Abstract
In this paper we present a mathematical programming based approach for revenue management in cargo airlines. The approach is based on a modified version of a multicommodity network flow model which has been developed in a decision support approach for schedule planning in cargo airlines. We think that using the same concept for planning and revenue management is essential for consistency of planning and operation. To meet the real-time requirements of revenue management special computational strategies for solving the large models are necessary.
Similar content being viewed by others
References
Ahuja RK, Magnanti TL, Orlin JB (1993) Network flows: theory, algorithms, and applications. Prentice Hall, Englewood Cliffs
Antes J, Campen L, Derigs U, Titze C, Wolle G-D (1998) SYNOPSE: a model-based decision support system for the evaluation of flight schedules for cargo airlines. Decis Support Syst 22:307–323
Bartodziej P, Derigs U (2004) On an experimental algorithm for revenue management for cargo airlines. In: Lecture notes in computer science 3059. Springer, Berlin Heidelberg New York, pp 57–71
Berge ME, Hopperstad CA (1993) Demand driven dispatch: a method for dynamic aircraft capacity assignment, models and algorithms. Oper Res 41(1):153–168
Billings JS, Diener AG, Yuen BB (2003) Cargo revenue optimization. J Revenue Pricing Manage 2:69–79
Cross RG (1997) Revenue management: hard core tactics for market domination. Broadway Books, New York
Derigs U, Zils M (2001) Strategisches Controlling: Strategic Alliance Portfolio Analysis (SAP) - ein modellbasierter Ansatz zur Strategie- und Partnerselektion bei Strategischen Allianzen. In: ZfB-Ergänzungsheft 2/2001, pp 137–159
Etschmaier MM, Mathaisel DF (1985) Arline scheduling: an overview. Transp Sci 19(2):127–138
Elmasri R, Navathe SB (2004) Fundamentals of database systems, 4 edn. Pearson Education, Boston
Gershkoff I (1998) An approach for just-in-time airline scheduling, chapter 6. In: Yu G (ed) Operations research in the airline industry, Kluwer, Dordrecht, pp 158–188
Kasilingam RG (1996) Air cargo revenue management: characteristics and complexities. Eur J Oper Res 96:36–44
Kleywegt AJ, Papastavrou JD (1998) The dynamic and stochastic knapsack problem. Oper Res 46:17–35
Kleywegt AJ, Papastavrou JD (2001) The dynamic and stochastic knapsack problem with random sized items. Oper Res 49:26–41
McGill JI, van Ryzin GJ (1999) Revenue management: research overview and prospects. Transp Sci 33(2):233–256
Pak K, Dekker R (2004) Cargo revenue management: Bid-prices for a 0-1 multi knapsack problem, ERIM Report Series Research in Management 55, Erasmus University Rotterdam
Pompeo L, Sapountzis T (2002) Freight expectations. McKinsey Q 2:90–99
Slager B, Kapteijns L (2004) Implementation of cargo revenue management at KLM. J Revenue Pricing Manage 3:80–90
Talluri KT, van Ryzin GJ (2004) The theory and practice of revenue management. Springer, Berlin Heidelberg New York
Zils M (1998) C.A.R.M.A.—Cargo Airline Relative Market Share Analyst: An O&D-based market model for flight network design in the Air Cargo industry, Working Paper, WINFORS, University of Cologne, Germany
Zils M (1999) AirCargo Scheduling Problem Benchmark Instanzen, Working Paper, WINFORS, University of Cologne, Germany
Acknowledgements
We want to thank two anonymous referees for their valuable comments on an earlier version of this paper.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Bartodziej, P., Derigs, U. & Zils, M. O&D revenue management in cargo airlines—a mathematical programming approach. OR Spectrum 29, 105–121 (2007). https://doi.org/10.1007/s00291-005-0019-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00291-005-0019-y