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by Re I He, Computat I Onal, I Ntell, I Gence, Ingo Wegener, Ingo Wegener
http://sfbci.cs.uni-dortmund.de/home/English/Publications/Reference/Downloads/Weg00d.ps
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Abstract:
Abstract: Evolutionary algorithms are problem-independent randomized search heuristics. It is discussed when it is useful to work with such algorithms and it is argued why these search heuristics should be analyzed just as all other deterministic and randomized algorithms. Such an approach is started by analyzing a simple evolutionary algorithm on linear functions, quadratic functions, unimodal functions, and its behavior on plateaus of constant fitness. Furthermore, it is investigated what can be gained and lost by a dynamic variant of this algorithm. Finally, it is proved that crossover can decrease the run time of evolutionary algorithms significantly.
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