Fabio D’Andreagiovanni (Google Scholar Account)
Department of Mathematical Optimization, Zuse Institute Berlin (ZIB)
Department of Mathematics and Computer Science, Freie Universität Berlin
Faculty of Mechanical Engineering and Transport Systems, Technische Universität Berlion
Over the last years, Robust Optimization (RO) has emerged as an effective and efficient methodology to tackle data uncertainty in real-world optimization problems. RO takes into account data uncertainty in the shape of hard constraints that restrict the feasible set and maintain only robust solutions, i.e. solutions that remain feasible even when the values of the input data change.
In this talk, I will provide an overview of my research about theory and applications of RO. Specifically, I will present Multiband Robustness (Büsing and D’Andreagiovanni 2012), a new model for RO proposed to generalize and refine the classical Gamma-robustness model by Bertsimas and Sim. The main aim of the model is to provide an improved representation of arbitrary non-symmetric distributions of the uncertainty, which are commonly present in real-world applications. Such refined representation grants a reduction in conservatism of robust solutions, while maintaining the accessibility and computational tractability that have been a key factor of success of Gamma-robustness. I will also provide an overview of applications of the Multiband model to real-world problems that I have considered in past and ongoing industrial research projects.
Fabio D’Andreagiovanni (email@example.com) is Head of the Research Group “Mathematics of Telecommunications” at the Department of Mathematical Optimization of Zuse Institute Berlin (ZIB) and Lecturer at Freie Universität and Technische Universität Berlin. He received his Ph.D. in Operations Research from Sapienza Università di Roma (2010) and was a research scholar in the Department of Industrial Engineering and Operations Research at Columbia University in the City of New York (2008–2009). His research has focused on developing strong formulations and efficient exact and heuristic algorithms for Mixed Integer Programming problems and on theory and applications of Robust Optimization. He has especially worked in the optimization of telecommunications and energy systems. His research on real-world (robust) network design has received several awards, such as the Accenture M.Sc. Prize 2006, the INFORMS Telecom Doctoral Dissertation Award 2010, the ESF-JSPS Excellence Award “Mathematics for Innovations” 2012 and the INFORMS Telecom Best Paper Award 2014.
Location, Date and Time
Ecole Polytechnique, in the Alain Turing Building (see map), in the Marcel-Paul Schützenberger seminar room.
- March 16, 2016 at noon