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.
Video about our collaboration with ProRail (in Dutch)
Vacancies
PhD students / Early Stage Researchers on the subject of Polynomial Optimization, Efficiency through Moments and Algebra.
Centrum Wiskunde & Informatica (CWI) has vacancies in the Networks and Optimization research group for two talented PhD students / Early Stage Researchers on the subject of Polynomial Optimization, Efficiency through Moments and Algebra. The vacancies are within the research consortium POEMA (Polynomial Optimization, Efficiency through Moments and Algebra).
News
CWI-mathematician proves: altruism does not necessarily lead to better outcomes in game theory
New mathematical research shows that consideration for others does not always lead to the best outcome - that is, when it’s applied in game theory.
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
Members
Associated Members
Publications
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Chen, J.-J, Bansal, N, Chakraborty, S, & von der Brüggen, G. (2018). Packing sporadic real-time tasks on identical multiprocessor systems. In 29th International Symposium on Algorithms and Computation (pp. 71:1–71:14). doi:10.4230/LIPIcs.ISAAC.2018.71
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Dadush, D.N, Nikolov, A, Talwar, K, & Tomczak-Jaegermann, N. (2018). Balancing vectors in any norm. In Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS (pp. 1–10). doi:10.1109/FOCS.2018.00010
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Carvalho Rodrigues, F, Schäfer, G, & Xavier, E.C. (2018). On the effectiveness of connection tolls in fair cost facility location games. In Proceedings of the 19th Italian Conference on Theoretical Computer Science (pp. 36–47).
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van Heuven van Staereling, I.I. (2018). Tree decomposition methods for the periodic event scheduling problem. In OpenAccess Series in Informatics. doi:10.4230/OASIcs.ATMOS.2018.6
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Carstens, C.J, & Kleer, P.S. (2018). Speeding up switch Markov chains for sampling bipartite graphs with given degree sequence. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2018) (pp. 36:1–36:18). doi:10.4230/LIPIcs.APPROX-RANDOM.2018.36
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Amanatidis, G, Birmpas, G, & Markakis, V. (2018). Comparing approximate relaxations of envy-freeness. In IJCAI International Joint Conference on Artificial Intelligence (pp. 42–48).
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Bansal, N, Dadush, D.N, Garg, S, & Lovett, S. (2018). The Gram-Schmidt Walk: A Cure for the Banaszczyk Blues. In Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2018 (pp. 587–597). doi:10.1145/3188745.3188850
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Dadush, D.N, & Huiberts, S. (2018). A friendly smoothed analysis of the simplex method. In Proceedings of the Annual ACM Symposium on Theory of Computing (pp. 214–227). doi:10.1145/3188745.3188826
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Kamphorst, B. (2018, May 31). Heavy-traffic behaviour of scheduling policies in queues.
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Amanatidis, G, Green, B, & Mihail, M. (2018). Connected realizations of joint-degree matrices. Discrete Applied Mathematics. doi:10.1016/j.dam.2018.04.010
Current projects with external funding
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Continuous Methods in Discrete Optimization ()
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Smart Heuristic Problem Optimization
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Wiskundecluster DIAMANT
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Approximation Algorithms, Quantum Information and Semidefinite Optimization (AQSO)
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Mixed-Integer Non-Linear Optimisation Applications (MINOA)
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Polynomial Optimization, Efficiency through Moments and Algebra (POEMA)
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Vóórkomen en voorkómen van incidenten op het spoor (PPS Prorail)
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Towards a Quantitative Theory of Integer Programming (QIP)
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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Dassault Systèmes B.V.
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IBM
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INRIA
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Prorail
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Rheinische Friedrich-Wilhelmus Universitaet Bonn
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Technische Universität Dortmund
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Tilburg University
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Tromsø, Norway
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Universita degli Studi di Firenze
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Universität Konstanz
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University of Birmingham