A Mathematical Model for Deriving Optimal Leasing Policies of a Satellite Operator

DOI: 10.4236/ojop.2014.34005   PDF   HTML   XML   3,446 Downloads   3,909 Views  


This paper presents a dynamic mathematical model of optimal leasing allocation of satellite band-width and services in terms of expected revenues and associated risk. This tool meets the need of a Satellite Operator to determine the optimal leasing policy of the available bandwidth. A methodology and a tool for techno-economic evaluation of satellite services are developed. The output of the tool enables the policy decisions to be customized by the attitude toward risk that the company wants to apply at each time period. The study is based on inputs concerning data and services from an existing Satellite Operator and addresses a real situation. Demand and pricing data have been gathered from the international market. The decision making tool is given in the set-up of a decision tree presenting quantified alternative leasing policies and risks. Sensitivity analysis is also performed to measure the efficiency of the model.

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Sarri, E. and Papavassilopoulos, G. (2014) A Mathematical Model for Deriving Optimal Leasing Policies of a Satellite Operator. Open Journal of Optimization, 3, 43-58. doi: 10.4236/ojop.2014.34005.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Haase, E., Christensen, C.B. and Ten, C.H. (2012) Global Commercial Space Industry Indicators and Trends. Acta Astronautica, 50, 747-757.
[2] Marchese, M. and Jamalipour, A. (2005) Key Technologies and Applications of Present and Future Satellite Communications. IEEE Wireless Communications, 12, 8-9.
[3] NSR (2010) Global Assessment of Satellite Supply & Demand. 8th Edition.
[4] Wood, D. and Weigel, A. (2012) A Framework for Evaluating National Space Activity. Acta Astronautica, 73, 221236.
[5] Henri, Y. and Nozdrin, V. (2012) Economic Methods of Improving Efficient Use of the Orbit/Spectrum Resource by Satellite Systems. Space Policy, 28, 185-191.
[6] Saleh, J.H. and Padilla, J.P.T. (2007) Beyond Cost Models: Communications Satellite Revenue Models. Integrating Cost Considerations into a Value-Centric Mindset. International Journal of Satellite Communications and Networking, 25, 69-92.
[7] Bertsekas, D.P. (2007) Dynamic Programming and Optimal Control. 3rd Edition, Athena Scientific, Belmont.
[8] Ross, S.M. (1983) Introduction to Stochastic Dynamic Programming. Academic Press, New York.
[9] Maral, G. and Bousquet, M. (1998) Satellite Communications Systems: Systems, Techniques and Technology. 3rd Edition, John Wiley & Sons Ltd., New York.
[10] Sarri, E. (2007) Modelling and Techno-Economic Evaluation of Telecommunication—Satellite Services Using Optimization Techniques. Ph.D. Thesis, National Technical University of Athens, Athens.
[11] Pace, P. and Sun, Z. (2007) Demand Sensitive Model for Tuning Price over Satellite Digital Multimedia Broadcast System. IEEE Transactions on Broadcasting, 53, 329-337.
[12] Courcoubetis, C., Kelly, F.P., Siris, V.A. and Weber, R. (2000) A Study of Simple Usage-Based Charging Schemes for Broadband Networks. Telecommunications Systems, 15, 323-343.
[13] Sat, H. Greek Satellite Operator.

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