Discrete Mathematics, Optimization, and Convexity

We are researchers at TUM interested in mathematical optimization problems that typically involve a large number of discrete decisions to be made. Such problems occur in a variety of real-world problems arising in logistics, scheduling, (social) networks, routing, chip design, data analysis, or tomography.

Besides practical applications, we are highly interested in theoretical foundations of discrete optimization. Keywords that describe our focus are:

  • algorithmic game theory
  • approximation algorithms
  • complexity theory
  • combinatorial optimization
  • convex geometry
  • extended formulations
  • graph algorithms
  • geometric representations
  • linear and integer programming
  • network design
  • polyhedral combinatorics
  • scheduling

We also offer various courses on such topics, particularly designed for students in Mathematics or Computer Science.

The groups are led by Peter GritzmannAndreas S. Schulz, and Stefan Weltge. A complete list of our members can be found here.