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
Post-doc position in the area of Discrete and Continuous Optimization
Centrum Wiskunde & Informatica (CWI) has a vacancy in the Networks & Optimization research group for a talented postdoctoral researcher in the area of discrete and continuous optimization.
News
Large H2020 grant for optimisation research project ‘MINOA’
Recently, the EU granted the Mixed-Integer Non-Linear Optimisation Applications (MINOA) project, as part of the Horizon 2020 Research and Innovation Framework Programme. The project is a collaborative European Training Network, with 12 research partners, CWI being one of them.
Monique Laurent elected as Fellow of SIAM
CWI researcher Monique Laurent is elected as a Fellow of the international Society for Industrial and Applied Mathematics – SIAM. This prestigious Fellowship honours SIAM members who have made outstanding contributions to these fields. Laurent, who is a member of the management team of CWI and a professor at Tilburg University, receives the fellowship for her contributions to discrete and polynomial optimization and revealing interactions between them.
Rubicon grants for David de Laat and Alessandro Zocca
CWI researchers David de Laat and Alessandro Zocca both received an NWO Rubicon grant. De Laat will study new techniques to compute optimal packings at MIT for one year, and Zocca will study renewables and uncertainty in future power systems at Caltech for two years. NWO granted these subsidies to 22 young, highly promising research talents to gain international research experience at foreign top institutes.
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
Current events
Dutch Seminar on Optimization (online series) with Lucas Slot (CWI) and Juan José Maulén (Groningen)
- 2021-10-28T16:00:00+02:00
- 2021-10-28T17:00:00+02:00
Dutch Seminar on Optimization (online series) with Lucas Slot (CWI) and Juan José Maulén (Groningen)
Start: 2021-10-28 16:00:00+02:00 End: 2021-10-28 17:00:00+02:00
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.
Speakers: Lucas Slot (CWI) and Juan José Maulén (RU Groningen)
Title of the talk of Lucas Slot: Degree bounds for positivity certificates and the polynomial kernel method
Abstract of the talk of Lucas Slot:
The classical Positvestellensaetze of Putinar and Schmuedgen state that the positivity of a polynomial f over a (compact) semialgebraic set S can be verified by expanding f as a conic combination of the polynomials that define S, using sums of squares of polynomials as coefficients. Recently, there has been an interest in proving bounds on the largest degree of the sum-of-squares coefficients involved in this expansion. Such bounds have direct implications for the convergence rate of Lasserre-type hierarchies for polynomial optimization. We present the polynomial kernel method for proving degree bounds on special sets S, which was first used in the case of the hypersphere by Fang and Fawzi.
We apply the PKM to additional sets, including the binary hypercube {-1, 1}^n, the unit box [-1, 1]^n and the unit ball.
This is based on joint work with Monique Laurent.
Arxiv link: https://arxiv.org/abs/2011.04027
Title of the talk of Juan José Maulén: Acceleration of fixed point algorithms via inertia
Abstract of the talk of Juan José Maulén:
In this talk, we will use the results about the convergence of inertial optimization algorithms, defined as fixed point iterations from a family of cocoercive operators. This result implies that exists inertial versions of the Primal-dual splitting algorithm proposed by Briceño and Roldan on 2019, and for the three-operator splitting scheme proposed by Davis and Yin on 2015. Both algorithms fit on the framework of optimization algorithms defined by cocoercive operators. The inertial versions obtained are tested in several numerical experiments, where better performance with respect to the original algorithms can be observed.
The lecture will be given online. Please visit the website for more information and the zoom link.
- Web
- Email: Daniel Dadush and Sven Polak
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iCal
Members
Associated Members
Publications
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Bansal, N, Naor, J, & Talmon, O. (2021). Efficient online weighted multi-level paging. In Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (pp. 94–104). doi:10.1145/3409964.3461801
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Borst, S.J, Dadush, D.N, Huiberts, S, & Tiwari, S.S.K. (2021). On the integrality gap of binary integer programs with Gaussian data. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 427–442). doi:10.1007/978-3-030-73879-2_30
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Slot, L.F.H, & Laurent, M. (2021). Sum-of-squares hierarchies for binary polynomial optimization. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 43–57). doi:10.1007/978-3-030-73879-2_4
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Kuiper, A, Mandjes, M.R.H, de Mast, J, & Brokkelkamp, K.R. (2021). A flexible and optimal approach for appointment scheduling in healthcare. Decision Sciences. doi:10.1111/deci.12517
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Bansal, N, Jiang, H, Meka, R, Singla, S, & Sinha, M. (2021). Online discrepancy minimization for stochastic arrivals. In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 2842–2861). doi:10.1137/1.9781611976465.169
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Dadush, D.N, & Huiberts, S. (2020). A friendly smoothed analysis of the simplex method. SIAM Journal on Computing, 49(5). doi:10.1137/18M1197205
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Dadush, D.N, & Huiberts, S. (2020). Smoothed analysis of the simplex method. In T Roughgarden (Ed.), Beyond the Worst-Case Analysis of Algorithms. Cambridge University Press.
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Dadush, D.N, Huiberts, S, Natura, B, & Végh, L.A. (2020). A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix. In Proceedings of the Annual ACM Symposium on Theory of Computing (pp. 761–774). doi:10.1145/3357713.3384326
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Bienkowski, M, Byrka, J, Coester, C.E, & Jeż, L. (2020). Unbounded lower bound for k-server against weak adversaries. In Proceedings of the Annual ACM SIGACT Symposium on Theory of Computing (pp. 1165–1169). doi:10.1145/3357713.3384306
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van Apeldoorn, J.T.S, Gilyén, A.P, Gribling, S.J, & de Wolf, R.M. (2020). Quantum SDP-Solvers: Better upper and lower bounds. Quantum, 4. doi:10.22331/q-2020-02-14-230
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