Optimising railway timetable robustness using random search metaheuristics
J.P. Jaspers (TU Delft - Electrical Engineering, Mathematics and Computer Science)
R.M.P. Goverde – Mentor (TU Delft - Civil Engineering & Geosciences)
T.M.L. Janssen – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
L.J.J. van Iersel – Graduation committee member (TU Delft - Electrical Engineering, Mathematics and Computer Science)
E. Lorist – Graduation committee member (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
When designing a railway timetable, it is important to consider that small delays can frequently occur. If a timetable can recover from small delays and this leads to little hindrance for other trains, we call this a robust timetable. Time supplement is planned in a timetable to improve robustness. Finding the best possible allocation of time supplement is computationally expensive. In this thesis, we instead use a group of algorithms called metaheuristics, which try to efficiently explore a search space to find near-optimal solutions. These metaheuristics are used to reallocate time supplement in a timetable. The timetable is only modified within a network, without requiring changes to the timetable outside of this network.
A graph-based model is used to evaluate timetables created by the metaheuristics based on a set of delay scenarios. These delay scenarios first consisted of sampled entrance delays and dwell times, later also fluctuations in running time were added. A computational study on the Utrecht-Arnhem corridor showed that metaheuristics are suitable for improving allocation of time supplement within limited time. Therefore, metaheuristics deserve more attention in future research to improve the robustness of railway timetables.