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Genetic algorithms and genetic programming. Modern concepts and practical applications. (English) Zbl 1231.90003
Numerical Insights 6. Boca Raton, FL: CRC Press (ISBN 978-1-58488-629-7/hbk; 978-1-138-11427-2/pbk; 978-1-4200-1132-6/ebook). xxvii, 365 p. (2009).
Publisher’s description: This book discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for algorithm development.
The book focuses on both theoretical and empirical aspects. The theoretical sections explore the important and characteristic properties of the basic GA as well as main characteristics of the selected algorithmic extensions developed by the authors. In the empirical parts of the text, the authors apply GAs to two combinatorial optimization problems: the traveling salesman and capacitated vehicle routing problems. To highlight the properties of the algorithmic measures in the field of GP, they analyze GP-based nonlinear structure identification applied to time series and classification problems.
Written by core members of the HeuristicLab team, this book provides a better understanding of the basic workflow of GAs and GP, encouraging readers to establish new bionic, problem-independent theoretical concepts. By comparing the results of standard GA and GP implementation with several algorithmic extensions, it also shows how to substantially increase achievable solution quality.

90-02 Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming
90C59 Approximation methods and heuristics in mathematical programming
90C27 Combinatorial optimization
68W05 Nonnumerical algorithms
68T05 Learning and adaptive systems in artificial intelligence
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