http://repub.eur.nl/res/aut/5705/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/22613/ 2010-12-10T00:00:00Z Traditional rolling stock rescheduling applications either treat passengers as static objects whose influence on the system is unchanged in a disrupted situation, or they treat passenger behavior as a given input. In case of disruptions however, we may expect the flow of passengers to change significantly. In this paper we present a model for passenger flows during disruptions and we describe an iterative heuristic for optimizing the rolling stock to the disrupted passenger flows. The model is tested on realistic problem instances of NS, the major operator of passenger trains in the Netherlands. http://repub.eur.nl/res/pub/16557/ 2009-08-18T00:00:00Z This paper deals with real-time disruption management of rolling stock in passenger railway transportation. We present a generic framework for modeling disruptions in railway rolling stock schedules. The framework is presented as an online combinatorial decision problem where the uncertainty of a disruption is modeled by a sequence of information updates. To decompose the problem we propose a rolling horizon approach where only rolling stock decisions within a certain time horizon from the time of rescheduling are taken into account. The schedules are then revised as the situation progresses and more accurate information becomes available. We extend an existing model for rolling stock scheduling to the specific requirements of the real-time case and apply it in the rolling horizon framework. We perform computational tests on instances constructed from real life cases and explore the consequences of different settings of the approach for the trade-off between solution quality and computation time. http://repub.eur.nl/res/pub/18643/ 2009-02-01T00:00:00Z In December 2006, Netherlands Railways introduced a completely new timetable. Its objective was to facilitate the growth of passenger and freight transport on a highly utilized railway network and improve the robustness of the timetable, thus resulting in fewer operational train delays. Modifications to the existing timetable, which was constructed in 1970, were not an option; additional growth would require significant investments in the rail infrastructure. Constructing a railway timetable from scratch for about 5,500 daily trains was a complex problem. To support this process, we generated several timetables using sophisticated operations research techniques. Furthermore, because rolling-stock and crew costs are principal components of the costs of a passenger railway operator, we used innovative operations research tools to devise efficient schedules for these two resources. The new resource schedules and the increased number of passengers resulted in an additional annual profit of 40 million ($60 million); the additional revenues generated approximately 10 million of this profit. We expect this profit to increase to 70 million ($105 million) annually in the coming years. However, the benefits of the new timetable for the Dutch society as a whole are much greater: more trains are transporting more passengers on the same railway infrastructure, and these trains are arriving and departing on schedule more than they ever have in the past. In addition, the rail transport system will be able to handle future transportation demand growth and thus allow cities to remain accessible to more people. Therefore, we expect that many will switch from car transport to rail transport, thus reducing the emission of greenhouse gases. http://repub.eur.nl/res/pub/13767/ 2008-11-10T00:00:00Z In December 2006, Netherlands Railways introduced a completely new timetable. Its objective was to facilitate the growth of passenger and freight transport on a highly utilized railway network, and improve the robustness of the timetable resulting in less train delays in the operation. Further adjusting the existing timetable constructed in 1970 was not option anymore, because further growth would then require significant investments in the rail infrastructure. Constructing a railway timetable from scratch for about 5,500 daily trains was a complex problem. To support this process, we generated several timetables using sophisticated operations research techniques, and finally selected and implemented one of these timetables. Furthermore, because rolling-stock and crew costs are principal components of the cost of a passenger railway operator, we used innovative operations research tools to devise efficient schedules for these two resources. The new resource schedules and the increased number of passengers resulted in an additional annual profit of 40 million euros ($60 million) of which about 10 million euros were created by additional revenues. We expect this to increase to 70 million euros ($105 million) annually in the coming years. However, the benefits of the new timetable for the Dutch society as a whole are much greater: more trains are transporting more passengers on the same railway infrastructure, and these trains are arriving and departing on schedule more than they ever have in the past. In addition, the rail transport system will be able to handle future transportation demand growth and thus allow cities to remain accessible. Therefore, people can switch from car transport to rail transport, which will reduce the emission of greenhouse gases. http://repub.eur.nl/res/pub/13601/ 2008-07-01T00:00:00Z