Michael Affenzeller, Stefan Wagner, Stephan Winkler and Andreas Beham: Genetic algorithms and genetic programming modern concepts and practical applications
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In evolutionary algorithms, there is no guarantee that a child will have better fitness than its parents. But what if that was true, would the behaviour of an evolutionary algorithm change? The main goal of this book is to answer to this question. In eleven chapters, the authors introduce the theory and show extensive experimental results and their analysis for enhanced replacement strategies.
The book starts with an introduction to the basics of genetic algorithms (GA) in Chap. 1 and genetic programming (GP) in Chap. 2, and describes classical examples of applications, such as combinatorial optimization and symbolic regression. These chapters include descriptions of the GA and GP schema theories and building blocks hypothesis, which are the basis and motivation for the enhancements proposed in Chaps. 4 and 5.
Chapter 3 discusses the combination of “essential” genetic information from individuals (where “essential” implies alleles present in the optimal or high quality solutions)....
The author would like to thank Dr. W. B. Langdon for his helpful comments on the text.