Discrete Optimization Lab

Prof. Dr. Johannes Thürauf

At the Discrete Optimization Lab, we develop algorithms and solution techniques to solve optimization problems in different fields.

• Optimization under Uncertainty
  We develop solution methods that take into account uncertainties, e.g. uncertain data, in optimization problems. Our goal is to compute robust, reliable, resilient or adaptive solutions that can be applied across various fields, from resilient energy networks to logistics.
• Bilevel Optimization
  We further focus on solving bilevel and multilevel optimization problems that are capable of modeling hierarchical decision processes. These problems are particularly relevant in many applications including machine learning tasks.
• Optimization and Beyond
  Moreover, we conduct research in nonlinear, and integer programming, network optimization, graph algorithms, and polyhedral combinatorics.
• Link Theory and Practice
  We are dedicated to link theory and practice by developing advanced solution meth- ods, implementing them, and applying these methods to real-world challenges. Our research emphasizes interdisciplinary collaborations and combines expert knowledge from different fields, enabling us to jointly solve complex problems of today.

Prof. Dr. Johannes Thürauf
Professor of Discrete Optimization