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
2-year Postdoc, within the research project OPTIMAL
Centrum Wiskunde & Informatica (CWI) has a vacancy in the Networks and Optimization research group for a talented 2-year Postdoc, within the research project OPTIMAL. OPTIMAL (Optimization for and with Machine Learning) is a Dutch ENW-groot project funded by NWO (2019-2025), offering 5 PhD and 6 PostDoc positions in the Netherlands, starting from September 2020 or later.
Postdoc on the subject of Towards a Quantitative Theory of Integer Programming.
Centrum Wiskunde & Informatica (CWI) has a vacancy in the Networks & Optimization research group for a talented Postdoc, on the subject of Towards a Quantitative Theory of Integer Programming.
News
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).
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.
Members
Associated Members
Publications
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Dadush, D.N, & Huiberts, S. (2020). Smoothed analysis of the simplex method. In T Roughgarden (Ed.), Beyond the Worst-Case Analysis of Algorithms. Cambridge University Press.
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van Apeldoorn, J.T.S. (2020, February 6). A quantum view on convex optimization. ILLC Dissertation Series.
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Slot, L.F.H, & Laurent, M. (2020). Improved convergence analysis of Lasserre’s measure-based upper bounds for polynomial minimization on compact sets. Mathematical Programming, 2020. doi:10.1007/s10107-020-01468-3
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van Apeldoorn, J.T.S, Gilyén, A.P, Gribling, S.J, & de Wolf, R.M. (2020). Convex optimization using quantum oracles. Quantum, 4. doi:10.22331/q-2020-01-13-220
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Bansal, N, & Meka, R. (2020). On the discrepancy of random low degree set systems. In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms. doi:10.1137/1.9781611975482.157
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Abbasi-Zadeh, S, Bansal, N, Guruganesh, G, Nikolov, A, Schwartz, R, & Singh, M. (2020). Sticky Brownian rounding and its applications to constraint satisfaction problems. In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 854–873).
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Dadush, D.N, Garg, S, Lovett, S, & Nikolov, A. (2019). Towards a constructive version of Banaszczyk’s vector balancing theorem. Theory of Computing, 15(Special Issue). doi:10.4086/toc.2019.v015a015
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Kleer, P.S, & Schäfer, G. (2019). Topological Price of Anarchy bounds for clustering games on networks. In Proceedings of the International Conference on Web and Internet Economics (pp. 241–255). doi:10.1007/978-3-030-35389-6_18
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Sinha, M, & de Wolf, R.M. (2019). Exponential separation between quantum communication and logarithm of approximate rank. In Proceedings of FOCS (pp. 966–981). doi:10.1109/FOCS.2019.00062
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de Klerk, E, & Laurent, M. (2019). Worst-case Examples for Lasserre’s Measure–Based Hierarchy for Polynomial Optimization on the Hypercube. Mathematics of Operations Research, 2019(November 5), 1–13. doi:10.1287/moor.2018.0983
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