Airline Revenue Management with Shifting Capacity

Airline revenue management is the practice of controlling the booking requests such that the planes are filled with the most profitable passengers. In revenue management the capacities of the business and economy class sections of the plane are traditionally considered to be fixed and distinct capacities. In this paper, we give up this notion and instead consider the use of convertible seats. A row of these seats can be converted from business class seats to economy class seats and vice versa. This offers an airline company the possibility to adjust the capacity configuration of the plane to the demand pattern at hand. We show how to incorporate the shifting capacity opportunity into a dynamic, network-based revenue management model. We also extend the model to include cancellations and overbooking. With a small test case we show that incorporating the shifting capacity opportunity into the revenue management decision indeed provides a means to improve revenues.

[1]  Gabriel R. Bitran,et al.  An Application of Yield Management to the Hotel Industry Considering Multiple Day Stays , 1995, Oper. Res..

[2]  Marvin Hersh,et al.  A Model for Dynamic Airline Seat Inventory Control with Multiple Seat Bookings , 1993, Transp. Sci..

[3]  Richard Freling,et al.  Mathematical programming for network revenue management revisited , 2002, Eur. J. Oper. Res..

[4]  Richard Van Slyke,et al.  Finite Horizon Stochastic Knapsacks with Applications to Yield Management , 2000, Oper. Res..

[5]  K. Talluri,et al.  An Analysis of Bid-Price Controls for Network Revenue Management , 1998 .

[6]  Ioana Popescu,et al.  Revenue Management in a Dynamic Network Environment , 2003, Transp. Sci..

[7]  Yigao Liang,et al.  Solution to the Continuous Time Dynamic Yield Management Model , 1999, Transp. Sci..

[8]  Tim Baker,et al.  A Comparative Revenue Analysis of Hotel Yield Management Heuristics , 1999 .

[9]  Janakiram Subramanian,et al.  Airline Yield Management with Overbooking, Cancellations, and No-Shows , 1999, Transp. Sci..

[10]  Shaler Stidham,et al.  The Underlying Markov Decision Process in the Single-Leg Airline Yield-Management Problem , 1999, Transp. Sci..

[11]  E R Kraft,et al.  REVENUE MANAGEMENT IN RAILROAD APPLICATIONS , 2000 .

[12]  M. Geraghty,et al.  Revenue Management Saves National Car Rental , 1997 .

[13]  Larry Weatherford,et al.  Length of Stay Heuristics: Do They Really Make a Difference? , 1995 .

[14]  Garrett J. van Ryzin,et al.  A Randomized Linear Programming Method for Computing Network Bid Prices , 1999, Transp. Sci..

[15]  Gabriel R. Bitran,et al.  Managing Hotel Reservations with Uncertain Arrivals , 1996, Oper. Res..

[16]  Richard Freling,et al.  Models and techniques for hotel revenue management using a rolling horizon , 2001 .

[17]  Laura Palagi,et al.  A Mathematical Programming Approach for the Solution of the Railway Yield Management Problem , 1999, Transp. Sci..