journal article·2025-07-14Open access

The Environmental Impact of Inland Empty Container Movements Within Two-Depot Systems

Alaa Abdelshafie, May Salah, Tomaž Kramberger

Applied Sciences· Volume 15· Issue 14

Abstract

Inefficient inland repositioning of empty containers between depots remains a persistent challenge in container logistics, contributing significantly to unnecessary truck movements, elevated operational costs, and increased CO2 emissions. Acknowledging the importance of this problem, a large amount of relevant literature has appeared. The objective of this paper is to track the empty container flow between ports, empty depots, inland terminals, and customer premises. Additionally, it aims to simulate and assess CO2 emissions, capturing the dynamic interactions between different agents. In this study, agent-based modeling (ABM) was proposed to simulate the empty container movements with an emphasis on inland transportation. ABM is an emerging approach that is increasingly used to simulate complex economic systems and artificial market behaviours. NetLogo was used to incorporate real-world geographic data and quantify CO2 emissions based on truckload status and to evaluate the other operational aspects. Behavior Space was also utilized to systematically conduct multiple simulation experiments, varying parameters to analyze different scenarios. The results of the study show that customer demand frequency plays a crucial role in system efficiency, affecting container availability and logistical tension.
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Research context

OpenAlex topics: Urban and Freight Transport Logistics · Transportation Planning and Optimization · Maritime Ports and Logistics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of International Transport and Logistics, Arab Academy for Science, Technology and Maritime Transport, Alexandria 12577, Egypt

Faculty of Logistics, University of Maribor, 2000 Celje, Slovenia

References (61)

