The Port of Antwerp is the second-largest container port in Europe. The rising demand for container transport requires significant investments in infrastructure projects. Macomi helps the Port of Antwerp to determine the effect of different projects on the throughput of the port using simulation. In this thesis, the aim is to create algorithms for the introduced online variant of the lock scheduling problem which are applicable for a real-time simulation. In addition, an algorithmic approach to recover the existing schedule when a vessel is delayed is required. To achieve these goals, three online lock scheduling algorithms are introduced and tested on realistic problem instances. Their run-time is negligible compared to exact methods and the resulting lock schedules are competitive. Assuming a constant lockage duration during scheduling allows the number of interactions to be reduced significantly with a small decrease in lock schedule quality. The online lock scheduling algorithms could also be applied to the problem of disruption management. The results are comparable to the high-performing adaptive large neighbourhood search meta-heuristic.

For the past 10 weeks, we have been tasked with improving the performance of the transaction monitoring system of bunq, an internationally active mobile bank. bunq has requested that we improve this system by automating the training of the machine learning model, providing better input data for this model and creating additional machine learning models. During this project, we have been working at the offices of bunq on this system. This thesis will give an overview of our research, software design process and implementation.