Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications

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Michael Affenzeller Stefan Wagner

Genetic Algorithms and Genetic Programming

Modern Concepts and Practical Applications

Michael Affenzeller, Stefan Wagner, Stephan Winkler , Andreas Beham

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English

CRC Press
16 April 2018

Computing: general; Algorithms & data structures; Data mining; Computer science

Series: Numerical Insights

Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications 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.

By: Michael Affenzeller, Stefan Wagner, Stephan Winkler, Andreas Beham
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 594g
ISBN: 9781138114272
ISBN 10: 1138114278
Series: Numerical Insights
Pages: 400
Publication Date: 16 April 2018
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Introduction. Simulating Evolution: Basics about Genetic Algorithms. Evolving Programs: Genetic Programming. Problems and Success Factors. Preservation of Relevant Building Blocks. SASEGASA—More Than the Sum of All Parts. Analysis of Population Dynamics. Characteristics of Offspring Selection and the RAPGA. Combinatorial Optimization: Route Planning. Evolutionary System Identification. Applications of Genetic Algorithms: Combinatorial Optimization. Data-Based Modeling with Genetic Programming. Conclusion and Outlook. Symbols and Abbreviations. References. Index.

Michael Affenzeller, Stefan Wagner, Stephan Winkler, Andreas Beham