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)




No vacancies currently.


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
September 30 Thursday

Start: 2021-09-30 16:00:00+02:00 End: 2021-09-30 17:00:00+02:00

On-line seminar

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.

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).


Associated Members


Current projects with external funding

  • 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