Maintenance Appointments in Railway Rolling Stock Rescheduling

textabstractThis paper addresses the railway rolling stock rescheduling problem, while taking maintenance appointments into account. After a disruption, the rolling stock of the disrupted passenger trains has to be rescheduled to restore a feasible rolling stock circulation. Usually, a number of train units have a scheduled maintenance appointment during the day: these appointments must be taken into account while rescheduling the rolling stock. In this paper we propose three mixed-integer programming models for this purpose. All models are extensions of the composition model from the literature, which does not distinguish individual train units. The extra unit type model adds an additional rolling stock type for each train unit that requires maintenance. The shadow-account model keeps track of a shadow account for each train unit that requires maintenance. The job-composition model creates a path for each train unit such that the train units that require maintenance are on time for their maintenance appointments. All models are tested on instances of Netherlands Railways. The results showthat especially the shadow-account model and the job-composition model are effectively able to take maintenance appointments into account during real-time rescheduling. It depends on the characteristics of an instance whether the shadow-account model or the job-composition model performs best.

[1]  Leo G. Kroon,et al.  Maintenance routing for train units: The interchange model , 2007, Comput. Oper. Res..

[2]  Lars Kjaer Nielsen,et al.  Rolling Stock Rescheduling in Passenger Railways: Applications in short-term planning and in disruption management , 2011 .

[3]  Jean-François Cordeau,et al.  SIMULTANEOUS LOCOMOTIVE AND CAR ASSIGNMENT AT VIA RAIL CANADA , 1998 .

[4]  George L. Nemhauser,et al.  The aircraft rotation problem , 1997, Ann. Oper. Res..

[5]  Lucas P. Veelenturf,et al.  An overview of recovery models and algorithms for real-time railway rescheduling , 2014 .

[6]  Kalyan T. Talluri,et al.  The Four-Day Aircraft Maintenance Routing Problem , 1998, Transp. Sci..

[7]  C. Bron,et al.  Algorithm 457: finding all cliques of an undirected graph , 1973 .

[8]  Naoto Fukumura,et al.  Real-time freight locomotive rescheduling and uncovered train detection during disruption , 2012, Eur. J. Oper. Res..

[9]  Jacques Desrosiers,et al.  OPERATIONAL CAR ASSIGNMENT AT VIA RAIL CANADA , 2000 .

[10]  David K. Smith Network Flows: Theory, Algorithms, and Applications , 1994 .

[11]  Tomohiro Murata,et al.  Crew and Vehicle Rescheduling Based on a Network Flow Model and Its Application to a Railway Train Operation , 2009 .

[12]  George L. Nemhauser,et al.  Flight String Models for Aircraft Fleeting and Routing , 1998, Transp. Sci..

[13]  Ralf Borndörfer,et al.  Integrated Optimization of Rolling Stock Rotations for Intercity Railways , 2016, Transp. Sci..

[14]  Leo Kroon,et al.  Maintenance Appointments in Railway Rolling Stock Rescheduling , 2016 .

[15]  G. Maróti,et al.  Maintenance Routing for Train Units: The Transition Model , 2005, Transp. Sci..

[16]  Peter Brucker,et al.  Routing of Railway Carriages , 2003, J. Glob. Optim..

[17]  Marc Peeters,et al.  Circulation of railway rolling stock: a branch-and-price approach , 2003, Comput. Oper. Res..

[18]  Leo G. Kroon,et al.  Rescheduling of Railway Rolling Stock with Dynamic Passenger Flows , 2010, Transp. Sci..

[19]  Leo G. Kroon,et al.  A rolling stock circulation model for combining and splitting of passenger trains , 2006, Eur. J. Oper. Res..

[20]  Leo G. Kroon,et al.  A rolling horizon approach for disruption management of railway rolling stock , 2012, Eur. J. Oper. Res..

[21]  Dario Pacciarelli,et al.  Rolling Stock Rostering Optimization Under Maintenance Constraints , 2014, J. Intell. Transp. Syst..

[22]  Leena Suhl,et al.  Rotation Planning of Locomotive and Carriage Groups with Shared Capacities , 2004, ATMOS.

[23]  Gábor Maróti,et al.  Operations research models for railway rolling stock planning , 2006 .