Photo credit SJ
Railways have an expensive infrastructure. The process of planning activities relevant to railways is highly complex and consists of many steps that have different planning horizons and involve various players. One part of this planning process is to schedule crew for trains that provide public railway transport. This research project therefore addresses the question how railway operators can handle disruptions and reschedule their crew efficiently. The long-term goal is to develop an optimisation-based decision support tool that can help planners to handle disruptions in a cost-efficient manner that also considers the schedules’ quality.
Photo credit SJ
Efficient solution within a limited amount of time
Since disruptions are handled online, it is important that the decision support tool is able to propose a new, high-quality plan quickly. From an optimisation perspective, this means that the implemented methods need to offer an efficient solution within a limited amount of time. For this purpose, we intend to develop matheuristic methods that utilise machine learning to choose a suitable search space.
This project is conducted within KAJT (Capacity in the Railway Traffic System), a research programme for improved railway system performance.
