Solution algorithms for the generalized train unit shunting problem (original) (raw)

Shunting of passenger train units: an integrated approach

2006

In this paper, we describe a new model for the Train Unit Shunting Problem. This model is capable of solving the matching and parking subproblems in an integrated manner, usually requiring a reasonable amount of computation time for generating acceptable solutions. Furthermore, the model incorporates complicating details from practice, such as trains composed of several train units and tracks that can be approached from two sides. Computation times are reduced by introducing the concept of virtual shunt tracks. Computational results are presented for real-life cases of NS Reizigers, the main Dutch passenger railway operator. Abstract In this paper, we describe a new model for the Train Unit Shunting Problem. This model is capable of solving the matching and parking subproblems in an integrated manner, usually requiring a reasonable amount of computation time for generating acceptable solutions. Furthermore, the model incorporates complicating details from practice, such as trains composed of several train units and tracks that can be approached from two sides. Computation times are reduced by introducing the concept of virtual shunt tracks. Computational results are presented for real-life cases of NS Reizigers, the main Dutch passenger railway operator.

A Local Search Algorithm for Train Unit Shunting with Service Scheduling

Transportation Science, 2022

In this paper we consider the Train Unit Shunting Problem extended with Service Task Scheduling. This problem originates from Dutch Railways (NS), which is the main railway operator in the Netherlands. Its urgency stems from the upcoming expansion of the rolling stock fleet needed to handle the ever increasing number of passengers. The problem consists of matching train units arriving on a shunting yard to departing trains, scheduling service tasks such as cleaning and maintenance on the available resources, and parking the trains on the available tracks such that the shunting yard can operate conflict-free. These different aspects lead to a computationally extremely difficult problem, which combines several well-known NP-hard problems. In this paper we present the first solution method covering all aspects of the shunting and scheduling problem. We describe a partial order schedule representation that captures the full problem, and we present a local search algorithm that utilizes the partial ordering. The proposed solution method is compared to an existing Mixed Integer Linear Program in a computational study on realistic instances provided by NS. We show that our local search algorithm is the first method to solve real-world problem instances of the complete shunting and

Shunting passenger trains: getting ready for departure

In this paper we consider the problem of shunting train units on a railway station. Train units arrive at and depart from the station according to a given train schedule and in between the units may have to be stored at the station. The assignment of arriving to departing train units (called matching) and the scheduling of the movements to realize this matching is called shunting. The goal is to realize the shunting using a minimal number of shunt movements.

TRAIN CIRCULATION PLANNING: QUANTITATIVE APPROACHES

1 The railway traffic system is an important player in passenger and freight transportation. This paper aims to present a survey of optimization models for the most commonly studied rail transportation problems related to train scheduling. We propose a classification of models and describe their characteristics by focusing on model structure and algorithmic aspects. Most reviewed papers have been proposed during the last decades. Apart from a few exceptions, the survey concentrates on published and easily accessible material. We have also elected to limit ourselves to contributions dealing specifically with rail transportation planning in single and double tracks. Each model has different goals, such as, to minimize service delays, to reduce the unscheduled train stops or to minimize the total time a train has to remain motionless, specially to allow crossings. For each group of problems, we propose a classification of models and describe their important characteristics by focusing on model structure and algorithmic aspects. The literature review involve papers published since the 1970s, but recent publications suggest that the problem is still heavily investigated. The main approaches considered are those that focus on Mathematical Optimization and Simulation. The review also considers the approach used to generate the solution, the type of railroad (real or hypothetical), and the infrastructure characteristics used to represent the railroad model. Our analysis focuses on showing an overview of those planning models.

Optimal train reallocation strategies under service disruptions

Train scheduling is commonly the third step in the classical hierarchical approach to railway services planning and perhaps is the phase more related to user's perception about quality of service due to the passengers' direct perception of timetables. Unfortunately, disruptions appear frequently due to an increase of the demand or as a consequence of fleet size reductions. Both circumstances give rise to un-supplied demand at certain stations, which generate passenger overloads in the available vehicles. Design strategies that guarantee reasonable users' waiting time and maintain admissible operation costs are then an important topic in this field. Traditionally, two main off-line strategies to deal with such kind of situations have been used: Short-turning and deadheading. The first one is usually used when only a few of high demand stations should be attended. With this strategy, some vehicles perform short cycles in order to increase the frequency in certain stations of the lines. The second one consists of skipping stops (deadheading) at those stations with less demand, diminishing travel times and allowing for a fast service in conflictive stations. In both cases, different approaches to this problem have been developed considering frequencies (periodic timetables) and supposing uniform demand behaviour. This paper proposes a tactical model to determine optimal policies of short-turning and non-stopping at certain stations, considering different objectives like minimizing the passenger overload and preserving certain level of quality of service. The model enables to obtain both periodic and non-periodic timetables and, in contrast with previous works, it is able to use a dynamic behavior of the demand along the complete planning horizon (usually one day). Computational results for a real case study and comparisons with previous approaches are provided.

Heuristic techniques for single line train scheduling

Journal of Heuristics, 1997

A. HIGGINS AND E. KOZAN School of Mathematics, Queensland University of Technology, PO Box 2434, QLD 4001, Australia email: A.Higgins@fsc.qut.edu.au, E.Kozan@fsc.qut.edu.au ... L. FERREIRA School of Civil Engineering, Queensland University of Technology, PO Box ...

