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 student, within the research project OPTIMAL
Centrum Wiskunde & Informatica (CWI) has a vacancy in the Networks & Optimization research group for a talented PhD student, 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. The institutes and researchers involved in OPTIMAL are University of Amsterdam, Amsterdam (Dick den Hertog), Tilburg University, Tilburg (Etienne de Klerk), Centrum Wiskunde & Informatica (CWI), Amsterdam (Monique Laurent, Guido Schäfer and Leen Stougie) and Delft University of Technology, Delft (Karen Aardal and Leo van Iersel).
News
Pieter Kleer wins Gijs de Leve Prize
Pieter Kleer, former PhD student of CWI, was awarded the Gijs de Leve Prize 2018-2020 for the best PhD thesis in in the area of Mathematics of Operations Research defended in the last three years.
Daniel Dadush and Samarth Tiwari receive Best Paper Award at CCC'20
Daniel Dadush and Samarth Tiwari from CWI's Networks and Optimization research group receive the Best Paper Award at the Computational Complexity Conference 2020 for their work 'On the Complexity of Branching Proofs'.
Daniel Dadush receives prestigious Van Dantzig Prize
Daniel Dadush has been awarded the Van Dantzig Prize, which is considered the highest Dutch award in statistics and operations research. It is awarded by the VVSOR once every five years.
CWI researchers involved in two NWO-Groot grants
In the NWO Open Competition ENW-GROOT programme, four CWI researchers received in total two grants to study machine learning and neural networks: Nikhil Bansal, Monique Laurent, Benjamin Sanderse and Leen Stougie.
Members
Associated Members
Publications
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Bansal, N, Naor, J, & Talmon, O. (2021). Efficient online weighted multi-level paging. In Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (pp. 94–104). doi:10.1145/3409964.3461801
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Borst, S.J, Dadush, D.N, Huiberts, S, & Tiwari, S.S.K. (2021). On the integrality gap of binary integer programs with Gaussian data. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 427–442). doi:10.1007/978-3-030-73879-2_30
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Slot, L.F.H, & Laurent, M. (2021). Sum-of-squares hierarchies for binary polynomial optimization. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 43–57). doi:10.1007/978-3-030-73879-2_4
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Kuiper, A, Mandjes, M.R.H, de Mast, J, & Brokkelkamp, K.R. (2021). A flexible and optimal approach for appointment scheduling in healthcare. Decision Sciences. doi:10.1111/deci.12517
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Bansal, N, Jiang, H, Meka, R, Singla, S, & Sinha, M. (2021). Online discrepancy minimization for stochastic arrivals. In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 2842–2861). doi:10.1137/1.9781611976465.169
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Dadush, D.N, & Huiberts, S. (2020). A friendly smoothed analysis of the simplex method. SIAM Journal on Computing, 49(5). doi:10.1137/18M1197205
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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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Dadush, D.N, Huiberts, S, Natura, B, & Végh, L.A. (2020). A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. In Proceedings of the Annual ACM Symposium on Theory of Computing (pp. 761–774). doi:10.1145/3357713.3384326
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Bienkowski, M, Byrka, J, Coester, C.E, & Jeż, L. (2020). Unbounded lower bound for k-server against weak adversaries. In Proceedings of the Annual ACM SIGACT Symposium on Theory of Computing (pp. 1165–1169). doi:10.1145/3357713.3384306
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van Apeldoorn, J.T.S, Gilyén, A.P, Gribling, S.J, & de Wolf, R.M. (2020). Quantum SDP-Solvers: Better upper and lower bounds. Quantum, 4. doi:10.22331/q-2020-02-14-230
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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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