Written by core members of the HeuristicLab team, this book sets out the basic workflow of genetic algorithms (GAs) and genetic programming (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, the book also shows how to increase achievable solution quality. The book reviews algorithmic development in the context of GAs and GP, and describes their application to two combinatorial optimization problems (the traveling salesman problem and the capacitated vehicle routing problem) using HeuristicLab, a paradigm-independent and extensible environment for heuristic optimization, as a platform for algorithmic development. To highlight the properties of the algorithmic measures in the field of GP, the book analyzes GP-based nonlinear structure identification applied to time series and classification problems. Several generic algorithms are described that can be used in any kind of GA or with evolutionary optimization techniques. Affenzeller is affiliated with Upper Austria University of Applied Sciences and Johannes Kepler University of Linz. Annotation ©2009 Book News, Inc., Portland, OR (booknews.com)