Department of Computer Science
cs.aalto.fi
Bissan Ghaddar
Ivey Business School in Canada
Technical University of Denmark
Abstract: The use of machine learning techniques to improve the performance of branch-and-bound optimization algorithms is a very active area in the context of mixed integer linear problems, but little has been done for non-linear optimization. To bridge this gap, we develop a learning framework for spatial branching and show its efficacy in the context of the Reformulation-Linearization Technique for polynomial optimization problems. The proposed learning is performed offline, based on instance-specific features and with no computational overhead when solving new instances. Novel graph-based features are introduced, which turn out to play an important role in the learning. Experiments on different benchmark instances from the literature show that the learning-based branching rule significantly outperforms the standard rules.
Bio: Bissan Ghaddar is an Associate Professor of Management Science at the Ivey Business School working on problems at the intersection of smart cities, IoT, and optimization models. Prior to joining Ivey Business School, she was an Assistant Professor in Data Analytics at the Department of Management Sciences at the University of Waterloo. She has also worked on energy, water, and transportation network optimization at IBM Research and on inventory management problems at the Centre for Operational Research and Analysis, Department of National Defence Canada. She was invited for extended research visits at the Universität zu Köln in Germany and the University of Avignon in France. Dr. Ghaddar received a Ph.D. degree in operations research from the University of Waterloo, Canada. Her work has been published in prestigious journals such as Mathematical Programming, SIAM Journal on Optimization, Transportation Research, among others. Her research has been supported by national and international scholarships including NSERC, Cisco, H2020, and FP7 IIF European Union Grant.
If you would like to meet Bissan during her visit, please send an email to Mario Di Francesco ([email protected]) and Gopika Premsankar ([email protected]) to organize a meeting time.
cs.aalto.fi
The department of Information and Communications Engineering has a strong focus in the ICT area varying from ICT technology to core electrical engineering and its basic phenomena.