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
Postdoc in the research project "Approximation Algorithms, Quantum Information and Semidefinite Optimization"
The research project “Approximation algorithms, quantum information and semidefinite optimization” aims to explore the limits of efficient computation within classical and quantum computing, using semidefinite optimization as a main unifying tool. The position involves research into the mathematical and computer science aspects of approximation algorithms for discrete optimization, quantum entanglement in communication, and complexity of fundamental problems in classical and quantum computing. More information about the project can be found at this website.
News
Large H2020 grant for optimisation research project ‘MINOA’
Recently, the EU granted the Mixed-Integer Non-Linear Optimisation Applications (MINOA) project, as part of the Horizon 2020 Research and Innovation Framework Programme. The project is a collaborative European Training Network, with 12 research partners, CWI being one of them.
Monique Laurent elected as Fellow of SIAM
CWI researcher Monique Laurent is elected as a Fellow of the international Society for Industrial and Applied Mathematics – SIAM. This prestigious Fellowship honours SIAM members who have made outstanding contributions to these fields. Laurent, who is a member of the management team of CWI and a professor at Tilburg University, receives the fellowship for her contributions to discrete and polynomial optimization and revealing interactions between them.
Rubicon grants for David de Laat and Alessandro Zocca
CWI researchers David de Laat and Alessandro Zocca both received an NWO Rubicon grant. De Laat will study new techniques to compute optimal packings at MIT for one year, and Zocca will study renewables and uncertainty in future power systems at Caltech for two years. NWO granted these subsidies to 22 young, highly promising research talents to gain international research experience at foreign top institutes.
Better ranking for big data using seriation solution
The recent availability of large data sets leads to the challenge of identifying patterns and structures in them. These patterns can be deployed to improve the user experience
Members
Associated Members
Publications
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Geelen, J, Gerards, A.M.H, & Whittle, G. (2017). Quasi-graphic matroids (corrected version of a paper that was previously retracted at the request of the authors). Journal of Graph Theory. doi:10.1002/jgt.22177
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Laurent, M, & Seminaroti, M. (2017). Similarity-First Search: A new algorithm with application to Robinsonian matrix recognition. SIAM Journal on Discrete Mathematics, 31(3), 1765–1800. doi:https://doi.org/10.1137/16M1056791
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Gribling, S.J, de Laat, D, & Laurent, M. (2017). Lower bounds on matrix factorization ranks via noncommutative polynomial optimization.
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de Klerk, E, Lasserre, J.B, Laurent, M, & Sun, Z. (2017). Bound-constrained polynomial optimization using only elementary calculations. Mathematics of Operations Research, 42(3), 834–853. doi:10.1287/moor.2016.0829
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Apt, K.R, de Keijzer, B, Rahn, M.M, Schäfer, G, & Simon, S.E. (2017). Coordination games on graphs. International Journal of Game Theory. doi:10.1007/s00182-016-0560-8
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Kleer, P.S, & Schäfer, G. (2017). Potential function minimizers of combinatorial congestion games: Efficiency and computation. In EC 2017 - Proceedings of the 2017 ACM Conference on Economics and Computation (pp. 223–240). doi:10.1145/3033274.3085149
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Laurent, M, & Tanigawa, S.-I. (2017). Perfect elimination orderings for symmetric matrices.
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de Klerk, E, & Laurent, M. (2017). Comparison of Lasserre's measure-based bounds for polynomial optimization to bounds obtained by simulated annealing.
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de Klerk, E, Laurent, M, Sun, Z, & Vera, J.C. (2017). On the convergence rate of grid search for polynomial optimization over the simplex. Optimization Letters, 11(3), 597–608. doi:10.1007/s11590-016-1023-7
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de Klerk, E, Laurent, M, & Sun, Z. (2017). Convergence analysis for Lasserre’s measure-based hierarchy of upper bounds for polynomial optimization. Mathematical Programming, 162(1), 363–392. doi:10.1007/s10107-016-1043-1
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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Real Time Verkeersdata voor Goederenvervoer (ITSLOG)
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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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Hogeschool van Amsterdam
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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