Dynamic Parameter Control in Simple Evolutionary Algorithms

Stefan Droste droste@ls2.cs.uni-dortmund.de; Thomas Jansen jansen@ls2.cs.uni-dortmund.de; Ingo Wegener wegener@ls2.cs.uni-dortmund.de    FB Informatik, LS 2, Univ. Dortmund, 44221 Dortmund, Germany

Abstract

Evolutionary 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 ...

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