Description
Leader of the group Networks and Optimization: Guido Schäfer.
In today’s society, complex systems surround us. From transport and traffic, to behavioral economics and operations management, real-world applications often demand that we identify simple, optimal solutions among a huge set of possibilities. Our research group Networks and Optimization (N&O) does fundamental research to tackle such challenging optimization problems.
We develop algorithmic methods to solve complex optimization problems efficiently. Our research provides efficient algorithms to some of the most challenging problems, for example, in planning, scheduling and routing. To come up with the best optimization algorithms, we combine and extend techniques from different disciplines in mathematics and computer science.
N&O covers a broad spectrum of optimization aspects. Our expertise ranges from discrete to continuous optimization and applies to centralized and decentralized settings. We focus on both problem-specific methods and universal toolkits to solve different types of optimization problems. The key in our investigations is to understand and exploit combinatorial structures, such as graphs, networks, lattices and matroids. Our research is of high scientific impact and contributes to various fields.
In several cooperations with industry partners, the algorithmic techniques that we develop in our group have proven useful to solve complex real-world problems. We are always interested in new algorithmic challenges arising in real-world applications and are open to new cooperations.
Watch our group video to get a glimpse of our activities.
Vacancies
PhD Student in the research project 'Mixed-Integer Non-Linear Optimisation: Algorithms and Applications' (MINOA)
The research project is part of the Marie Skłodowska-Curie Action Innovative Training Network MINOA funded under the Horizon 2020 programme. The MINOA ITN is an interdisciplinary research and training network consisting of 11 academic partners and six industrial partners in France, Germany, Italy and the Netherlands. The job is a full-time PhD position (Early Stage Researcher) in the field of Mathematical Optimization. A special focus is on the development and analysis of algorithms for polynomial optimization problems. These are non-linear optimization problems, involving polynomial constraints and variables which can be binary, continuous, or non-commutative. Such problems arise in many areas in operations research, discrete optimization and quantum information. The objective is to design new methods and algorithms using combinatorial and algebraic techniques combined with linear and semidefinite optimization.
News
CWI researchers in research consortium Gravity programme
Six research consortia in which prominent scientists from various Dutch universities work together are receiving a combined sum of 153 million euros for long-term and large-scale research.
Conditions for optimal solutions to semidefinite problems found
Most optimization problems in real-life are hard to solve optimally. However, for practical purposes it is usually sufficient to settle for near-optimal solutions that can be found quickly. Fast and more accurate approximations can be computed using semidefinite programming, a novel powerful optimization tool
Connection between graph theory and algebra deepened
PhD student Guus Regts from Centrum Wiskunde & Informatica (CWI) investigated mathematical connections between graph theory and algebra.
Current events
Highlights of Algorithms 2018 (HALG 2018)
- 2018-06-04T00:00:00+02:00
- 2018-06-06T23:59:59+02:00
Highlights of Algorithms 2018 (HALG 2018)
Start: 2018-06-04 00:00:00+02:00 End: 2018-06-06 23:59:59+02:00
The 3rd Highlights of Algorithms (HALG 2018) conference is designed to be a forum for presenting the highlights of recent developments in algorithms and for discussing potential further advances in this area. For more information and registration please visit the website.
- Web
- Email: Susanne van Dam
- Phone: 020-592 4189
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iCal
Members
Associated Members
Publications
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Kamphorst, B. (2018, May 31). Heavy-traffic behaviour of scheduling policies in queues.
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Hu, H, & Laurent, M. (2018). On the linear extension complexity of stable set polytopes for perfect graphs. European Journal of Combinatorics. doi:10.1016/j.ejc.2018.02.014
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Beurs van 1,5 miljoen voo TU/e-hoogleraar Bansal - E52.nl - 26-02-18. (2018). Beurs van 1,5 miljoen voo TU/e-hoogleraar Bansal - E52.nl - 26-02-18.
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Geelen, J, Gerards, A.M.H, & Whittle, G. (2018). Quasi-graphic matroids (corrected version of a paper that was previously retracted at the request of the authors). Journal of Graph Theory, 87(2), 253–264. doi:10.1002/jgt.22177
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Bansal, N, Böhm, M, Eliáš, M, Koumoutsos, G, & Umboh, S.W. (2018). Nested convex bodies are chaseable. In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 1253–1260). doi:10.1137/1.9781611975031.81
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Dadush, D.N, Végh, L.A, & Zambelli, G. (2018). Geometric Rescaling Algorithms for Submodular Function Minimization. In Annual ACM-SIAM Symposium on Discrete Algorithms.
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Kleer, P.S, & Schäfer, G. (2017). The impact of worst-case deviations in non-atomic network routing games. Theory of Computing Systems, 1–36. doi:10.1007/s00224-017-9829-y
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Janus, T, & de Keijzer, B. (2017). On strong equilibria and improvement dynamics in network creation games. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 161–176). doi:10.1007/978-3-319-71924-5_12
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Colini-Baldeschi, R, Goldberg, P.W, de Keijzer, B, Leonardi, S, & Turchetta, S. (2017). Fixed price approximability of the optimal gain from trade. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 146–160). doi:10.1007/978-3-319-71924-5_11
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Adamczyk, M, Borodin, A, Ferraioli, D, de Keijzer, B, & Leonardi, S. (2017). Sequential posted-price mechanisms with correlated valuations. ACM Transactions on Economics and Computation, 5(4). doi:10.1145/3157085
Current projects with external funding
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Networks
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New Frontiers in Lattice Algorithms and Design
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Verbeteren van de efficiency en prestatie van logistieke processen in de binnevaart
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Wiskundecluster DIAMANT
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Approximation Algorithms, Quantum Information and Semidefinite Optimization (AQSO)
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Combining Machine Learning and Game-theoretic Approaches for Cluster Analysis (CoMGA)
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Mixed-Integer Non-Linear Optimisation Applications (MINOA)
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Societal Impact Games (SocialACT)
Related partners
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Alma Mater Studiorum-Universita di Bologna
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Alpen-Adria-Universität Klagenfurt
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CNR Pisa
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CNRS
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CTVrede
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IBM
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Rheinische Friedrich-Wilhelmus Universitaet Bonn
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Stanford University
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Technische Universität Dortmund
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Tilburg University
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Radboud Universiteit
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Technische Universiteit Eindhoven
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Universiteit Leiden
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Universiteit van Amsterdam