Year: 2026
Type: article
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 $$\hbox {CO}_2$$ CO 2 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.
Source: Annals of Operations Research
Institution: Liverpool John Moores University
Language: English
Topic: Maritime Ports and Logistics
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,090
Funder: Liverpool John Moores University
OpenAlex ID: W7212026277