Dynamic parameter control in simple evolutionary algorithms. FOGA’2000. Foundations of Genetic Algorithms 6

Evolutionary algorithms are general, randomized search heuristics that are influ-enced 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 algo-rithm and rigorously prove that employing dynamic parameter control can greatly speed-up optimization.