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 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 PhD student, on the subject of Towards a Quantitative Theory of Integer Programming.
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
QuSoft/CWI team earns 4th place in Benelux Algorithm Programming Contest 2019
On Saturday 19 October 2019, Arjan Cornelissen, Farrokh Labib and Ruben Brokkelkamp formed a combined QuSoft/CWI team in the BAPC 2019 programming contest. They earned the 4th place, competing against companies such as ASML, Booking.com, Ortec and Sioux.
CWI research connects quantum computing and optimization
Sander Gribling studied if and how quantum computers can help solve optimization problems, like finding the shortest route. He developed new quantum algorithms that can help to solve them more efficiently. He defends his PhD thesis on 30 September.
Cum laude for CWI research quantifying effect of safety margins in route planning
When drivers avoid certain highways to escape the risk of usual traffic jams, they can significantly increase the average travel time for everyone in the road network. CWI researcher Pieter Kleer developed models to analyze this.
Jie Li and Sophie Huiberts selected to participate in the 7th Heidelberg Laureate Forum
Jie Li from the DIS group and Sophie Huiberts from the N&O group have been selected to participate in the 7th Heidelberg Laureate Forum (HLF). The annual HLF event selects a small group of 200 most qualified Young Researchers worldwide to meet pre-eminent scientists from the fields of mathematics and computer science.
Members
Associated Members
Publications
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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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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
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Carvalho Rodrigues, F, Schäfer, G, & Xavier, E.C. (2018). On the effectiveness of connection tolls in fair cost facility location games. In Proceedings of the 19th Italian Conference on Theoretical Computer Science (pp. 36–47).
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van Heuven van Staereling, I.I. (2018). Tree decomposition methods for the periodic event scheduling problem. In OpenAccess Series in Informatics. doi:10.4230/OASIcs.ATMOS.2018.6
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Carstens, C.J, & Kleer, P.S. (2018). Speeding up switch Markov chains for sampling bipartite graphs with given degree sequence. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2018) (pp. 36:1–36:18). doi:10.4230/LIPIcs.APPROX-RANDOM.2018.36
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Amanatidis, G, Birmpas, G, & Markakis, V. (2018). Comparing approximate relaxations of envy-freeness. In IJCAI International Joint Conference on Artificial Intelligence (pp. 42–48).
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Bansal, N, Dadush, D.N, Garg, S, & Lovett, S. (2018). The Gram-Schmidt Walk: A Cure for the Banaszczyk Blues. In Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2018 (pp. 587–597). doi:10.1145/3188745.3188850
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Dadush, D.N, & Huiberts, S. (2018). A friendly smoothed analysis of the simplex method. In Proceedings of the Annual ACM Symposium on Theory of Computing (pp. 214–227). doi:10.1145/3188745.3188826
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Kamphorst, B. (2018, May 31). Heavy-traffic behaviour of scheduling policies in queues.
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