Nadine Friesen: Robust Infrastructure
Associate doctoral researcher
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The extended planning periods and the long life cycle of railway infrastructure require a long planning horizon. Therefore, bottlenecks in the infrastructure have to be recognized at an early stage to initiate adequate measures. At the present, the infrastructure is planned while only little about the intended operation is known. Hence, the timetable and the operation are adjusted to the infrastructure. Since space, time and money for extension measures of railway infrastructure are limited, each modification has to be done carefully and long lasting. To meet the customers’ future needs, infrastructural projects have to planned such that the infrastructure will be appropriate for the future unknown demand.
2 -3 Chapter about Details:
For the long-term service life of the planned infrastructure, it makes sense to include timetable scenarios in the planning in order to be able to expand the railroad infrastructure, which is already reaching its capacity limits on some lines, in a targeted manner.
The aim of the project is to provide a procedure for timetable-based, robust infrastructure planning to complement the previous infrastructure-based timetable construction. In doing so, the idea of a long-term timetable and the infrastructure adaptation based on it will be precisely defined and further developed. For this purpose, infrastructure planning is modeled as a network design problem under uncertainties. Subsequently, a solution is to be found by means of robust optimization.
The term "robustness" is generally understood as the ability of a method to find a correct solution even under uncertain input data. In the context of this project, the timetables are not yet fixed until the end of the infrastructure's service life and are thus still uncertain at the time of infrastructure planning. For example, it is not a realistic scenario to run only one timetable throughout, but likewise infrastructure cannot be held in reserve for every scenario, no matter how unlikely, for both financial and spatial reasons. In the context of this project, both the various, potential timetable scenarios as well as the actual operational scenarios are to be included in the considerations. For this purpose, the uncertain input data will be modeled in a first step. In the context of the project, it is first determined which criteria for a "similarity" of timetable scenarios have to be fulfilled to which extend. Subsequently, infrastructure planning is modeled as a network design problem. Here, a solution is to be found for which new edges, i.e. track sections, are needed and for which edges the capacity should be increased. This solution should ensure the feasibility of all planned timetable scenarios at the lowest possible cost.
A first deterministic optimization model has been implemented. In a next step, the uncertainty set of timetables has to be defined and the robust counterpart of the model has to be implemented. These timetable sets should consider minimum headway times which depend on the train sequences. Afterwards the running time of the optimization problem, which is increased due to the incorporation of the temporal aspect, should be reduced by finding heuristics. Finally, the remaining capacity for the timetable set should be determined.