Misalignment between truck arrivals and terminal capacity is an increasingly critical bottleneck in major seaports within the global containerised supply chain. This misalignment is largely due to unpredictable delays caused by both road congestion and terminal operation disruptions. Traditionally, Truck Appointment Systems (TAS) aimed to coordinate pick-up and drop-off activities with the use of fixed time slot reservations. However, this approach lacks the flexibility to adapt to real-time disruptions, particularly in a siloed multi facility setting.
This study proposes an integrated and dynamic multi-facility coordination framework that applies real-time Estimated Time of Arrival (ETA) data into appointment rescheduling and reassignment decisions. Through a rolling horizon approach, schedules are continuously updated to reflect the most recent system state. The scenario analysis has demonstrated that the integration of real-time ETA data can reduce total waiting times by up to 96%, with the enablement of container reassignment resulting in the most efficient outcomes. Through multi-objective optimisation, the trade-off between minimising waiting times and limiting reschedules has been assessed. Sensitivity analyses further illustrated how congestion severity, timeslot duration, and fleet sizes influence overall system performance. The results indicate that collaborative, data-driven coordination mechanisms can significantly improve port logistics efficiency, reduce port congestion, and enhance service reliability. These findings provide a foundation for the development of dynamic decision-making models that balance operational stability for terminals with minimal delays for carriers.