Genetic Algorithms (GAs) are adaptive heuristic search algorithm premised on the
evolutionary ideas of natural selection and genetic. The basic concept of GAs 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. As such
they represent an intelligent exploitation of a random search within a defined search
space to solve a problem.
GAs were introduced as a computational analogy of adaptive systems. They are modelled
loosely on the principles of the evolution via natural selection, employing a population of
individuals that undergo selection in the presence of variation-inducing operators such as
mutation and recombination (crossover). A fitness function is used to evaluate
individuals, and reproductive success varies with fitness.
Thursday, September 17, 2009
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