In the second chapter we present the first average-case analysis of three different algorithms for maintaining a topological ordering of the nodes of a directed acyclic graph under dynamic updates. We prove an expected runtime which is significantly less than the best known worst-case bound for this problem.
We finish with a third chapter that deals with randomized search heuristics. We examine the impact of different diversity mechanisms on the runtime of a single-objective evolutionary algorithm. We also show how this can exponentially slow down evolutionary algorithms for multi-objective problems.