Optimal Reinsertion of Cancelled Train Lines

One recovery strategy in case of a major disruption in a rail network is to cancel all trains on a specific line of the network. When the disturbance has ended, the cancelled line must be reinserted as soon as possible. In this article we present a mixed integer programming (MIP) model for calculating the best way to reinsert cancelled train lines in a rail network covered by a periodic timetable. Using a high abstraction level it has been possible to incorporate the temporal aspect in the model only relying on the information embedded in the train identification numbers of each departure. The model finds the optimal solution in an average of 0.5 CPU seconds in each test case

The Rolling Stock Recovery Problem

DSB S-tog (S-tog) operates on the double tracked, suburban network surrounding Copenhagen, Denmark. S-tog is the sole operator on the network. The network is owned and controlled by the infrastructure manager BaneDanmark. During the last years there has been an increased focus on developing tools to aid the planning process in railway transportation. The tools are computer software, which can fully or partly automate some part of the planning process. As in other industries the initial focus has been on strategic, tactical and operational planning. Only lately focus has turned to the area of short term and real time planning. This paper concentrates on the area of rolling stock real time planning. In practice rolling stock dispatchers monitor the operation of the rolling stock plan and the depot plans. When the rolling stock plan is disrupted, the rolling stock dispatcher makes real time decisions on the re-assignments of train units to train tasks. This process is called recovery. An automated tool will improve the recovery process, help supplying sufficient seat capacity for passengers and reduce the operating cost

Robustness and Recovery in Train Scheduling - a simulation study from DSB S-tog a/s

This paper presents a simulation model to study the robustness of timetables of DSB S-tog a/s, the city rail of Copenhagen. Dealing with rush hour scenarios only, the simulation model investigates the effects of disturbances on the S-tog network. Several timetables are analyzed with respect to robustness. Some of these are used in operation and some are generated for the purpose of investigating timetables with specific alternative characteristics

Disruption Management in Passenger Railway Transportation

This paper deals with disruption management in passenger railway transportation. In the disruption management process, many actors belonging to different organizations play a role. In this paper we therefore describe the process itself and the roles of the different actors. Furthermore, we discuss the three main subproblems in railway disruption management: timetable adjustment, and rolling stock and crew re-scheduling. Next to a general description of these problems, we give an overview of the existing literature and we present some details of the specific situations at DSB S-tog and NS. These are the railway operators in the suburban area of Copenhagen, Denmark, and on the main railway lines in the Netherlands, respectively. Since not much research has been carried out yet on Operations Research models for disruption management in the railway context, models and techniques that have been developed for related problems in the airline world are discussed as well. Finally, we address the integration of the re-scheduling processes of the timetable, and the resources rolling stock and crew

Robustness and Recovery in Train Scheduling - a Case Study from DSB S-tog a/s

This paper presents a simulation model to study the robustness of timetables of DSB S-tog a/s, the city rail of Copenhagen. Dealing with rush hour scenarios only, the simulation model investigates the effects of disturbances on the S-tog network. Several timetables are analyzed with respect to robustness. Some of these are used in operation and some are generated for the purpose of investigating timetables with specific alternative characteristics