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
No vacancies currently.
News
Quantum entanglement can make communications more efficient
Entanglement – a quantum mechanical correlation between particles that can exist even over long distances – might be used for future ways of communication.
Veni grants for Daniel Dadush and Hannes Mühleisen
The Netherlands Organisation for Scientific Research (NWO) has awarded Veni grants to Daniel Dadush and Hannes Mühleisen of CWI. The funding allows these researchers, who have recently obtained their PhD, to conduct independent research and develop their ideas for a period of three years.
Daniel Dadush receives A.W. Tucker Prize 2015
Daniel Dadush of CWI's Networks & Optimization group has been awarded the A. W. Tucker Prize 2015. He received the prize for his doctoral thesis that he completed at Georgia Tech in 2012.
Lex Schrijver receives EURO Gold Medal 2015
Researcher Lex Schrijver of CWI has been awarded the EURO Gold Medal 2015. This prize is considered the highest European distinction in Operational Research (OR) and is awarded by the Association of European Operational Research Societies (EURO).
Members
Associated Members
Publications
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Brokkelkamp, K.R, van Venetië, R., de Vries, M.J, & Westerdiep, J. (2020). PACE Solver Description: tdULL. In 15th International Symposium on Parameterized and Exact Computation. doi:10.4230/LIPIcs.IPEC.2020.29
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Bansal, N, & Spencer, J.H. (2020). On-line balancing of random inputs. Random Structures & Algorithms, 57(4), 879–891. doi:10.1002/rsa.20955
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Slot, L.F.H, & Laurent, M. (2020). Near-optimal analysis of Lasserre’s univariate measure-based bounds for multivariate polynomial optimization. Mathematical Programming. doi:10.1007/s10107-020-01586-y
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Dadush, D.N, & Tiwari, S.S.K. (2020). On the complexity of branching proofs. In Leibniz International Proceedings in Informatics, LIPIcs. doi:10.4230/LIPIcs.CCC.2020.34
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Bansal, N, & Meka, R. (2020). On the discrepancy of random low degree set systems. Random Structures & Algorithms, 57(3). doi:10.1002/rsa.20935
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Bansal, N, Jiang, H, Singla, S, & Sinha, M. (2020). Online vector balancing and geometric discrepancy. In Proceedings of the Annual ACM Symposium on Theory of Computing (pp. 1139–1152). doi:10.1145/3357713.3384280
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Dadush, D.N, Végh, L.A, & Zambelli, G. (2020). Rescaling algorithms for linear conic feasibility. Mathematics of Operations Research, 45(2), 732–754. doi:10.1287/moor.2019.1011
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Huizing, D, Schäfer, G, van der Mei, R.D, & Bhulai, S. (2020). The median routing problem for simultaneous planning of emergency response and non-emergency jobs. European Journal of Operational Research. doi:10.1016/j.ejor.2020.02.002
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de Klerk, E, & Laurent, M. (2020). Convergence analysis of a Lasserre hierarchy of upper bounds for polynomial minimization on the sphere. Mathematical Programming, 2020. doi:10.1007/s10107-019-01465-1
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Abiad, A, Gribling, S.J, Lahaye, D.J.P, Mnich, M, Regts, G, Vena, L, … Zwaneveld, P.J. (2020). On the complexity of solving a decision problem with flow-depending costs: The case of the IJsselmeer dikes. Discrete Optimization. doi:10.1016/j.disopt.2019.100565
Current projects with external funding
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Continuous Methods in Discrete Optimization ()
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Wiskundecluster DIAMANT ()
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Smart Heuristic Problem Optimization
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Mixed-Integer Non-Linear Optimisation Applications (MINOA)
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Optimization for and with Machine Learning (OPTIMAL)
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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
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Universiteit van Tilburg