The introduction of the shipping container revolutionised global trade by significantly reducing handling costs, improving efficiency and enabling intermodal transportation. This development paved the way for the expansion of international trade and the development of highly interconnected global supply chains. Congestion, sustainability concerns, and vulnerability to disruption have become major obstacles. Recent examples of such obstacles are the COVID-19 pandemic and the blockage of the Suez Canal. Synchromodality has been identified as a potential solution for mitigating some of these concerns.

As a relatively new concept, synchromodality has mainly been studied at a theoretical level, focusing on its definition and potential. As the concept of synchromodality seems to gain attention from a broader public, more recent research has also focused on the more quantitative side. These quantitative studies primarily model the transport planning side of synchromodality. In these studies, some aspects in the supply chain have been overlooked so far, mainly the impact on critical infrastructure such as container terminals.

This research addresses this overlooked area in the existing academic landscape. Aspects such as the loading, unloading and stacking of containers are explicitly modelled in combination with synchromodal transport planning optimisation. This allows for an assessment of how synchromodality influences container terminal operations and how constraints and the dynamics at container terminals influence the transport planning. A multi-agent system approach is used as a framework for this model, as this presents a good option to model the different stakeholders involved in synchromodal transport.

The performance was analysed based on key performance metrics, including container relocation frequency, dwell times, and cost efficiency. The findings indicate that the integration of synchromodal transport planning with container terminal operations yields significant improvements. An iterative feedback loop between the transport planning agent and terminal agents facilitates more effective decision-making, leading to feasible transport planning, smoother operations, and improved resource utilisation.

Scenario analysis yielded further interesting results in terms of how a synchromodal planner would adapt to disruptions. The two most interesting findings are a decrease in the number of transshipments and a modal shift towards faster, more flexible, but also more expensive and more polluting transport modes.

In conclusion, this research demonstrates that the integration of synchromodal transport planning and container terminal operations improves the efficiency and adaptability of synchromodal logistics networks. Through these advances, this research contributes to ongoing efforts in the planning of synchromodal transport and the optimisation of container terminals, offering valuable information for both academia and industry.