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
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).
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.
Current events
Dutch Seminar on Optimization (online series)
- 2021-01-28T16:00:00+01:00
- 2021-01-28T17:00:00+01:00
Dutch Seminar on Optimization (online series)
Start: 2021-01-28 16:00:00+01:00 End: 2021-01-28 17:00:00+01:00
The Dutch Seminar on Optimization is an initiative to bring together researchers from the Netherlands and beyond. The objective is to establish a new forum for the Dutch optimization community to come together, to help provide a spotlight for up and coming local talent, and to bring in high quality international speakers.
Next talk by David de Laat (TU Delft)
For more information please visit the website.
- Web
- Email: Daniel Dadush
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iCal
NMC 2021 (Dutch Mathematical Congress)
- 2021-01-28T16:00:00+01:00
- 2021-01-28T17:00:00+01:00
NMC 2021 (Dutch Mathematical Congress)
Start: 2021-01-28 16:00:00+01:00 End: 2021-01-28 17:00:00+01:00
The organizing committee of NMC has composed a programme containing various online activities at different times during the year: we proudly present the NMC 2021 Series!
Opening date 28 January 2021 with the Stieltjes Prize award ceremony.
For more information and registration please visit the website.
Members
Associated Members
Publications
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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
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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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de Klerk, E, & Laurent, M. (2020). Worst-case Examples for Lasserre’s Measure–Based Hierarchy for Polynomial Optimization on the Hypercube. Mathematics of Operations Research, 45(1). doi:10.1287/moor.2018.0983
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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
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