Airline revenue management: A simulation of dynamic capacity management

Abstract

In this paper, an event-driven stochastic simulation model mirroring a real world's revenue management system is presented. Its primary purpose is to evaluate revenue impacts of a continuously adjusted fleet assignment during the booking period. To account for realistic consumer behaviour, a demand model allowing for dependencies between booking classes is developed for the simulation. The simulation set-up and its major components as well as the input parameters are described. Then, computational results are displayed including sensitivity analyses concerning input parameters. Finally, future directions for the study of flexible capacity allocation will be given.

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Correspondence to Anika Schroeder.

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1 Michael Frank is a project manager at Lufthansa German Airlines (LH), currently working on planning process optimisation. His research interests include queuing theory, production planning and stochastic simulations.

2 Martin Friedemann is a doctoral candidate at the Clausthal University of Technology (C.UniTech) cooperating with LH. Part of his doctorial thesis will be the further investigation of dynamic capacity allocation in revenue management.

3 Michael Mederer is manager of the LH Simulation Center and Research Scientist at the C.UniTech. He has given lectures in various fields of stochastic applications and has presented at several AGIFORS operations conferences, addressing schedule robustness and airport capacity.

4 Anika Schroeder is working for her PhD sponsored by the research cooperation of the LH Simulation Center and the C.UniTech. Her research objective is the investigation of revenue management with a focus on risk considerations.

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Frank, M., Friedemann, M., Mederer, M. et al. Airline revenue management: A simulation of dynamic capacity management. J Revenue Pricing Manag 5, 62–71 (2006). https://doi.org/10.1057/palgrave.rpm.5160014

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Keywords

  • revenue management
  • dynamic fleet assignment
  • simulation
  • dependent demand