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Numerical Insights Ser.: Genetic Algorithms and Genetic Programming : Modern Concepts and Practical Applications by Stephan Winkler, Andreas Beham, Stefan Wagner and Michael Affenzeller (2009, Hardcover)
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About this product
Product Identifiers
PublisherCRC Press LLC
ISBN-101584886293
ISBN-139781584886297
eBay Product ID (ePID)50941495
Product Key Features
Number of Pages394 Pages
Publication NameGenetic Algorithms and Genetic Programming : Modern concepts and Practical Applications
LanguageEnglish
SubjectProgramming / Games, Programming / Algorithms, Life Sciences / Genetics & Genomics, Databases / Data Mining
Publication Year2009
TypeTextbook
AuthorStephan Winkler, Andreas Beham, Stefan Wagner, Michael Affenzeller
Subject AreaComputers, Science
SeriesNumerical Insights Ser.
FormatHardcover
Dimensions
Item Height1 in
Item Weight24.1 Oz
Item Length9.6 in
Item Width6.4 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2009-003656
IllustratedYes
Table Of ContentIntroduction. 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.
SynopsisGenetic 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., 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.
LC Classification NumberQA76.623
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