A microscopic model for optimal train short-turnings during complete blockages. (November 2017)

• Record Type: Journal Article
• Authors: Ghaemi, Nadjla; Cats, Oded; Goverde, Rob M.P.
• Is Part Of: Transportation research. Volume 105(2017)
• Page Start: 423
• Page End: 437
• Publication Date: 2017-11
• Subjects: Microscopic optimization -- Railway disruption -- Rescheduling -- Short-turning; Transportation -- Research -- Periodicals; Transportation -- Mathematical models -- Periodicals
• DOI: 10.1016/j.trb.2017.10.002
• Languages: English
• ISSNs: 0191-2615

Abstract

Highlights: A microscopic railway rescheduling model is developed to compute the optimal short-turning choice. The model includes the optimal short-turning stations, platforms and routes based on the available capacity. The model has been tested on two Dutch railway corridors. The results confirm the advantage of including multiple short-turning stations in reducing delay propagation. The model can compute the optimal solution in a short time. 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.