This project presents a comprehensive study on the development of Integrated Water and Land-based Transportation (IWLT) Systems for city logistics. The research addresses the growing challenges of urban traffic by proposing a decision model for multi-modal transportation systems that leverages waterways alongside traditional road networks. The problem is defined as a two-echelon multi-trip location routing problem with satellite synchronisation (2E-MTLRP-SS), incorporating capacitated vehicles, multiple depots and time constraints. A decomposition-based decision model is introduced, breaking down the problem into manageable sub-problems interconnected through synchronisation in time, space, and load. The decision model uses metaheuristics to be able to handle large-scale, realistic problems and provide feasible solutions for real-life applications. The model’s effectiveness is demonstrated through a case study in Amsterdam, showing the potential of IWLT systems to reduce congestion-related issues and improve the livability of cities. Different scenarios for the IWLT system are investigated, to assist Amsterdam's system developers in making design choices for implementation. The proposed decision model is widely applicable to multi-modal transportation systems all over the world.

In recent years, shared mobility systems have had a growing presence in cities all over the world. This is understandable given its numerous advantages such as the reduced need for personal vehicle ownership, reduced traffic congestion and emissions, increased parking efficiency, and cost savings for users. Overall, shared mobility systems offer the potential to revolutionize transportation, providing individuals with more options and helping to create more sustainable, livable cities. For shared mobility systems to fully deliver their benefits, vehicle availability must be maintained at the right place and time. If the vehicle distribution is not optimal, it may lead to overcrowding and shortages which in turn will discourage usage and lead to reduced revenues for the operator. Therefore, ensuring proper balancing of supply and demand is crucial for the success of the shared mobility service. One way to balance supply and demand is through physically rebalancing vehicles within the service area. In this study, a simulation-based optimization model is created and used to determine the optimal rebalancing operations while quantifying system improvement. A case study is conducted using real data from the Dutch moped sharing provider Felyx to examine the impact of performing rebalancing operations in Eindhoven throughout May ’22. The results demonstrate a potential increase in profit of up to 2.06%. By performing the recommended rebalancing actions several times a week in each city where the operator is active, a significant amount of extra profit can be made. This additional profit will even rise as the usage of shared mobility rises in general.