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 al

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Yes, you can access Genetic Algorithms and Genetic Programming by Michael Affenzeller, Stefan Wagner, Stephan Winkler, Andreas Beham in PDF and/or ePUB format, as well as other popular books in Computer Science & Programming Algorithms. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Chapman and Hall/CRC

Year

2009

ISBN

9781420011326

Edition

Topic

Computer Science

Subtopic

Programming Algorithms

Index

Computer Science

Cover
Title
Copyright
Contents
List of Tables
List of Figures
List of Algorithms
Introduction
Chapter 1: Simulating Evolution: Basics about Genetic Algorithms
Chapter 2: Evolving Programs: Genetic Programming
Chapter 3: Problems and Success Factors
Chapter 4: Preservation of Relevant Building Blocks
Chapter 5: SASEGASA – More than the Sum of All Parts
Chapter 6: Analysis of Population Dynamics
Chapter 7: Characteristics of Offspring Selection and the RAPGA
Chapter 8: Combinatorial Optimization: Route Planning
Chapter 9: Evolutionary System Identification
Chapter 10: Applications of Genetic Algorithms: Combinatorial Optimization
Chapter 11: Data-Based Modeling with Genetic Programming
Conclusion and Outlook
Symbols and Abbreviations
References
Index