Postdoctoral researcher in optimization for robust railway timetables — ETH Zürich
Role overview
Postdoctoral researcher in optimization for robust railway timetables
Despite the excellent quality of public transport systems in Switzerland, the railway system needs to increase its performance (quality, for instance, travel time, and delays) and capacity (amount of services run) and attract more travellers to match the ambitious targets from policy and environmental goals. One key aspect of traditional railway transport systems is their plan, which is based on predetermined routes, lines, and scheduled times, with little possibility of adjusting to unplanned and unexpected circumstances. On the other hand, delays and disruption might affect many services throughout a network by means of propagation. The project focuses on timetable planning that is able to minimize delays and their impacts.
To do so, large-scale optimisation addresses the railway timetabling problem. Typically Mixed Integer Linear Programming approaches are used, which are mathematically complex, and with some limits, when modelling real-life complexity. Incorporating robustness against delays is an additional important aspect. This project assumes that we are able to quantify how small delays develop and propagate throughout the network; how larger disruptions develop and propagate in the network. Given this, we want to determine robust timetables, with suitable choice of buffers and running time reserves. Those timetables, under delays, are able to perform quantitatively better (i.e. less delays, fewer larger delays,...).
Description
Postdoctoral researcher in optimization for robust railway timetables
Despite the excellent quality of public transport systems in Switzerland, the railway system needs to increase its performance (quality, for instance, travel time, and delays) and capacity (amount of services run) and attract more travellers to match the ambitious targets from policy and environmental goals. One key aspect of traditional railway transport systems is their plan, which is based on predetermined routes, lines, and scheduled times, with little possibility of adjusting to unplanned and unexpected circumstances. On the other hand, delays and disruption might affect many services throughout a network by means of propagation. The project focuses on timetable planning that is able to minimize delays and their impacts.
To do so, large-scale optimisation addresses the railway timetabling problem. Typically Mixed Integer Linear Programming approaches are used, which are mathematically complex, and with some limits, when modelling real-life complexity. Incorporating robustness against delays is an additional important aspect. This project assumes that we are able to quantify how small delays develop and propagate throughout the network; how larger disruptions develop and propagate in the network. Given this, we want to determine robust timetables, with suitable choice of buffers and running time reserves. Those timetables, under delays, are able to perform quantitatively better (i.e. less delays, fewer larger delays,...).
