Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications

ISBN-13: 9781138114272 / Angielski / Miękka / 2018 / 379 str.

Michael Affenzeller; Stefan Wagner; Stephan Winkler

Opis

This book describes several generic algorithmic concepts that can be used in any kind of GA or with evolutionary optimization techniques. It 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, the authors show how to substantially increase achievable solution quality. They also describe structure identification using HeuristicLab as a platform for algorithm development. Software, dynamical presentations of representative test runs, and more are available on a supplementary website.

Spis treści

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.