To build and operate a modern telecommunication network economically, the uncertainty of demand forecasts and the evolution of the network over time must already be better taken into account during the planning phase. Demands evolve over time and the capacity planning as well as commodity routing for the telecommunications network should be re-adapted at specific time instants in the future.
Goal of this project is to develop mathematical models and optimization algorithms which build up an economic and efficient network taking future extensions into consideration.
Main factors that influence the resulting network are (a) the forecasting of demands and their uncertainty which define the required capacities to be installed per stage, as well as (b) the forecasting of price evolution and its uncertainty for the different network technology elements.
The problems are formulated as mixed integer programs and/or stochastic programs and the algorithms developed should be efficient in computational complexity and should exhibit provable (near) optimality.
The resulting solution should provide the installation actions as well as building cost per time period depending on different demand and pricing scenarios and assumptions on routing.

Publications

2014
A fast hybrid primal heuristic for multiband robust capacitated network design with multiple time periods Applied Soft Computing, Vol.26, pp. 497-507, 2014 (preprint available as ZIB-Report 14-40) Fabio D'Andreagiovanni, Jonatan Krolikowski, Jonad Pulaj PDF (ZIB-Report)
BibTeX
DOI
Multiperiod Network Optimization
A hybrid primal heuristic for Robust Multiperiod Network Design EvoApplications 2014, Lecture Notes in Computer Science, 2014 (preprint available as ) Fabio D'Andreagiovanni, Jonatan Krolikowski, Jonad Pulaj PDF
BibTeX
Multiperiod Network Optimization