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
Vici grants for Nikhil Bansal and Roeland Merks
CWI researchers Nikhil Bansal and Roeland Merks have been awarded Vici grants from NWO. With the 1.5 million euro grant, Bansal and Merks can develop their own research lines in the next five years.
CWI and ProRail predict railway incidents
Centrum Wiskunde & Informatica and ProRail recently started a research collaboration in the area of the handling of incidents at the Dutch railways. It concerns a public private partnership between CWI and ProRail striking up a four year period. The research is aimed at prevention and handling of a broad spectrum of railway incidents, like disturbance of the railway infrastructure, people walking on the tracks and collisions.
Large H2020 grant for optimisation research project ‘MINOA’
Recently, the EU granted the Mixed-Integer Non-Linear Optimisation Applications (MINOA) project, as part of the Horizon 2020 Research and Innovation Framework Programme. The project is a collaborative European Training Network, with 12 research partners, CWI being one of them.
Monique Laurent elected as Fellow of SIAM
CWI researcher Monique Laurent is elected as a Fellow of the international Society for Industrial and Applied Mathematics – SIAM. This prestigious Fellowship honours SIAM members who have made outstanding contributions to these fields. Laurent, who is a member of the management team of CWI and a professor at Tilburg University, receives the fellowship for her contributions to discrete and polynomial optimization and revealing interactions between them.
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