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
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
Better ranking for big data using seriation solution
The recent availability of large data sets leads to the challenge of identifying patterns and structures in them. These patterns can be deployed to improve the user experience
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.
Current events
Postponed: SDP Days - a workshop on Applications of Semidefinite Optimization
- 2020-05-06T00:00:00+02:00
- 2020-05-07T23:59:59+02:00
Postponed: SDP Days - a workshop on Applications of Semidefinite Optimization
Start: 2020-05-06 00:00:00+02:00 End: 2020-05-07 23:59:59+02:00
Iedereen is welkom bij de SDP-dagen bij te wonen; een workshop over applicaties van semidefiniete optimalisatie. Alle informatie (sprekers en abstracts) is te vinden op de website. Deelname is gratis, maar schrijf je voor 25 april in door een mail te sturen naar Susanne van Dam (susanne@cwi.nl) zodat we de catering kunnen organiseren.
- Web
- Email: Susanne van Dam
- Phone: +31-20 592 4189
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iCal
Members
Associated Members
Publications
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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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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
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Amanatidis, G, Kleer, P.S, & Schäfer, G. (2019). Budget-feasible mechanism design for non-monotone submodular objectives: Offline and online. In ACM EC 2019 - Proceedings of the 2019 ACM Conference on Economics and Computation (pp. 901–919). doi:10.1145/3328526.3329622
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Bansal, N, Eliéš, M, Jeż, Ł, & Koumoutsos, G. (2019). The (h,k)-Server Problem on Bounded Depth Trees. ACM Transactions on Algorithms, 15(2). doi:10.1145/3301314
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