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
CWI co-organizes international trimester program at Bonn University
Together with TU/e, UU and LSE London, CWI is co-organizing an international trimester program on Discrete Optimization at the Hausdorff Research Institute for Mathematics (HIM) in Bonn. Goal of this research community service is to collaborate and make progress on long-standing open problems.
Monique Laurent elected as EUROPT Fellow 2021
Monique Laurent, researcher and management team member at CWI and a professor at Tilburg University, was recently elected as EUROPT Fellow 2021. She was honoured for being an outstanding researcher in continuous optimization.
Strong Contribution of Networks and Optimization at IPCO 2021
Research carried out by CWI's Networks and Optimization (N&O) group has resulted in several contributions to the 22nd Conference on Integer Programming and Combinatorial Optimization, IPCO 2021: three presentations of research papers and the award in the Student Poster Competition.
NETWORKS consortium awarded €1M from EU COFUND for postdoc programme
After receiving the COFUND grant from the Horizon 2020 programme for 14 PhD positions, NETWORKS has been granted a COFUND grant of €1.0 million to appoint 14 postdoctoral researchers for 2 years.
Current events
Dutch Seminar on Optimization: talk by Martin Skutella (TU Berlin)
- 2021-09-30T16:00:00+02:00
- 2021-09-30T17:00:00+02:00
Dutch Seminar on Optimization: talk by Martin Skutella (TU Berlin)
Start: 2021-09-30 16:00:00+02:00 End: 2021-09-30 17:00:00+02:00
Everyone is welcome to attend the online seminar by Martin Skutella (TU Berlin). The title of his lecture is: A Faster Algorithm for Quickest Transshipments via an Extended Discrete Newton Method.
Abstract:
The Quickest Transshipment Problem is to route flow as quickly as possible from sources with supplies to sinks with demands in a network with capacities and transit times on the arcs. It is of fundamental importance for numerous applications in areas such as logistics, production, traffic, evacuation, and finance. More than 25 years ago, Hoppe and Tardos presented the first (strongly) polynomial-time algorithm for this problem. Their approach, as well as subsequently derived algorithms with strongly polynomial running time, are hardly practical as they rely on parametric submodular function minimization via Megiddo's
method of parametric search. The main contribution of this paper is a considerably faster algorithm for the Quickest Transshipment Problem that instead employs a subtle extension of the Discrete Newton Method.
This improves the previously best known running time of $\tilde{O}(m^4k^{14})$ to $\tilde O(m^2k^5+m^3k^3+m^3n)$, where $n$ is the number of nodes, $m$ the number of arcs, and $k$ the number of sources and sinks.
This is joint work with Miriam Schlöter (ETH Zurich) and Khai Van Tran (TU Berlin).
- Web
- Email: Daniel Dadush
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iCal
Members
Associated Members
Publications
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Brosch, D, Laurent, M, & Steenkamp, J.A.J. (2021). Optimizing hypergraph-based polynomials modeling job-occupancy in queuing with redundancy scheduling. SIAM Journal on Optimization, 31(3), 2227–2254. doi:10.1137/20M1369592
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Bansal, N, & Sinha, M. (2021). k-Forrelation optimally separates quantum and classical query complexity. In Proceedings of the Annual ACM SIGACT Symposium on Theory of Computing (pp. 1303–1316). doi:10.1145/3406325.3451040
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Saha, A, Brokkelkamp, K.R, Velaj, Y, Khan, A, & Bonchi, F. (2021). Shortest paths and centrality in uncertain networks. In Proceedings of the VLDB Endowment (pp. 1188–1201). doi:10.14778/3450980.3450988
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Bansal, N, Batra, J, Farhadi, M, & Tetali, P. (2021). Improved approximations for min sum vertex cover and generalized min sum set cover. In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 986–1005). doi:10.1137/1.9781611976465.62
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Bansal, N, & Batra, J. (2021). Non-uniform geometric set cover and scheduling on multiple machines. In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 3011–3021).
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Brokkelkamp, K.R, van Venetië, R., de Vries, M.J, & Westerdiep, J. (2020). PACE Solver Description: tdULL. In 15th International Symposium on Parameterized and Exact Computation. doi:10.4230/LIPIcs.IPEC.2020.29
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Bansal, N, & Spencer, J.H. (2020). On-line balancing of random inputs. Random Structures & Algorithms, 57(4), 879–891. doi:10.1002/rsa.20955
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Slot, L.F.H, & Laurent, M. (2020). Near-optimal analysis of Lasserre’s univariate measure-based bounds for multivariate polynomial optimization. Mathematical Programming. doi:10.1007/s10107-020-01586-y
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Dadush, D.N, & Tiwari, S.S.K. (2020). On the complexity of branching proofs. In Leibniz International Proceedings in Informatics, LIPIcs. doi:10.4230/LIPIcs.CCC.2020.34
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Bansal, N, & Meka, R. (2020). On the discrepancy of random low degree set systems. Random Structures & Algorithms, 57(3). doi:10.1002/rsa.20935
Current projects with external funding
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Smart Heuristic Problem Optimization ()
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Wiskundecluster DIAMANT ()
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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