Optimisation and Logistics
We research optimisation methods that are frequently used to solve hard and complex optimisation problems. These include linear programming, branch and bound, genetic algorithms, evolution strategies, genetic programming, ant colony optimisation, particle swarm optimisation, local search and other related approaches.
Our research is related to real world issues and how problems can be solved by specialised computing techniques. And in our theoretical research we analyse how heuristic methods work and show in a rigorous way how these algorithms are able to deal with different types of problems. This includes mathematical investigations that analyse the runtime of heuristics in a rigorous way. Furthermore, we use statistical approaches to understand the difficulty of interesting problems for certain classes of algorithms.