Event Details

An Introduction to Robust Combinatorial Optimization

An Introduction to Robust Combinatorial Optimization

Under the umbrella of robust optimization, many different approaches to treat uncertainty have been developed. While most have in common that some kind of worst-case performance measure is optimized, there can be quite large differences in the types of techniques that are applied to treat these problems. In particular combinatorial problems often behave quite differently to their more general counterparts.

In this class I try to give a general introduction to this topic, covering min-max, min-max regret, two-stage and multi-stage problems with different types of uncertainty (discrete, budgeted, intervals), as well as pointing out some of the more recent results and challenges. In pen-and-paper tutorials we gain a deeper understanding of these approaches and test them in small programming exercises using Gurobi with Python.