Train Scheduling in High Speed Railways: Considering Competitive Effects

Abstract The railway planning problem is usually studied from two different points of view: macroscopic and microscopic. We propose a macroscopic approach for the high-speed rail scheduling problem where competitive effects are introduced. We study train frequency planning, timetable planning and rolling stock assignment problems and model the problem as a multi-commodity network flow problem considering competitive transport markets. The aim of the presented model is to maximize the total operator profit. We solve the optimization model using realistic problem instances obtained from the network of the Spanish railway operator RENFE, including other transport modes in Spain.

[1]  Leo G. Kroon,et al.  Shunting of Passenger Train Units: An Integrated Approach , 2006, Transp. Sci..

[2]  Luis Cadarso,et al.  Integration of timetable planning and rolling stock in rapid transit networks , 2012, Ann. Oper. Res..

[3]  Peter Belobaba,et al.  Overview of Airline Economics, Markets and Demand , 2009 .

[4]  Cynthia Barnhart,et al.  An assessment of the impact of demand management strategies for efficient allocation of airport capacity , 2012 .

[5]  Ricardo García-Ródenas,et al.  Train Scheduling and Rolling Stock Assignment in High Speed Trains , 2014 .

[6]  Derek Palmer,et al.  High Speed Rail and Sustainability , 2011 .

[7]  Matteo Fischetti,et al.  Modeling and Solving the Train Timetabling Problem , 2002, Oper. Res..

[8]  Luis Cadarso Morga.  Robustness and Recoverability in Transport Logistics , 2013 .

[9]  Cynthia Barnhart,et al.  Modeling Airline Frequency Competition for Airport Congestion Mitigation , 2012, Transp. Sci..

[10]  Luis Cadarso,et al.  Improving robustness of rolling stock circulations in rapid transit networks , 2014, Comput. Oper. Res..

[11]  Shangyao Yan,et al.  A flight scheduling model for Taiwan airlines under market competitions , 2007 .

[12]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .

[13]  Andrea D'Ariano,et al.  Conflict Resolution and Train Speed Coordination for Solving Real-Time Timetable Perturbations , 2007, IEEE Transactions on Intelligent Transportation Systems.

[14]  Mark Hansen,et al.  Impact of aircraft size and seat availability on airlines' demand and market share in duopoly markets , 2005 .

[15]  Paolo Toth,et al.  A Survey of Optimization Models for Train Routing and Scheduling , 1998, Transp. Sci..

[16]  Luis Cadarso,et al.  Robust routing of rapid transit rolling stock , 2010, Public Transp..

[17]  Ricardo García-Ródenas,et al.  A demand-based weighted train delay approach for rescheduling railway networks in real time , 2013, J. Rail Transp. Plan. Manag..

[18]  Paolo Toth,et al.  Solving a real-world train-unit assignment problem , 2010, Math. Program..

[19]  Luis Cadarso,et al.  Robust rolling stock in rapid transit networks , 2011, Comput. Oper. Res..

[20]  Cynthia Barnhart,et al.  Mitigating airport congestion: market mechanisms and airline response models , 2009 .

[21]  Ferenc Szidarovszky,et al.  A multi-objective train scheduling model and solution , 2004 .