Evolutionary computation techniques have received a lot of attention regarding their potential as optimization techniques for complex real-world problems. These techniques, based on the powerful principle of "survival of the fittest", model some natural phenomena of genetic inheritance and Darwinian strife for survival; they also constitute an interesting category of modern heuristic search. This introductory article presents the main paradigms of evolutionary algorithms (genetic algorithms, evolution strategies, evolutionary programming, genetic programming) as well as other (hybrid) methods of evolutionary computation. Two particular research directions (parallel evolutionary techniques and self-adaptation) are discussed further in the last part of this paper. 1
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