Integrated Airline Scheduling: Considering Competition Effects and the Entry of the High Speed Rail

Airlines and high speed rail are increasingly competing for passengers, especially in Europe and Asia. Competition between them affects the number of captured passengers and, therefore, revenues. We consider competition between airlines (legacy and low-cost) and high speed rail. We develop a new approach that generates airline schedules using an integrated mixed integer, nonlinear optimization model that captures the impacts of airlines’ decisions on passenger demand. We estimate the demand associated with a given schedule using a nested logit model. We report our computational results on realistic problem instances of the Spanish airline IBERIA and show that the actual airline schedules are found to be reasonably close to the schedules generated by our approach. Next, we use this optimization modeling approach under multimodal competition to evaluate multiple scenarios involving entry of high speed rail into new markets. We account for the possibility of demand stimulation as a result of the new services. We validate our approach using data from markets that had an entry by high speed rail in the past. The out-of-sample validation results show a close match between the predicted and observed solutions. Finally, we use our validated model to predict the impacts of future entry by high speed rail in new markets. Our results provide several interesting and useful insights into the schedule changes, fleet composition changes, and fare changes that will help the airline cope effectively with the entry of high speed rail.

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

[2]  Cynthia Barnhart,et al.  Airline Fleet Assignment with Enhanced Revenue Modeling , 2009, Oper. Res..

[3]  Giuseppe Salvo,et al.  Modelling Airlines Competition on Fares and Frequencies of Service by Bi-level Optimization , 2011 .

[4]  Vikrant Suhas Vaze Competition and congestion in the National Aviation System : multi-agent, multi-stakeholder approaches for evaluation and mitigation , 2011 .

[5]  Diego Klabjan,et al.  Airline Crew Scheduling , 2003 .

[6]  Cynthia Barnhart,et al.  Airline Schedule Planning: Accomplishments and Opportunities , 2004, Manuf. Serv. Oper. Manag..

[7]  Jun Li,et al.  Unconstraining Methods in Revenue Management Systems: Research Overview and Prospects , 2012, Adv. Oper. Res..

[8]  Cynthia Barnhart Airline Schedule Optimization , 2009 .

[9]  Richard Robert Wickham Evaluation of forecasting techniques for short-term demand of air transportation , 1995 .

[10]  David A. Hensher,et al.  A latent class model for discrete choice analysis: contrasts with mixed logit , 2003 .

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

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

[13]  António Pais Antunes,et al.  Integrated Flight Scheduling and Fleet Assignment Under Airport Congestion , 2013, Transp. Sci..

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

[15]  George L. Nemhauser,et al.  The fleet assignment problem: Solving a large-scale integer program , 1995, Math. Program..

[16]  Cynthia Barnhart,et al.  Airline Schedule Planning: Integrated Models and Algorithms for Schedule Design and Fleet Assignment , 2004, Transp. Sci..

[17]  Mark Hansen,et al.  Airline competition in a hub-dominated environment: An application of noncooperative game theory , 1990 .

[18]  Concepción Román,et al.  Competition of high-speed train with air transport: The case of Madrid–Barcelona , 2007 .

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

[20]  C. Behrens,et al.  Intermodal Competition in the London-Paris Passenger Market: High-Speed Rail and Air Transport , 2009 .

[21]  Patrick T. Harker,et al.  Air traffic network equilibrium: Toward frequency, price and slot priority analysis , 1992 .

[22]  George L. Nemhauser,et al.  Air Transportation: Irregular Operations and Control , 2007 .

[23]  Franz Rothlauf,et al.  Gravity models for airline passenger volume estimation , 2007 .

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

[25]  Arthur E. McGarity,et al.  Design And Operation Of Civil And Environmental Engineering Systems , 1997 .

[26]  Chieh-Hua Wen,et al.  Latent class models of international air carrier choice , 2010 .

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

[28]  Jacques Desrosiers,et al.  Daily Aircraft Routing and Scheduling , 1994 .

[29]  Cynthia Barnhart,et al.  Itinerary-Based Airline Fleet Assignment , 2002, Transp. Sci..

[30]  François Soumis,et al.  Improving the Objective Function of the Fleet Assignment Problem , 2007 .

[31]  Ellis L. Johnson,et al.  Incorporating Network Flow Effects into the Airline Fleet Assignment Process , 2008, Transp. Sci..

[32]  Diego Klabjan,et al.  Attractiveness-Based Airline Network Models with Embedded Spill and Recapture , 2014 .

[33]  M. Hansen,et al.  Airlines' competition in aircraft size and service frequency in duopoly markets , 2007 .

[34]  Luis Cadarso,et al.  Robust passenger oriented timetable and fleet assignment integration in airline planning , 2013 .