Introduction to Genetic Algorithms

Front Cover
Springer Science & Business Media, Oct 24, 2007 - Technology & Engineering - 442 pages
Theoriginofevolutionaryalgorithmswasanattempttomimicsomeoftheprocesses taking place in natural evolution. Although the details of biological evolution are not completely understood (even nowadays), there exist some points supported by strong experimental evidence: • Evolution is a process operating over chromosomes rather than over organisms. The former are organic tools encoding the structure of a living being, i.e., a cr- ture is “built” decoding a set of chromosomes. • Natural selection is the mechanism that relates chromosomes with the ef ciency of the entity they represent, thus allowing that ef cient organism which is we- adapted to the environment to reproduce more often than those which are not. • The evolutionary process takes place during the reproduction stage. There exists a large number of reproductive mechanisms in Nature. Most common ones are mutation (that causes the chromosomes of offspring to be different to those of the parents) and recombination (that combines the chromosomes of the parents to produce the offspring). Based upon the features above, the three mentioned models of evolutionary c- puting were independently (and almost simultaneously) developed.
 

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nice book.easy tounderstanding the concepts

Contents

Evolutionary Computation
1
Genetic Algorithms
15
Terminologies and Operators of GA
39
Exercise Problems
81
Exercise Problems
103
Exercise Problems
129
Exercise Problems
163
Genetic Algorithm Optimization Problems
165
Exercise Problems
209
Genetic Algorithm Optimization in CC++
263
Applications of Genetic Algorithms
317
Introduction to Particle Swarm Optimization and Ant Colony
403
Bibliography
425
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