Disruption-caused railway timetable rescheduling problem and its solution

In the framework of this master thesis an adaptive large neighborhood search meta-heuristic is implemented to solve the disruption caused railway timetable rescheduling problem. The multi-objective optimisation tries to minimize the travel time of passengers, the operational costs and the deviation of the initial timetable. In collaboration with a railway consulting company, the implemented method is tested on a real railway network in an urban area. The results show that the passenger satisfaction can be improved, while taking into account slightly higher operational costs and deviation from the timetable. To apply the developed algorithm for resolving disruptions in real time, further work is needed in order to reduce the computational time.