Suboptimal control strategies for multilocomotive powered trains

IEEE Transactions on Automatic Control, 1982

Thin pcper introduces two different controllers for the handling of very long dripovered trains, including braking operati-. The deviations f r a r e f e r e n c e v a l u e due to grade changes and other pmpose of the controller is to minimize coupler force and v e l o c i t y disturbances. The controller is nuperi.lposed t o a throttling and brakin8 schedule known beforehand. As there a r e ConstrnintB on the inputs (especially the braking inputs) and the coupler forces that c-t be neglected, a linear control lav cannot be applied straightforvnrd. lberefore a switching policy is chosen such that a piecevi.e linear system results. me linear suboptimal controllers acting between the switching-ts are derived f r a No different arll scale train models using standard optfsal control design. One d e l represents a reduced order =del of the long train, the other one uses a short train configuration consisting of f&r cars cluracteristics. From the obtained weighting patterns a control Cbrn the given train, *ere the cars however preserve the original h w for the large scale system is derived. As not a l l the states are assmed to be measurable a simple observer-like structure i s used for the est-tion of the i.portant missing s t a t e s needed for the control. Simulation results are prwented for a train congrade p r o f i l e s. s i s t i n g of three locmatives and s i x t y cars operating over various

A set partitioning approach to shunting

Discrete Applied Mathematics, 2012

The Vehicle Positioning Problem (VPP), also know as the shunting problem, is a classical combinatorial optimization problem in public transport planning. It has been investigated using several models and approaches, which work well for small instances, but not for large ones. We propose in this article a novel set partitioning model and an associated column generation approach for the VPP and for a multiperiod generalization. The model provides a tight linear description of the problem and can, in particular, produce non-trivial lower bounds. The pricing problem, and hence the LP relaxation itself, can be solved in polynomial resp. pseudo-polynomial time, for some versions of the problem. Computational results for large-scale instances are reported. § The work of this author is supported by CNPq-Brazil. modeled the VPP with two-index variables as a Quadratic Assignment Problem (QAP) and used linearization techniques to solve it as an integer linear program. Hamdouni, Soumis and Desaulniers [9] extend their work exploring robustness and introducing the concept of uniform tracks to solve larger problems. Gallo and Di Miele [7] propose a three-index formulation and extend the problem to deal with vehicles of different lengths and interlaced sequences of arrivals and departures. Freling, Kroon, Lentink, and Huisman [6] and Kroon, Lentink, and Schrijver [12] improved this model by a new formulation of shunting constraints involving additional binary variables. They also consider decomposable vehicles (trains) and different types of tracks (the number of uniform tracks is assumed to be known in advance). Lentink [11] continues by a heuristic and a column generation algorithm based on a decomposition strategy for the problem. Recently, Borndörfer and Cardonha [3] combined the original binary quadratic programming model of Winter with the model improvement of Kroon, Lentink, and Schrijver [12] in order to derive the first non-trivial lower bounds for the number of shunting movements. However, all of the mentioned approaches work only satisfactorily for specifically structured or for very small instances, and, in particular, not for an integrated treatment of multi-period problems.

The Locomotive Routing Problem

Transportation Science, 2008

Given a schedule of trains, the locomotive planning (or scheduling) problem (LPP) is to determine the minimum cost assignment of locomotive types to trains that satisfies a number of business and operational constraints. Once this is done, the railroad has to determine the sequence of trains to which each locomotive is assigned by unit number so that it can be fueled and serviced as necessary. We refer to this problem as the locomotive routing problem (LRP). The LRP is a very large scale combinatorial optimization problem, and the general version that we consider has previously been unstudied and unsolved in the research literature. In this paper, we develop robust optimization methods to solve the LRP. There are two major constraints that need to be satisfied by each locomotive route: (1) locomotive fueling constraints, which require that every unit visits a fueling station at least once for every F miles of travel, and (2) locomotive servicing constraints, which require that every unit visits a service station at least once for every S miles of travel. The output of the LPP is not directly implementable because the LPP does not consider these fueling and servicing constraints. The LRP considers these constraints and its output is therefore implementable. We model the LRP by considering alternative fueling and servicingfriendly train paths (or strings) between servicing stations on the network. We formulate the LRP as an integer programming problem on a suitably constructed space-time network and show that this problem is NP-complete. This integer programming problem has millions of decision variables. We develop a fast aggregation-disaggregation based algorithm to solve the problem within a few minutes of computational time to near-optimality. Finally, we present computational results and extensive case studies of our algorithms on real data provided by a major Class I US railroad.

Advanced modelling of train operations in stations and networks

Transportation Research Part B: Methodological, 2007

When studying the papers on scheduling of railway operations published in international scientific journals, one gets the impression that many authors are not fully aware of the state-of-the-art of railway traffic engineering in different European countries, especially in Germany, France and Italy. Many papers dealt with scheduling of trains in low-frequency single-track networks typical for American rail freight transport and only a minority came from engineering disciplines. At the same time, substantial advances were being made in the theory and practice of railway operations and scheduling for highly complex, high density, scheduled rail networks in Europe and Asia by railway researchers, typically with an engineering background, but this work was not reflected in the international scientific journals for transport. Meanwhile many authors who had no close relationship with the railway industry made valiant efforts to solve scheduling problems by means of new mathematical programming techniques without having fully reviewed the current state of traffic engineering theory and practice. Furthermore, European transport deregulation policy, privatization of British Railways and European Railway Directives contributed, in first instance, to some confusion and fragmentation of the railway research community.