Air Cargo Revenue Management in Variable Operating Conditions of Capacity, Considering the Possibility of Double Booking

Document Type : Research Paper

Authors

Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

Revenue Management (RM) is a subfield of operations research that aims at maximizing revenues acquired by selling perishable products/services in a specified period. Due to the substantial growth in air cargo industry over the past few years, some techniques are needed to maximize revenue. In this paper, space allocation problem in two cases including overbooking possibility and impossibility are studied. Since the proposed dynamic programming needs much memory for obtaining exact solution, three heuristics including deterministic integer linear programming (DILP), bid price (BP) and dynamic programming decomposition (DPD) are proposed. Results show that BP and DILP performance is better than other approaches. In addition, results show that when overbooking is possible, it leads to revenue increment by more than 10 percent.

Keywords


1. Talluri, K.T. and Van Ryzin, G.J. (2006). The theory and practice of revenue management (Vol. 68), Springer Science & Business Media.
2. Boeing Company (2005b). World Air Cargo Forecast 2002–2003. http://www.boeing.com/ commercial/ cargo/exec_summary.htm
3. Hendricks, G. and Kasilingam, R. (1993). Cargo revenue management at American airlines cargo, Presentation at the AGIFORS Cargo Study Group Meeting, Rome, Italy.
4. Slager, B. and Kapteijns, L. (2004). "Implementation of cargo revenue management at KLM", Journal of Revenue & Pricing Management, Vol. 3, No. 1, PP. 80–90.
5. Nielsen, K. (2004). Revenue management at virgin Atlantic cargo, Presentation at the AGIFORS Cargo Study Group Meeting, Washington DC, USA.
6. Karaesmen, I. Z. (2001). Three essays on revenue management, PhD Thesis, Columbia University.
7. Pak, K. and Dekker, R. (2004). Cargo revenue management: Bid-prices for a 0-1 multi knapsack problem (Technical report). Erasmus University, Erasmus Research Institute of Management, Rotterdam.
8. Huang, K. and Hsu, W. (2005). Revenue management for air cargo space with supply uncertainty, Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, PP. 570–580.
9. Luo, L. and Shi, X. (2006). The stochastic model of multi-leg capacity allocation for air cargo revenue management, In Proceedings of the international conference on service systems and service management, Vol. 2, pp. 917-921, 25-27 Oct, Troyes, France.
10. Popescu, A., Keskinocak, P., Johnson, E., LaDue, M. and Kasilingam, R. (2006). "Estimating air-cargo overbooking based on a discrete show-up-rate distribution", Interfaces, Vol. 36, No. 3, PP. 248–258.
11. Amaruchkul, K., Cooper, W. L. and Gupta, D. (2007). "Single-leg air-cargo revenue management", Transportation Science, Vol. 41, No. 4, PP. 457–469.
12. Huang, K. and Chang, K.C. (2010). "An approximate algorithm for the two-dimensional air cargo revenue management problem", Transportation Research: Logistics and Transportation Review, Vol. 46, No. 3, PP. 426–435.
13. Zhuang, W., Gumus, M. and Zhang, D. (2011). “A single-resource revenue management problem with random resource consumptions”, Journal of the Operational Research Society, (Advance online publication 14 December 2011, doi: 10.1057/jors.2011.129).
14. Han, D. L., Tang, L. C. and Huang, H. C. (2010). "A Markov model for single-leg air cargo revenue management under a bid-price policy", European Journal of Operational Research, Vol. 200, No. 3, PP. 800–811.
15. Levin, Y., Nediak, M. and Topaloglu, H. (2012). "Cargo capacity management with allotments and spot market demand", Operations Research, Vol. 60, No. 2, PP. 351–365.
16. Levina, T., Levin, Y., McGill, J. and Nediak, M. (2011). "Network cargo capacity management", Operations Research, Vol. 59, No. 4, PP. 1008–1023.
17. Hoffmann, R., (2013). Dynamic Capacity Control in Air Cargo Revenue Management, KIT Scientific Publishing.
18. Huang, K. and Lu, H. (2015). "A linear programming-based method for the network revenue management problem of air cargo", Transportation Research Part C: Emerging Technologies, No. 59, PP.248–259.
19. Wang, X., (2016). "Stochastic resource allocation for containerized cargo transportation networks when capacities are uncertain", Transportation Research Part E: Logistics and Transportation Review, No. 93, PP. 334–357.
20. Wannakrairot, A. and Phumchusri, N. (2016). "Two-dimensional air cargo overbooking models under stochastic booking request level, show-up rate and booking request density", Computers & Industrial Engineering, No. 100, PP. 1–12.
21. Kashan, A.H., Akbari, A.A. and Ostadi, B. (2015). "Grouping evolution strategies: An effective approach for grouping problems", Applied Mathematical Modelling, Vol. 39, No. 9, PP. 2703–2720.