Description
Leader of the group Networks and Optimization: Daniel Dadush.
In today’s society, complex systems surround us. From transport and traffic, to behavioral economics and operations management, realworld 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 problemspecific 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 realworld problems. We are always interested in new algorithmic challenges arising in realworld 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
Current events
Dutch Seminar on Optimization (online series) with Andreas Wiese (VU Amsterdam)
 20220127T16:00:00+01:00
 20220127T17:00:00+01:00
Dutch Seminar on Optimization (online series) with Andreas Wiese (VU Amsterdam)
Start: 20220127 16:00:00+01:00 End: 20220127 17:00:00+01:00
The Dutch Seminar on Optimization is an initiative to bring together researchers from the Netherlands and beyond, with topics that are centered around Optimization in a broad sense. We would like to invite all researchers, especially also PhD students, who are working on related topics to join the events.
Speaker: Andreas Wiese (VU Amsterdam)
Title:
A PTAS for the Unsplittable Flow on a Path problem
(joint work with Fabrizio Grandoni and Tobias Mömke)
Abstract:
The lecture will be given online. Please visit the website for more information and the zoom link.
Members
Associated Members
Publications

Slot, L.F.H, & Laurent, M. (2022). Sumofsquares hierarchies for binary polynomial optimization. Mathematical Programming. doi:10.1007/s10107021017459

Antoniadis, A, Coester, C.E, Eliáš, M, Polak, A, & Simon, B. (2021). Learningaugmented dynamic power management with multiple states via new ski rental bounds. In Proceedings NeurIPS (Annual Conference on Neural Information Processing Systems).

Huizing, D, & Schäfer, G. (2021). The Traveling kMedian Problem: Approximating optimal network coverage. In Proceedings of the 19th International Workshop on Approximation and Online Algorithms (pp. 80–98). doi:10.1007/9783030927028_6

Bansal, N, & Cohen, I.R. (2021). Contention resolution, matrix scaling and fair allocation. In Proceedings of the 19th International Workshop on Approximation and Online Algorithms (pp. 252–274). doi:10.1007/9783030927028_16

Brosch, D, Laurent, M, & Steenkamp, J.A.J. (2021). Optimizing hypergraphbased polynomials modeling joboccupancy in queuing with redundancy scheduling. SIAM Journal on Optimization, 31(3), 2227–2254. doi:10.1137/20M1369592

Dadush, D.N, Végh, L.A, & Zambelli, G. (2021). Geometric rescaling algorithms for submodular function minimization. Mathematics of Operations Research, 46(3), 1081–1108. doi:10.1287/MOOR.2020.1064

Coester, C.E, Koutsoupias, E, & Lazos, P. (2021). The infinite server problem. ACM Transactions on Algorithms, 17(3), 1–23. doi:10.1145/3456632

Bansal, N, & Sinha, M. (2021). kForrelation 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

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

Borst, S.J, Dadush, D.N, Olver, N.K, & Sinha, M. (2021). Majorizing measures for the optimizer. In Leibniz International Proceedings in Informatics, LIPIcs. doi:10.4230/LIPIcs.ITCS.2021.73
Current projects with external funding

Smart Heuristic Problem Optimization ()

MixedInteger NonLinear Optimisation Applications (MINOA)

New frontiers in numerical nonlinear algebra (None)

Optimization for and with Machine Learning (OPTIMAL)

Polynomial Optimization, Efficiency through Moments and Algebra (POEMA)

Towards a Quantitative Theory of Integer Programming (QIP)
Related partners

Alma Mater StudiorumUniversita di Bologna

AlpenAdriaUniversität Klagenfurt

CNR Pisa

CNRS

Dassault Systèmes B.V.

IBM

INRIA

Rheinische FriedrichWilhelmus Universitaet Bonn

Technische Universität Dortmund

Tilburg University

Tromsø, Norway

Universita degli Studi di Firenze

Universität Konstanz

University of Birmingham

Universiteit van Tilburg