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)




PhD student, within the research project OPTIMAL

Centrum Wiskunde & Informatica (CWI) has a vacancy in the Networks & Optimization research group for a talented PhD student, within the research project OPTIMAL. OPTIMAL (Optimization for and with Machine Learning) is a Dutch ENW-groot project funded by NWO (2019-2025), offering 5 PhD and 6 PostDoc positions in the Netherlands. The institutes and researchers involved in OPTIMAL are University of Amsterdam, Amsterdam (Dick den Hertog), Tilburg University, Tilburg (Etienne de Klerk), Centrum Wiskunde & Informatica (CWI), Amsterdam (Monique Laurent, Guido Schäfer and Leen Stougie) and Delft University of Technology, Delft (Karen Aardal and Leo van Iersel).


Current events

Dutch Seminar on Optimization (online series) with Samuel Fiorini (Université libre de Bruxelles)

  • 2021-08-26T16:00:00+02:00
  • 2021-08-26T17:00:00+02:00
August 26 Thursday

Start: 2021-08-26 16:00:00+02:00 End: 2021-08-26 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. 

Speaker:  Samuel Fiorini (Université libre de Bruxelles) 

Tile: Integer programs with bounded subdeterminants and two nonzeros per row

We give a strongly polynomial-time algorithm for integer linear programs defined by integer coefficient matrices whose subdeterminants are bounded by a constant and that contain at most two nonzero entries in each row. The core of our approach is the first polynomial-time algorithm for the weighted stable set problem on graphs that do not contain more than k vertex-disjoint odd cycles, where k is any constant. Previously, polynomial-time algorithms were only known for k=0 (bipartite graphs) and for k=1. We observe that integer linear programs defined by coefficient matrices with bounded subdeterminants and two nonzeros per column can be also solved in strongly polynomial-time, using a reduction to b-matching. This is joint work with Gwenaël Joret (ULB), Stefan Weltge (TUM) and Yelena Yuditsky (ULB)

The lecture will be given online. Please visit the website for more information and the zoom link. 




Associated Members


Current projects with external funding

  • Continuous Methods in Discrete Optimization ()
  • Smart Heuristic Problem Optimization ()
  • Wiskundecluster DIAMANT ()
  • Mixed-Integer Non-Linear Optimisation Applications (MINOA)
  • Optimization for and with Machine Learning (OPTIMAL)
  • Polynomial Optimization, Efficiency through Moments and Algebra (POEMA)
  • Vóórkomen en voorkómen van incidenten op het spoor (PPS Prorail)
  • Towards a Quantitative Theory of Integer Programming (QIP)

Related partners

  • Alma Mater Studiorum-Universita di Bologna
  • Alpen-Adria-Universität Klagenfurt
  • CNR Pisa
  • CNRS
  • Dassault Systèmes B.V.
  • IBM
  • Prorail
  • Rheinische Friedrich-Wilhelmus Universitaet Bonn
  • Technische Universität Dortmund
  • Tilburg University
  • Tromsø, Norway
  • Universita degli Studi di Firenze
  • Universität Konstanz
  • University of Birmingham
  • Universiteit van Tilburg