A sustainability-aware optimization framework for port-hinterland truck scheduling

Mokhtari-Moghadam, A ORCID: 0009-0001-3798-5304, Nguyen, TT ORCID: 0000-0002-3268-1790, Mohsendokht, M ORCID: 0000-0003-2271-6838, Wang, J ORCID: 0000-0003-4646-9106 and Yang, Z ORCID: 0000-0003-1385-493X (2026) A sustainability-aware optimization framework for port-hinterland truck scheduling. Annals of Operations Research. pp. 1-45. ISSN 0254-5330

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Abstract

Ports are critical gateways for trade and regional growth but also generate substantial externalities such as emissions, congestion, and safety risks. Growing maritime transport and port throughput intensify long-haul diesel truck traffic on hinterland access roads, causing peak-hour bottlenecks, long queues, and higher environmental impacts. Despite many proposed operational strategies, these challenges remain insufficiently addressed. This paper develops a mixed-integer linear programming (MILP) model for sustainable port-hinterland truck scheduling within an integrated chassis-based remote gate (CRG) and battery-electric trucks (BET) framework for short-haul transport. Using a major UK port case study with real traffic data, the model minimizes total logistics costs, including fixed investments, transport, waiting and idling times for short- and long-haul trucks, and CO2 emissions. To handle large-scale instances, a two-stage adaptive genetic algorithm (TS-AGA) is proposed and benchmarked against the MILP and a two-stage simulated annealing approach. Collaborative and non-collaborative scheduling strategies are compared to assess the benefits of coordinated decision-making. Results show that collaborative scheduling reduces total system costs by about 13.6% by better synchronizing long-haul diesel truck arrivals with short-haul battery-electric truck operations. Sensitivity analysis further examines how long-haul travel-time uncertainty affects congestion and economic performance. Overall, the proposed MILP model and TS-AGA solution approach demonstrate that coordinated truck scheduling can substantially improve the operational efficiency and sustainability of CRG-BET-based port-hinterland systems. By jointly optimizing long-haul and short-haul operations under collaborative and uncertainty-aware strategies, the study offers a practical and scalable scheduling methodology to reduce logistics costs, congestion, and emissions while supporting sustainable port-city connectivity.

Item Type:	Article
Uncontrolled Keywords:	3509 Transportation, Logistics and Supply Chains; 35 Commerce, Management, Tourism and Services; 13 Climate Action; 01 Mathematical Sciences; 08 Information and Computing Sciences; 15 Commerce, Management, Tourism and Services; Operations Research; 35 Commerce, management, tourism and services; 46 Information and computing sciences; 49 Mathematical sciences
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Civil Engineering and Built Environment (closed Aug 26)
Publisher:	Springer
Date of acceptance:	14 August 2026
Date of first compliant Open Access:	21 September 2026
Date Deposited:	21 Sep 2026 13:52
Last Modified:	21 Sep 2026 13:52
DOI or ID number:	10.1007/s10479-026-07397-2
URI:	https://researchonline.ljmu.ac.uk/id/eprint/29486

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