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2010

MEDAL Report 2010007
Genetic Algorithms
Martin Pelikan  (2010)

Abstract. Genetic algorithms are stochastic optimization methods inspired by natural evolution and genetics. Over the last few decades, genetic algorithms have been successfully applied to many problems of business, engineering, and science. Because of their operational simplicity and wide applicability, genetic algorithms are now playing an increasingly important role in computational optimization and operations research. This article provides an introduction to genetic algorithms as well as numerous pointers for obtaining additional information.


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Missouri Estimation of Distribution Algorithms Laboratory
Department of Mathematics and Computer Science
University of Missouri-St. Louis, St. Louis, MO

                   

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