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Airline revenue management: an overview of OR techniques 1982-2001

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  • Pak, K.
  • Piersma, N.

Abstract

With the increasing interest in decision support systems and the continuous advance of computer science, revenue management is a discipline which has received a great deal of interest in recent years. Although revenue management has seen many new applications throughout the years, the main focus of research continues to be the airline industry. Ever since Littlewood (1972) first proposed a solution method for the airline revenue management problem, a variety of solution methods have been introduced. In this paper we will give an overview of the solution methods presented throughout the literature.

Suggested Citation

  • Pak, K. & Piersma, N., 2002. "Airline revenue management: an overview of OR techniques 1982-2001," Econometric Institute Research Papers EI 2002-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:584
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    References listed on IDEAS

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    1. Chatwin, Richard E., 2000. "Optimal dynamic pricing of perishable products with stochastic demand and a finite set of prices," European Journal of Operational Research, Elsevier, vol. 125(1), pages 149-174, August.
    2. S. L. Brumelle & J. I. McGill, 1993. "Airline Seat Allocation with Multiple Nested Fare Classes," Operations Research, INFORMS, vol. 41(1), pages 127-137, February.
    3. Youyi Feng & Guillermo Gallego, 1995. "Optimal Starting Times for End-of-Season Sales and Optimal Stopping Times for Promotional Fares," Management Science, INFORMS, vol. 41(8), pages 1371-1391, August.
    4. Guillermo Gallego & Garrett van Ryzin, 1997. "A Multiproduct Dynamic Pricing Problem and Its Applications to Network Yield Management," Operations Research, INFORMS, vol. 45(1), pages 24-41, February.
    5. Anton J. Kleywegt & Jason D. Papastavrou, 2001. "The Dynamic and Stochastic Knapsack Problem with Random Sized Items," Operations Research, INFORMS, vol. 49(1), pages 26-41, February.
    6. Garrett van Ryzin & Jeff McGill, 2000. "Revenue Management Without Forecasting or Optimization: An Adaptive Algorithm for Determining Airline Seat Protection Levels," Management Science, INFORMS, vol. 46(6), pages 760-775, June.
    7. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    8. Fred Glover & Randy Glover & Joe Lorenzo & Claude McMillan, 1982. "The Passenger-Mix Problem in the Scheduled Airlines," Interfaces, INFORMS, vol. 12(3), pages 73-80, June.
    9. Tak C. Lee & Marvin Hersh, 1993. "A Model for Dynamic Airline Seat Inventory Control with Multiple Seat Bookings," Transportation Science, INFORMS, vol. 27(3), pages 252-265, August.
    10. Wen Zhao & Yu-Sheng Zheng, 2000. "Optimal Dynamic Pricing for Perishable Assets with Nonhomogeneous Demand," Management Science, INFORMS, vol. 46(3), pages 375-388, March.
    11. Youyi Feng & Baichun Xiao, 2000. "A Continuous-Time Yield Management Model with Multiple Prices and Reversible Price Changes," Management Science, INFORMS, vol. 46(5), pages 644-657, May.
    12. Richard Van Slyke & Yi Young, 2000. "Finite Horizon Stochastic Knapsacks with Applications to Yield Management," Operations Research, INFORMS, vol. 48(1), pages 155-172, February.
    13. Youyi Feng & Guillermo Gallego, 2000. "Perishable Asset Revenue Management with Markovian Time Dependent Demand Intensities," Management Science, INFORMS, vol. 46(7), pages 941-956, July.
    14. Anton J. Kleywegt & Jason D. Papastavrou, 1998. "The Dynamic and Stochastic Knapsack Problem," Operations Research, INFORMS, vol. 46(1), pages 17-35, February.
    15. Renwick E. Curry, 1990. "Optimal Airline Seat Allocation with Fare Classes Nested by Origins and Destinations," Transportation Science, INFORMS, vol. 24(3), pages 193-204, August.
    16. Peng-Sheng You, 1999. "Dynamic Pricing in Airline Seat Management for Flights with Multiple Flight Legs," Transportation Science, INFORMS, vol. 33(2), pages 192-206, May.
    17. Conrad J. Lautenbacher & Shaler Stidham, 1999. "The Underlying Markov Decision Process in the Single-Leg Airline Yield-Management Problem," Transportation Science, INFORMS, vol. 33(2), pages 136-146, May.
    18. Lawrence W. Robinson, 1995. "Optimal and Approximate Control Policies for Airline Booking with Sequential Nonmonotonic Fare Classes," Operations Research, INFORMS, vol. 43(2), pages 252-263, April.
    19. Richard D. Wollmer, 1992. "An Airline Seat Management Model for a Single Leg Route When Lower Fare Classes Book First," Operations Research, INFORMS, vol. 40(1), pages 26-37, February.
    20. Yigao Liang, 1999. "Solution to the Continuous Time Dynamic Yield Management Model," Transportation Science, INFORMS, vol. 33(1), pages 117-123, February.
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    Cited by:

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    2. Daniel Y. Mo & Stephen C. H. Ng & David Tai, 2019. "Revamping NetApp’s Service Parts Operations by Process Optimization," Service Science, INFORMS, vol. 49(6), pages 407-421, November.
    3. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    4. Quante, R. & Meyr, H. & Fleischmann, M., 2007. "Revenue Management and Demand Fulfillment: Matching Applications, Models, and Software," ERIM Report Series Research in Management ERS-2007-050-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Andreea Popescu & Earl Barnes & Ellis Johnson & Pinar Keskinocak, 2013. "Bid Prices When Demand Is a Mix of Individual and Batch Bookings," Transportation Science, INFORMS, vol. 47(2), pages 198-213, May.

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