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ISBN 13: 9781138114272
Author: Michael Affenzeller, Stefan Wagner, Stephan Winkler, Andreas Beham
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.
Simulating Evolution: Basics about Genetic Algorithms
Evolving Programs: Genetic Programming
Problems and Success Factors
SASEGASA: A Novel and Self-Adaptive Parallel Genetic Algorithm
Analysis of Population Dynamics
Building Block Analysis
Combinatorial Optimization: Route Planning
Evolutionary System Identification
Applications of Genetic Algorithms
Genetic Propagation
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Tags: Michael Affenzeller, Stefan Wagner, Stephan Winkler, Andreas Beham, Algorithms, Genetic
