Abstract
Mobile communication is taken for granted in these days. Having started primarily as a service for speech communication, data service and mobile Internet access are now driving the evolution of network infrastructure. Operators are facing the challenge to match the demand by continuously expanding and upgrading the network infrastructure. However, the evolution of the customer's demand is uncertain. We introduce a novel (long-term) network planning approach based on multistage stochastic programming, where demand evolution is considered as a stochastic process and the network is extended so as to maximize the expected profit. The approach proves capable of designing large-scale realistic UMTS networks with a time horizon of several years. Our mathematical optimization model, the solution approach, and computational results are presented.
Similar content being viewed by others
References
Birge JR, Louveaux F (1997) Introduction to stochastic programming. Springer series in operations research and financial engineering. Springer, Berlin
Bundesnetzagentur: Jahresbericht 2009
Dentcheva D, Ruszczyński A, Shapiro A (2009) Lectures on stochastic programming. Modeling and theory. SIAM
Geerdes HF (2008) UMTS radio network planning: mastering cell coupling for capacity optimization. PhD thesis, Technische Universität Berlin
Glasserman P (2003) Monte Carlo methods in financial engineering, stochastic modeling and applied probability, vol. 53. Springer, Berlin
Harmantzis FC, Ramirez W, Tanguturi VP (2007) Valuing wireless data services solutions for corporate clients using real options. Int J Mobile Commun 6(3): 259–280
Heitsch H (2007) Stabilität und Approximation stochastischer Optimierungsprobleme. PhD thesis, Humboldt-Universität zu Berlin
Heitsch H, Römisch W (2009) Scenario tree modeling for multistage stochastic programs. Math. Program. 118: 371–406
IBM ILOG CPLEX Optimizer. http://www.cplex.com
Koch T (2004) Rapid mathematical programming. PhD thesis, Technische Universität Berlin
Laiho, J, Wacker, A, Novosad, T (eds) (2006) Radio network planning and optimisation for UMTS. Wiley, New York
Nawrocki, M, Aghvami, H, Dohler, M (eds) (2006) Understanding UMTS radio network modelling, planning and automated optimisation: theory and practice. Wiley, New York
Schweiger J (2010) Application of multistage stochastic programming in strategic telecommunication network planning. Diploma thesis, Technische Universität Berlin
Shreve SE (2004) Stochastic Calculus for finance II: continuous-time models. Springer finance. Springer, Berlin
Trigeorgis L (1996) Real options–managerial flexibility and strategy in resource allocation. The MIT Press, Cambridge
Wang T (2005) Real options “in” projects and systems design—identification of options and solution for path dependency. PhD thesis, Massachusetts Institute of Technology, Massachusetts
Wang T, de Neufville R (2004) Building real options into physical systems with stochastic mixed-integer programming. Prepared for the 8th real options annual international conference, Montreal, Canada
Author information
Authors and Affiliations
Corresponding author
Additional information
This work is based on a diploma thesis in mathematics by Jonas Schweiger at Technische Universität Berlin, Germany.
Rights and permissions
About this article
Cite this article
Eisenblätter, A., Schweiger, J. Multistage stochastic programming in strategic telecommunication network planning. Comput Manag Sci 9, 303–321 (2012). https://doi.org/10.1007/s10287-012-0143-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10287-012-0143-5