TY - BOOK
T1 - Genetic algorithms and genetic programming
T2 - Modern concepts and practical applications
AU - Affenzeller, Michael
AU - Winkler, Stephan
AU - Wagner, Stefan
AU - Beham, Andreas
N1 - Publisher Copyright:
© 2009 by Taylor & Francis Group, LLC.
PY - 2009/1/1
Y1 - 2009/1/1
N2 - 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.
AB - 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.
KW - Genetic Algorithms
KW - Genetic Programming
KW - Structure Identification
KW - Combinatorial Optimization
KW - Genetic Algorithms
KW - Genetic Programming
KW - Structure Identification
KW - Combinatorial Optimization
UR - http://www.scopus.com/inward/record.url?scp=85055567229&partnerID=8YFLogxK
U2 - 10.1201/9781420011326
DO - 10.1201/9781420011326
M3 - Book
SN - 9781584886297
BT - Genetic algorithms and genetic programming
PB - CRC Press
ER -