Doctoral researcher in optimization for robust railway timetables — ETH Zürich

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Doctoral researcher in optimization for robust railway timetables 100%, Zurich, fixed-term print Drucken 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,...). This position will be available, with an ideal starting date between August 2026 and February 2027, or further upon agreement; the planned duration of the initial contract is 18 months, after which an aptitude colloquium will determine the further continuation of the doctoral project. The total doctoral project is expected to be finished in 4 years in total. Project background The focus of this project is to understand how different timetables result in complex dynamics as response to external events (small delays, larger disruptions). The scientific challenge involves integrating those dynamics into existing timetabling models, to identify those timetables that are actually better, under delays. This research targets improvement of timetable planning models, adjusting the amount and placement of buffers, and reserve times. The project is designed in collaboration with industry player operating as railway infrastructure manager. The project bases on available solvers for non-periodic timetabling, which include MILP and Logic-Based Benders-Decomposition approaches. This research is carried out within an international cooperation with the Complex Systems group at Utrecht University, in the Netherlands. Job description

• establish and use mathematical models for large-scale timetabling scheduling, with constraints on vehicles, crew, and infrastructure, able to address placement of buffers
• design and implement a simulation-optimization view to evaluate tentative solutions, considering estimated delay dynamics and possible degrees of rescheduling, to improve proactively and reactively the robustness against small and large delays.
• quantitatively understand the usefulness of the suggested decision, estimate its sensitivity to the considered assumptions; and compared to the typical reaction in real life Profile Ideally, you have (or are about to receive) a Masters’ degree in transport sciences, management/ decision sciences, econometrics, mathematics, statistics, computer science, physics or related fields. Your research track is consistent and shows a track record, or clear potential, for analysing, modelling, control, and optimisation of transport systems. You are highly motivated and self-driven, with a clear research vision, academic ambition, and excellent communication and writing skills (fluent spoken and written English is mandatory). Moreover, the following skills are expected