TY - GEN A1 - D'Andreagiovanni, Fabio A1 - Gleixner, Ambros T1 - Towards an accurate solution of wireless network design problems N2 - The optimal design of wireless networks has been widely studied in the literature and many optimization models have been proposed over the years. However, most models directly include the signal-to-interference ratios representing service coverage conditions. This leads to mixed-integer linear programs with constraint matrices containing tiny coefficients that vary widely in their order of magnitude. These formulations are known to be challenging even for state-of-the-art solvers: the standard numerical precision supported by these solvers is usually not sufficient to reliably guarantee feasible solutions. Service coverage errors are thus commonly present. Though these numerical issues are known and become evident even for small-sized instances, just a very limited number of papers has tried to tackle them, by mainly investigating alternative non-compact formulations in which the sources of numerical instabilities are eliminated. In this work, we explore a new approach by investigating how recent advances in exact solution algorithms for linear and mixed-integer programs over the rational numbers can be applied to analyze and tackle the numerical difficulties arising in wireless network design models. T3 - ZIB-Report - 16-12 Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-59010 SN - 1438-0064 ER - TY - JOUR A1 - Bauschert, Thomas A1 - Büsing, Christina A1 - D'Andreagiovanni, Fabio A1 - Koster, Arie M.C.A. A1 - Kutschka, Manuel A1 - Steglich, Uwe T1 - Network planning under demand uncertainty with robust optimization JF - IEEE Communications Magazine Y1 - 2014 U6 - https://doi.org/10.1109/MCOM.2014.6736760 VL - 52 IS - 2 SP - 178 EP - 185 ER - TY - CHAP A1 - Bley, Andreas A1 - D'Andreagiovanni, Fabio A1 - Karch, Daniel T1 - Scheduling technology migration in WDM Networks T2 - Photonic Networks, 14. 2013 ITG Symposium. Proceedings Y1 - 2013 SP - 1 EP - 5 ER - TY - GEN A1 - Büsing, Christina A1 - D'Andreagiovanni, Fabio T1 - Robust Optimization under Multiband Uncertainty T2 - 2013 Mixed Integer Programming Workshop - MIP 2013 Y1 - 2013 ER - TY - CHAP A1 - Büsing, Christina A1 - D'Andreagiovanni, Fabio T1 - A New Theoretical Framework for Robust Optimization Under Multi-Band Uncertainty T2 - Operations Research Proceedings 2012 Y1 - 2014 U6 - https://doi.org/10.1007/978-3-319-00795-3_17 SP - 115 EP - 121 ER - TY - CHAP A1 - D'Andreagiovanni, Fabio A1 - Di Lullo, Michela A1 - Felici, Giovanni A1 - Lacalandra, Fabrizio T1 - A Unified View on Tight Formulations for the Unit Commitment Problem with Optimal Transmission Switching T2 - Gaspard Monge Program for Optimization - Conference on Optimization & Practices in Industry : PGMO-COPI '14 N2 - The classical Unit Commitment Problem (UC) consists in determining the production of a set of thermal and hydro power generation units over a given time horizon, in order to meet a forecast energy demand and minimize a cost function. In the last years, in connection with the UC, increasingly attention has been given to active switching, namely the possibility of changing the topology of the transmission network by tripping some of the lines. Active switching has been indeed recognized as an important way to improve capacity and reliability of the network. Modifying the network topology is also very useful in modern electricity systems, where the penetration of on-programmable renewable energy sources is high and tends to be very concentrated in some zones of the network. As a consequence, the interest for automatic and optimized switching procedures is currently spreading. In this paper, we address the UC when complemented by active switching, thus leading to so-called Unit Commitment with Optimal Transmission Switching (UCOTS). We formulate the UCOTS as a mixed integer linear program, where we unify tight formulations recently proposed in literature for relevant subfamilies of constraints of the problem. Concerning the cost function, in our formulation we approximate the quadratic thermal cost objective function by a piecewise linear function based on perspective cuts and we propose a new simple and effective way to perturb it, with the aim of breaking symmetries induced by optimal transmission switching decision variables. Our original solution approach also exploits specialized branching priorities. Computational experiments on realistic UCOTS instances highlight that our new framework is able to find optimal and near-optimal solutions in reasonable amount of time by direct use of a state-of-the-art commercial MIP solver. Y1 - 2014 ER -