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
Cooperative behaviour is not instinctive, but learnt
Cooperative behaviour is not an instinctive impulse or deliberate choice, but a learning process. Researchers of CWI and LUISS Guido Carli in Rome showed in an experiment that people living in a low-trust society intuitively choose non-cooperation in games. However, after playing several times their intuitive choices become more cooperative.
Network analysis reveals new information on tax treaties
Mathematical analysis of a data set collected by Centraal Planbureau (CPB), the Netherlands Bureau for Economic Policy Analysis, revealed new information on how bilateral tax treaties can be exploited to form ‘tax routes’ that minimize profit taxes.
Invited lecture Monique Laurent at ICM 2014
Monique Laurent will give an invited lecture at the International Congress of Mathematicians (ICM) 2014 on Wednesday 20 August in Seoul, Korea. It is a great honour to speak at ICM, the most important conference for mathematicians in the world, with thousands of participants and the award of the Fields Medals.
Bert Gerards on Solving Rota’s Conjecture in AMS Notices
Bert Gerards (CWI), Jim Geelen (University of Waterloo, Canada) and Geoff Whittle (Victoria University of Wellington, New Zealand) have published an article on Solving Rota’s Conjecture in the August issue of AMS Notices. The authors recently announced that they solved Rota's Conjecture after 15 years of work.
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