Real-time railway operations are subject to stochastic disturbances. Thus a timetable should be designed in such a way that it can cope with these disturbances as well as possible. For that purpose, a timetable usually contains time supplements in several process times and buffer times between pairs of consecutive trains. This paper describes a Stochastic Optimization Model that can be used to allocate the time supplements and the buffer times in a given timetable in such a way that the timetable becomes maximally robust against stochastic disturbances. The Stochastic Optimization Model was tested on several instances of NS Reizigers, the main operator of passenger trains in the Netherlands. Moreover, a timetable that was computed by the model was operated in practice in a timetable experiment on the so-called “Zaanlijn”. The results show that the average delays of trains can often be reduced significantly by applying relatively small modifications to a given timetable. http://repub.eur.nl/res/pub/10345/ 2007-06-21T00:00:00Z This paper addresses the Rolling Stock Balancing Problem (RSBP). This problem arises at a passenger railway operator when the rolling stock has to be re-scheduled due to changing circumstances. These problems arise both in the planning process and during operations. The RSBP has as input a timetable and a rolling stock schedule where the allocation of the rolling stock among the stations does not fit to the allocation before and after the planning period. The problem is then to correct these off-balances, leading to a modified schedule that can be implemented in practice. For practical usage of solution approaches for the RSBP, it is important to solve the problem quickly. Therefore, the focus is on heuristic approaches. In this paper, we describe two heuristics and compare them with each other on some (variants of) real-life instances of NS, the main Dutch passenger railway operator. Finally, to get some insight in the quality of the proposed heuristics, we also compare their outcomes with optimal solutions obtained by solving existing rolling stock circulation models. http://repub.eur.nl/res/pub/10346/ 2007-06-21T00:00:00Z In this paper we describe Operations Research (OR) models and techniques that can be used for determining (cyclic) railway timetables. We discuss the two aspects of railway timetabling: ($i$) the determination of arrival and departure times of the trains at the stations and other relevant locations such as junctions and bridges, and ($ii$) the assignment of each train to an appropriate platform and corresponding inbound and outbound routes in every station. Moreover, we discuss robustness aspects of both subproblems. http://repub.eur.nl/res/pub/8527/ 2007-01-31T00:00:00Z 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. http://repub.eur.nl/res/pub/8291/ 2006-12-20T00:00:00Z Real-time railway operations are subject to stochastic disturbances. However, a railway timetable is a deterministic plan. Thus a timetable should be designed in such a way that it can cope with the stochastic disturbances as well as possible. For that purpose, a timetable usually contains time supplements in several process times and buffer times between pairs of consecutive trains. This paper describes a Stochastic Optimization Model that can be used to allocate the time supplements and the buffer times in a given timetable in such a way that the timetable becomes maximally robust against stochastic disturbances. The Stochastic Optimization Model was tested on several instances of NS Reizigers, the main operator of passenger trains in the Netherlands. Moreover, a timetable that was computed by the model was operated in practice in a timetable experiment on the so-called “Zaanlijn”. The results show that the average delays of trains can often be reduced significantly by applying relatively small modifications to a given timetable. http://repub.eur.nl/res/pub/14199/ 2006-10-16T00:00:00Z This paper addresses the railway rolling stock circulation problem. Given the departure and arrival times as well as the expected numbers of passengers, we have to assign the rolling stock to the timetable services. We consider several objective criteria that are related to operational costs, service quality and reliability of the railway system. Our model is an extension of an existing rolling stock model for routing train units along a number of connected train lines. The extended model can also handle underway combining and splitting of trains. We illustrate our model by computational experiments based on instances of NS Reizigers, the main Dutch operator of passenger trains. http://repub.eur.nl/res/pub/14170/ 2005-11-01T00:00:00Z Train units need regular preventive maintenance. Given the train units that require maintenance in the forthcoming one to three days, the rolling stock schedule must be adjusted so that these urgent units reach the maintenance facility in time. Maróti and Kroon (2004) propose a model that requires a large amount of input data. In this paper we describe a less involved multicommodity flow type model for this maintenance routing problem. We study the complexity of the problem. It turns out that the feasibility problem for a single urgent train unit is polynomially solvable but the optimization version is NP-hard. Finally, we report our computational experiments on practical instances of NS Reizigers, the main Dutch operator of passenger trains.