1st Edition
Evolutionary Computation 1 Basic Algorithms and Operators
378 Pages
by
CRC Press
378 Pages
by
CRC Press
378 Pages
by
CRC Press
Also available as eBook on:
The field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.
WHY EVOLUTIONARY COMPUTATION?
Introduction to evolutionary computation
Possible applications of evolutionary computation
Advantages (and disadvantages) of evolutionary computation over other approaches
EVOLUTIONARY COMPUTATION: THE BACKGROUND
Principles of evolutionary processes
Principles of genetics
A history of evolutionary computation
EVOLUTIONARY ALGORITHMS AND THEIR STANDARD INSTANCES
Introduction to evolutionary algorithms
Genetic algorithms
Evolution strategies
Evolutionary programming
Derivative methods in genetic programming
Learning classifier systems
Hybrid methods
REPRESENTATIONS
Introduction to representations
Binary strings
Real-valued vectors
Permutations
Finite-state representations
Parse trees
Guidelines for a suitable encoding
Other representations
SELECTION
Introduction to selection
Proportionary selection and sampling algorithms
Tournament selection
Rank-based selection
Boltzmann selection
Other selection methods
Generation gap methods
A comparison of selection mechanisms
Interactive evolution
SEARCH OPERATORS
Introduction to search operators
Mutation operators
Recombination
Other operators
INDEX
Introduction to evolutionary computation
Possible applications of evolutionary computation
Advantages (and disadvantages) of evolutionary computation over other approaches
EVOLUTIONARY COMPUTATION: THE BACKGROUND
Principles of evolutionary processes
Principles of genetics
A history of evolutionary computation
EVOLUTIONARY ALGORITHMS AND THEIR STANDARD INSTANCES
Introduction to evolutionary algorithms
Genetic algorithms
Evolution strategies
Evolutionary programming
Derivative methods in genetic programming
Learning classifier systems
Hybrid methods
REPRESENTATIONS
Introduction to representations
Binary strings
Real-valued vectors
Permutations
Finite-state representations
Parse trees
Guidelines for a suitable encoding
Other representations
SELECTION
Introduction to selection
Proportionary selection and sampling algorithms
Tournament selection
Rank-based selection
Boltzmann selection
Other selection methods
Generation gap methods
A comparison of selection mechanisms
Interactive evolution
SEARCH OPERATORS
Introduction to search operators
Mutation operators
Recombination
Other operators
INDEX
Biography
Thomas Baeck, D.B Fogel, Z Michalewicz
"This new volume contains some extended material and provides basic information on evolutionary algorithms … This book provides an interesting reference for theorists, teachers, and practitioners also."
-H.D. Hecker, Zentralblatt Math