Show source-provided references
1. UNCTAD (2019). Review of maritime transport 2018. UNCTAD/RMT/2019, UNCTAD.
2. Song, D.-P., and Dong, J.-X. (2015). Empty container repositioning. Handbook of Ocean Container Transport Logistics, Springer.10.1007/978-3-319-11891-8_6 ↗
3. Empty container repositioning in liner shipping10.1080/03088830903056934 ↗
4. Abdelshafie, A., Salah, M., Kramberger, T., and Dragan, D. (2022). Repositioning and Optimal Re-Allocation of Empty Containers: A Review of Methods, Models, and Applications. Sustainability, 14.10.3390/su14116655 ↗
5. Tactical vessel deployment and empty container repositioning considering container turnover times10.1016/j.cie.2024.110032 ↗
6. The IMO initial strategy for reducing Greenhouse Gas (GHG) emissions, and its follow-up actions towards 2050
7. Positioning empty containers among multiple ports with leasing and purchasing considerations10.1007/s00291-010-0197-0 ↗
8. Leasing or repositioning empty containers? Determining the time-varying guide leasing prices for decision making10.1080/03088839.2020.1803431 ↗
9. Song, J., Tang, X., Wang, C., Xu, C., and Wei, J. (2022). Optimization of multi-port empty container repositioning under uncertain environments. Sustainability, 14.10.3390/su142013255 ↗
10. Planning local container drayage operations given a port access appointment system10.1016/j.tre.2007.07.004 ↗
11. Is the inland waterways system primed for mitigating road transport in Egypt?10.21622/IBL.2024.04.2.1056 ↗
12. Time Window Characteristics in a Heuristic Algorithm for a Full-Truck Vehicle Routing Heuristic Algorithm in An Intermodal Context10.25077/josi.v24.n1.p18-36.2025 ↗
13. Container drayage problem integrated with truck appointment system and separation mode10.1016/j.cie.2024.110307 ↗
14. Optimal empty vehicle repositioning and fleet-sizing for two-depot service systems10.1016/j.ejor.2006.12.034 ↗
15. Coordinating pricing and empty container repositioning in two-depot shipping systems10.1287/trsc.2020.0980 ↗
16. Analysis of empty container management
17. Olivo, A., Di Francesco, M., and Zuddas, P. (2015). An optimization model for the inland repositioning of empty containers. Port Management, Springer.10.1057/9781137475770_5 ↗
18. Notteboom, T., Pallis, A., and Rodrigue, J.-P. (2022). Port Economics, Management and Policy, Routledge.10.4324/9780429318184 ↗
19. Yu, X., Feng, Y., He, C., and Liu, C. (2024). Modeling and Optimization of Container Drayage Problem with Empty Container Constraints across Multiple Inland Depots. Sustainability, 16.10.3390/su16125090 ↗
20. Replenishment policies for empty containers in an inland multi-depot system10.1057/mel.2012.20 ↗
21. An agent-based simulation and logistics optimization model for managing uncertain demand in forest supply chains10.1016/j.sca.2023.100042 ↗
22. Modelling the dynamics of fragmented vs. consolidated last-mile e-commerce deliveries via an agent-based model10.1016/j.trpro.2022.02.020 ↗
23. Sustainability, resilience and complexity in supply networks: A literature review and a proposal for an integrated agent-based approach10.1016/j.spc.2022.01.009 ↗
24. Survey Paper—A Review of Empty Flows and Fleet Management Models in Freight Transportation10.1287/trsc.21.4.227 ↗
25. Models for multimode multicommodity location problems with interdepot balancing requirements10.1007/BF02097809 ↗
26. Dynamic and stochastic models for the allocation of empty containers10.1287/opre.41.1.102 ↗
27. Improved empty freight car distribution10.1287/trsc.32.2.163 ↗
28. Empty container management for intermodal transportation networks10.1016/S1366-5545(02)00018-2 ↗
29. Modelling a rail/road intermodal transportation system10.1016/j.tre.2003.08.005 ↗
30. Global intermodal tank container management for the chemical industry10.1016/j.tre.2005.06.004 ↗
31. An operational model for empty container management10.1057/palgrave.mel.9100136 ↗
32. Research on the optimization of intermodal empty container reposition of land-carriage
33. Regional repositioning of empty containers: Case for inland depots10.3141/2066-04 ↗
34. Heuristic-based truck scheduling for inland container transportation10.1007/s00291-010-0193-4 ↗
35. An improved particle swarm optimization for carton heterogeneous vehicle routing problem with a collection depot10.1007/s10479-015-1792-x ↗
36. Intermodal transportation of full and empty containers in harbor-inland regions based on revenue management10.1186/s12544-018-0342-4 ↗
37. Fourth IMO greenhouse gas study
38. UNCTAD (2023). Bold global action needed to decarbonize shipping and ensure just transition. UNCTAD Report, UNCTAD.
39. Englert, B., Lam, S., and Steinhoff, P. (2024, August 20). The Impact of Truck Repositioning on Congestion and Pollution in the LA Basin, Available online: https://rosap.ntl.bts.gov/view/dot/23264.
40. Schulte, F., González, R.G., and Voß, S. (2015, January 23–25). Reducing port-related truck emissions: Coordinated truck appointments to reduce empty truck trips. Proceedings of the Computational Logistics: 6th International Conference, ICCL 2015, Delft, The Netherlands.10.1007/978-3-319-24264-4_34 ↗
41. Reducing port-related empty truck emissions: A mathematical approach for truck appointments with collaboration10.1016/j.tre.2017.03.008 ↗
42. The pollution-routing problem10.1016/j.trb.2011.02.004 ↗
43. Carbon emissions from European land transportation: A comprehensive analysis10.1016/j.trd.2023.103851 ↗
44. Critical overview of emission calculation models in order to evaluate their potential use in estimation of Greenhouse Gas emissions from in port truck operations10.1016/j.jclepro.2018.02.036 ↗
45. Impacts of reducing air pollutants and CO2 emissions in urban road transport through 2035 in Chongqing, China10.1016/j.ese.2021.100125 ↗
46. Prediction and evaluation of greenhouse gas emissions for sustainable road transport within Europe10.1016/j.scs.2021.102924 ↗
47. Osama, A., Bagwari, A., and Hossam, N. (2023). The Effect of Using Intelligent Transportation Systems on Transportation-Sustainable Development in Egypt. Cases on International Business Logistics in the Middle East, IGI Global.10.4018/978-1-6684-4686-7.ch004 ↗
48. Is smart transportation associated with reduced carbon emissions? The case of China10.1016/j.eneco.2021.105715 ↗
49. Analyzing transport demand and environmental degradation: The case of G-7 countries10.1007/s10668-022-02729-1 ↗
50. Critical gaps in seagrass protection reveal the need to address multiple pressures and cumulative impacts10.1016/j.ocecoaman.2019.104946 ↗
51. Combinable containers: A container innovation to save container fleet and empty container repositioning costs10.1016/j.tre.2019.09.004 ↗
52. Optimization of empty container allocation for inland freight stations considering stochastic demand10.1016/j.ocecoaman.2022.106366 ↗
53. Macal, C.M., and North, M.J. (2005, January 4). Tutorial on agent-based modeling and simulation. Proceedings of the Winter Simulation Conference, Orlando, FL, USA.
54. Agent-based computing from multi-agent systems to agent-based models: A visual survey10.1007/s11192-011-0468-9 ↗
55. Agent-based simulation for modeling supply chains: A comparative case study
56. International container design regulations and ISO standards: Are they fit for purpose?10.1080/03088839.2018.1519862 ↗
57. Sulis, E., and Taveter, K. (2022). Agent-Based Simulation with NetLogo. Agent-Based Business Process Simulation: A Primer with Applications and Examples, Springer.10.1007/978-3-030-98816-6 ↗
58. Scheduling direct deliveries with time windows to minimise truck fleet size and customer waiting times10.1080/00207543.2018.1470696 ↗
59. The impact of container call size evidence from simulation modelling10.1016/j.martra.2024.100109 ↗
60. Efficiency analysis and benchmarking of container ports operating in lower-middle-income countries: A DEA approach10.1186/s41072-024-00163-2 ↗
61. Kipyegon, N. (2018). Inter-Organizations Technology Systems’ Data Analytics, Corridor Performance Monitoring Using the Northern Transport Corridor Observatory. [Doctoral dissertation, University of Nairobi].