@misc{KosterOrlowskiRaacketal.2007, author = {Koster, Arie M.C.A. and Orlowski, Sebastian and Raack, Christian and Bayer, Georg and Engel, Thomas}, title = {Single-layer Cuts for Multi-layer Network Design Problems}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-9641}, number = {07-21}, year = {2007}, abstract = {We study a planning problem arising in SDH/WDM multi-layer telecommunication network design. The goal is to find a minimum cost installation of link and node hardware of both network layers such that traffic demands can be realized via grooming and a survivable routing. We present a mixed-integer programming formulation that takes many practical side constraints into account, including node hardware, several bitrates, and survivability against single physical node or link failures. This model is solved using a branch-and-cut approach with problem-specific preprocessing and cutting planes based on either of the two layers. On several realistic two-layer planning scenarios, we show that these cutting planes are still useful in the multi-layer context, helping to increase the dual bound and to reduce the optimality gaps.}, language = {en} } @misc{KosterKutschkaRaack2011, author = {Koster, Arie M.C.A. and Kutschka, Manuel and Raack, Christian}, title = {Robust Network Design: Formulations, Valid Inequalities, and Computations}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-13890}, number = {11-34}, year = {2011}, abstract = {Traffic in communication networks fluctuates heavily over time. Thus, to avoid capacity bottlenecks, operators highly overestimate the traffic volume during network planning. In this paper we consider telecommunication network design under traffic uncertainty, adapting the robust optimization approach of Bertsimas and Sim [2004]. We present three different mathematical formulations for this problem, provide valid inequalities, study the computational implications, and evaluate the realized robustness. To enhance the performance of the mixed-integer programming solver we derive robust cutset inequalities generalizing their deterministic counterparts. Instead of a single cutset inequality for every network cut, we derive multiple valid inequalities by exploiting the extra variables available in the robust formulations. We show that these inequalities define facets under certain conditions and that they completely describe a projection of the robust cutset polyhedron if the cutset consists of a single edge. For realistic networks and live traffic measurements we compare the formulations and report on the speed up by the valid inequalities. We study the "price of robustness" and evaluate the approach by analyzing the real network load. The results show that the robust optimization approach has the potential to support network planners better than present methods.}, language = {en} }