§16§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 §16§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. §04§Evolutionary Computation.- Genetic Algorithms.- Terminologies and Operators of GA.- Advanced Operators and Techniques in Genetic Algorithm.- Classification of Genetic Algorithm.- Genetic Programming.- Genetic Algorithm Optimization Problems.- Genetic Algorithm Implementation Using Matlab.- Genetic Algorithm Optimization in C/C++.- Applications of Genetic Algorithms.- to Particle Swarm Optimization and Ant Colony Optimization. §02§The basic concept of Genetic Algorithms is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. This book is designed to provide an in-depth knowledge on the basic operational features and characteristics of Genetic Algorithms. The various operators and techniques given in the book are pertinent to carry out Genetic Algorithm Research Projects. The book features basic concepts, several applications of genetic algorithms and solved genetic problems using MATLAB software and C/C++. It is written for a wide range of readers who wish to learn the basic concepts of genetic algorithms with a minimal effort.
