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
2018 Women@McKinsey Dissertation Award for Yllka Velaj
CWI researcher and ERCIM Fellow Yllka Velaj has won the 2018 Women@McKinsey Dissertation Award for her PhD thesis, which analyzes the problem of how to maximize the dissemination of information and opinions in social networks. The award comes with a job offer by McKinsey & Company, and a sponsorship to attend the Open Data Science Conference 2018.
Monique Laurent opened World Women in Mathematics event in Rio
Monique Laurent from CWI opened the World Women in Mathematics event (WM)² in Rio de Janeiro with a keynote lecture.
ERC Starting grant for CWI researcher Daniel Dadush
In July, Daniel Dadush (CWI) was awarded an ERC Starting Grant of 1.5 million euro for his proposal ‘Towards a Quantitative Theory of Integer Programming’. He aims to revolutionize the understanding of integer programming (IP), the most popular method for finding optimal solutions to optimization problems.
CWI trainee Carla Groenland runner-up in UvA Master Thesis Award 2018
Carla Groenland, UvA alumnus and a trainee at CWI’s Networks & Optimization research group, was chosen as the runner-up in the finale for the UvA Master Thesis Award 2018. In total there were 92 competitors. You can listen to her podcast.
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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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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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 2019 - 60th Annual IEEE Symposium on Foundations of Computer Science.
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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
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Chen, J.-J, Bansal, N, Chakraborty, S, & von der Brüggen, G. (2018). Packing sporadic real-time tasks on identical multiprocessor systems. In 29th International Symposium on Algorithms and Computation (pp. 71:1–71:14). doi:10.4230/LIPIcs.ISAAC.2018.71
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Dadush, D.N, Nikolov, A, Talwar, K, & Tomczak-Jaegermann, N. (2018). Balancing vectors in any norm. In Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS (pp. 1–10). doi:10.1109/FOCS.2018.00010
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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Approximation Algorithms, Quantum Information and Semidefinite Optimization (AQSO)
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Mixed-Integer Non-Linear Optimisation Applications (MINOA)
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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