Droste, StefanJansen, ThomasWegener, Ingo2004-12-072004-12-0720002001-10-17http://hdl.handle.net/2003/539210.17877/DE290R-15248Evolutionary algorithms are general, randomized search heuristics that are influenced by many parameters. Though evolutionary algorithms are assumed to be robust,it is well-known that choosing the parameters appropriately is crucial for success and efficiency of the search. It has been shown in many experiments, that non-static parameter settings can be by far superior to static ones but theoretical verifications are hard to find. We investigate a very simple evolutionary algorithm and rigorously prove that employing dynamic parameter control can greatly speed-up optimization.enUniversität DortmundReihe Computational Intelligence ; 89004report