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, 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
PhD students / Early Stage Researchers on the subject of Polynomial Optimization, Efficiency through Moments and Algebra.
Centrum Wiskunde & Informatica (CWI) has vacancies in the Networks and Optimization research group for two talented PhD students / Early Stage Researchers on the subject of Polynomial Optimization, Efficiency through Moments and Algebra. The vacancies are within the research consortium POEMA (Polynomial Optimization, Efficiency through Moments and Algebra).
News
CWImathematician proves: altruism does not necessarily lead to better outcomes in game theory
New mathematical research shows that consideration for others does not always lead to the best outcome  that is, when it’s applied in game theory.
CWI researchers in research consortium Gravity programme
Six research consortia in which prominent scientists from various Dutch universities work together are receiving a combined sum of 153 million euros for longterm and largescale research.
Conditions for optimal solutions to semidefinite problems found
Most optimization problems in reallife are hard to solve optimally. However, for practical purposes it is usually sufficient to settle for nearoptimal solutions that can be found quickly. Fast and more accurate approximations can be computed using semidefinite programming, a novel powerful optimization tool
Members
Associated Members
Publications

Chen, J.J, Bansal, N, Chakraborty, S, & von der Brüggen, G. (2018). Packing sporadic realtime tasks on identical multiprocessor systems. In 29th International Symposium on Algorithms and Computation (pp. 71:1–71:14). doi:10.4230/LIPIcs.ISAAC.2018.71

Dadush, D.N, Nikolov, A, Talwar, K, & TomczakJaegermann, N. (2018). Balancing vectors in any norm. In Proceedings  Annual IEEE Symposium on Foundations of Computer Science, FOCS (pp. 1–10). doi:10.1109/FOCS.2018.00010

Carvalho Rodrigues, F, Schäfer, G, & Xavier, E.C. (2018). On the effectiveness of connection tolls in fair cost facility location games. In Proceedings of the 19th Italian Conference on Theoretical Computer Science (pp. 36–47).

van Heuven van Staereling, I.I. (2018). Tree decomposition methods for the periodic event scheduling problem. In OpenAccess Series in Informatics. doi:10.4230/OASIcs.ATMOS.2018.6

Carstens, C.J, & Kleer, P.S. (2018). Speeding up switch Markov chains for sampling bipartite graphs with given degree sequence. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2018) (pp. 36:1–36:18). doi:10.4230/LIPIcs.APPROXRANDOM.2018.36

Amanatidis, G, Birmpas, G, & Markakis, V. (2018). Comparing approximate relaxations of envyfreeness. In IJCAI International Joint Conference on Artificial Intelligence (pp. 42–48).

Bansal, N, Dadush, D.N, Garg, S, & Lovett, S. (2018). The GramSchmidt Walk: A Cure for the Banaszczyk Blues. In Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2018 (pp. 587–597). doi:10.1145/3188745.3188850

Dadush, D.N, & Huiberts, S. (2018). A friendly smoothed analysis of the simplex method. In Proceedings of the Annual ACM Symposium on Theory of Computing (pp. 214–227). doi:10.1145/3188745.3188826

Kamphorst, B. (2018, May 31). Heavytraffic behaviour of scheduling policies in queues.

Amanatidis, G, Green, B, & Mihail, M. (2018). Connected realizations of jointdegree matrices. Discrete Applied Mathematics. doi:10.1016/j.dam.2018.04.010
Current projects with external funding

Continuous Methods in Discrete Optimization ()

Smart Heuristic Problem Optimization

Wiskundecluster DIAMANT

Approximation Algorithms, Quantum Information and Semidefinite Optimization (AQSO)

MixedInteger NonLinear Optimisation Applications (MINOA)

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 StudiorumUniversita di Bologna

AlpenAdriaUniversität Klagenfurt

CNR Pisa

CNRS

Dassault Systèmes B.V.

IBM

INRIA

Prorail

Rheinische FriedrichWilhelmus Universitaet Bonn

Technische Universität Dortmund

Tilburg University

Tromsø, Norway

Universita degli Studi di Firenze

Universität Konstanz

University of Birmingham