Global trade heavily relies on maritime transport, with ships carrying most of the world's goods by volume. The effective planning of ports plays a pivotal role in the smooth operation of intermodal hubs required for the timely flow of goods. Ports are dynamic entities, constantly evolving due to technological advancements, economic fluctuations, political changes, and environmental factors, demanding innovative approaches to port planning. Furthermore, the complexity of port planning is compounded by the lengthy concessions that typically span 20 to 30 years.

The project HafenPlanZEN aims at providing a tool to facilitate and improve port planning decisions. The initiative represents a collaborative endeavor involving the Hamburg Port Authority, Hamburg Port Consulting, and the University of Hamburg. HafenPlanZEN harnesses this digital infrastructure, integrating data from various digital twins, offering a comprehensive overview of the port's performance and efficiency.

Central to our project is the development of a simulation and optimization tool aimed at the assessment and enhancement of port performance. HafenPlanZEN adopts a simulation-based approach and is directly fed with data from the port’s sensors and digital twins. Simulations allow port planners to experiment with diverse new development ideas as well as their refinement using optimization techniques. Such techniques can be used to automatically aid with infrastructure-independent decisions such as timing traffic lights and defining minimal parking and handling areas. Moreover, HafenPlanZen's capabilities extend to evaluating the impact of infrastructure changes, such as the construction of a new bridge or tunnel, providing comprehensive insights into port planning and management.

The aim of berth allocation planning is to derive conflict-free vessel assignments to the quay of a container terminal. An important objective of terminal operators in this context is to provide the best possible service quality to the shipping companies, i.e., especially short waiting times. The berthing schedule resulting from solving a dynamic Berth Allocation Problem (BAP) consists of the berthing times and positions of all vessels that are expected to arrive within a certain timeframe; these vessels are scheduled according to their respective arrival and handling times. However, both these times are uncertain due to different influences, e.g., wind and wave or defect handling equipment. Deviations from the planned handling time lead to delayed vessel departures, which cause waiting times for the succeeding vessels and also can ultimately result in conflicts that may impede the schedule’s feasibility. Hence, updating or re-planning of berthing schedules can become necessary, but this is costly and may be impossible when a plan is already in execution.

Therefore, the aim of this work is to derive robust berthing schedules that enhance the schedules’ stability by considering uncertainty already in the planning phase and, thus, are resistant to uncertainties of handling times. With a robust optimization approach which is based on time buffers, uncertainty is proactively considered, resulting in more robust schedules. The results of the new approach are evaluated from an ex post perspective using real ship data from the AIS and actual ship handling times.