มประสิทธิภาพการขนส่งตู้สินค้าในท่าเรือแหลมฉบัง. วารสารการวิจัยการบริหารการพัฒนา, 14(2), 457–474. สืบค้น จาก https://so01.tci-thaijo.org/index.php/JDAR/article/view/274310
