• Guillermo Gallego
  • Huseyin Topaloglu
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 279)


Early on, many airlines adopted the policy of not penalizing booked customers for canceling reservations at any time before departure. Some would not even penalize those that did not show up for booked flights. In essence, an airline ticket was “like money” since it could be used at full face value for a future flight or redeemed for cash at any future date. In the sixties, no-shows were becoming a problem for airlines who found that flights that were fully booked were departing with many empty seats. In response, the airlines began to overbook as a means of hedging against no-shows. If a flight had more passengers show than there were seats available, then the airlines would bump some passengers. The bumped passengers would be re-booked on a later flight. In addition, bumped passengers would be given other compensation, often a meal at the airport and a discount certificate applicable to future travel. The cost to the airline of bumping a passenger is called the denied boarding cost. The denied boarding cost would include the cost of putting a bumped passenger on another flight to her destination, the cost of any direct compensation to the bumped passenger, the cost of the meals or lodging that the airline provides to each bumped passenger, and the cost of “ill will” incurred by bumping the passenger. These costs can be different for each flight. For example, a passenger bumped from the last flight of the day will be provided with a hotel room at the airline’s expense.


  1. N. Aydin, S.I. Birbil, J.B.G. Frenk, N. Noyan, Single-leg airline revenue management with overbooking. Transp. Sci. 47 (4), 560–583 (2013)CrossRefGoogle Scholar
  2. R.E. Chatwin, Multiperiod airline overbooking with a single fare class. Oper. Res. 46 (6), 805–819 (1998)CrossRefGoogle Scholar
  3. R.E. Chatwin, Continuous-time airline overbooking with time-dependent fares and refunds. Transp. Sci. 33 (2), 182–191 (1999)CrossRefGoogle Scholar
  4. J. Dai, A. Kleywegt, Y. Xiao, Network revenue management with cancellations and no-shows. Prod. Oper. Manag. 8(2), 292–318 (2019)CrossRefGoogle Scholar
  5. A. Erdelyi, H. Topaloglu, Separable approximations for joint capacity control and overbooking decisions in network revenue management. J. Revenue Pricing Manag. 8 (1), 3–20 (2009)CrossRefGoogle Scholar
  6. A. Erdelyi, H. Topaloglu, A dynamic programming decomposition method for making overbooking decisions over an airline network. INFORMS J. Comput. 22 (3), 443–456 (2010)CrossRefGoogle Scholar
  7. I. Karaesmen, G. van Ryzin, Overbooking with substitutable inventory classes. Oper. Res. 52 (1), 83–104 (2004a)CrossRefGoogle Scholar
  8. I. Karaesmen, G. van Ryzin, Coordinating overbooking and capacity control decisions on a network. Technical report, Columbia Business School (2004b)Google Scholar
  9. A. Kleywegt, An optimal control problem of dynamic pricing. Technical report, Georgia Institute of Technology, Atlanta, GA (2001)Google Scholar
  10. S. Kunnumkal, H. Topaloglu, A stochastic approximation algorithm to compute bid prices for joint capacity allocation and overbooking over an airline network. Nav. Res. Logist. 58 (4), 323–343 (2011b)CrossRefGoogle Scholar
  11. S. Kunnumkal, K. Talluri, H. Topaloglu, A randomized linear programming method for network revenue management with product-specific no-shows. Transp. Sci. 46 (1), 90–108 (2012)CrossRefGoogle Scholar
  12. C.J. Lautenbacher, S. Stidham, The underlying Markov decision process in the single-leg airline yield management problem. Transp. Sci. 33 (2), 136–146 (1999)CrossRefGoogle Scholar
  13. M. Rothstein, An airline overbooking model. Transp. Sci. 5 (2), 180–192 (1971)CrossRefGoogle Scholar
  14. J.L. Simon, An almost practical solution to airline overbooking. J. Trans. Econ. Policy 2 (2), 201–202 (1968)Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Guillermo Gallego
    • 1
  • Huseyin Topaloglu
    • 2
  1. 1.Clearwater BayHong Kong
  2. 2.ORIECornell UniversityNew YorkUSA

Personalised recommendations