Parameterized Analysis of Bio-inspired Computing
We will establish the field of parameterized analysis of bio-inspired computing which includes prominent approaches such as evolutionary algorithms and ant colony optimization. We will rigorously analyze features of instances of combinatorial optimization problems and their impact on the runtime behavior of bio-inspired computing methods. Furthermore, we design new bio-inspired computing algorithms that make use of instance features and hardness characteristics. Our results will advance the theoretical knowledge of bio-inspired computing, bridge the gap between theory and practice, and provide more powerful algorithms for complex optimization problems occurring for example in the field of supply chain management for the mining industry.
Lehrstuhl Theoretische Informatik I
Australian Research Council (ARC)