Optimization of Berth Allocation and Scheduling in Container Terminals

Container terminals serve as critical nodes in global supply chains, where the allocation of berthing positions and the scheduling of vessel arrivals determine operational efficiency, throughput and environmental footprint. The berth allocation problem aims to assign incoming ships to discrete quay segments while respecting quay crane non-crossing constraints and vessel size, whereas berth scheduling determines the timing sequence to minimise waiting times and tardiness. Optimising these processes requires coordination among multiple resources—including quay cranes (QCs), automated guided vehicles (AGVs) and yard cranes—and must account for uncertainties in vessel arrivals and handling durations. Solution techniques span exact mixed-integer linear programming for small instances, simulation-based approaches for handling stochastic elements, and a range of heuristics and metaheuristics such as simulated annealing, large neighbourhood search and self-adaptive evolutionary algorithms. Advances also integrate energy consumption and CO₂ emissions into optimisation objectives, aligning terminal operations with sustainability targets. These developments support digitalisation trends, offering real-time decision support and enabling container terminals worldwide to enhance productivity, reduce costs and mitigate environmental impacts.

Research from Nature Portfolio

Recent studies have quantified energy consumption and carbon dioxide emissions across parallel and perpendicular container terminal layouts by analysing fuel and electricity usage of each handling equipment category. A comparative case study demonstrated that both layout types yield similar emissions per TEU, within a narrow range, suggesting flexibility in layout choice without compromising sustainability. Detailed statistical analysis identified which equipment—such as yard cranes or AGVs—dominates energy use, providing actionable insights for future layout planning and operational pattern optimisation to achieve greener terminal operations.

Optimization of Berth Allocation and Scheduling in Container Terminals publication trend

The graph below shows the total number of articles in optimization of berth allocation and scheduling in container terminals across all publications each year (not limited to Nature Index journals).

Technical terms

Berth allocation problem: Assigning vessels to specific quay positions along a terminal while respecting spatial and equipment constraints.

Berth scheduling: Sequencing and timing of vessel arrivals and departures to minimise waiting times and ensure efficient terminal flow.

Quay crane (QC): Large crane located on the quay used to load and unload containers from vessels.

Automated guided vehicle (AGV): Driverless vehicle used within terminals to transport containers between quay cranes and yard stacks.

Mixed-integer linear programming (MILP): Mathematical optimisation where some decision variables are restricted to integer values, used to model discrete operational decisions.

Large neighbourhood search (LNS): Metaheuristic that iteratively destroys and repairs large parts of a solution to explore diverse regions of the solution space.

References

1. Coordinated optimization of equipment operations in a container terminal. Flexible Services and Manufacturing Journal (2019).
2. Evaluation of CO2 emissions and energy use with different container terminal layouts. Scientific Reports (2021).
3. Discretization-Strategy-Based Solution for Berth Allocation and Quay Crane Assignment Problem. Journal of Marine Science and Engineering (2022).
4. A Self-Adaptive Evolutionary Algorithm for the Berth Scheduling Problem: Towards Efficient Parameter Control. Algorithms (2018).