Print Email Facebook Twitter A Microscopic Model for Optimal Train Short-Turnings during Complete Blockages Title A Microscopic Model for Optimal Train Short-Turnings during Complete Blockages Author Ghaemi, N. (TU Delft Transport and Planning) Cats, O. (TU Delft Transport and Planning) Goverde, R.M.P. (TU Delft Transport and Planning) Date 2017 Abstract Currently railway traffic controllers use predefined solutions (contingency plans) to deal with a disruption. These plans are manually designed by expert traffic controllers and are specific to a certain location and timetable. With a slight change in the timetable or infrastructure, these plans might not be feasible and have to be updated. Instead traffic controllers can benefit from algorithms that can quickly compute an optimal solution given a disruption specification. This paper presents a Mixed Integer Linear Programming model to compute a disruption timetable when there is a complete blockage and no train can use part of the track for several hours. The model computes the optimal short-turning stations, routes and platform tracks. In this approach short-turning as a common practice in case of complete blockages is modelled at a microscopic level of operational and infrastructural detail to guarantee feasibility of the solution. To demonstrate the functionality and applicability of the model two case studies are performed on two Dutch railway corridors. In the first case, four experiments are presented to show how different priorities can change the optimal solution including the order of services and the choice of short-turning station. In the second case the performance of the model on a big station is investigated. It is shown that the model can compute the optimal solution in a short time. Subject Microscopic optimizationRailway disruptionReschedulingShort-turning To reference this document use: http://resolver.tudelft.nl/uuid:c0e3b159-81bd-48d5-bd47-b2888f0e91d3 DOI https://doi.org/10.1016/j.trb.2017.10.002 Embargo date 2019-10-12 ISSN 0191-2615 Source Transportation Research. Part B: Methodological, 105, 423-437 Part of collection Institutional Repository Document type journal article Rights © 2017 N. Ghaemi, O. Cats, R.M.P. Goverde Files PDF Micro_short_turning.pdf 955.51 KB Close viewer /islandora/object/uuid:c0e3b159-81bd-48d5-bd47-b2888f0e91d3/datastream/OBJ/view