Genetic algorithm is a part of evolutionary computing which is a rapidly growing area of artificial intelligence. The genetic algorithm is inspired by Darwin’s theory about evolution. Here the solution to a problem solved by the genetic algorithm is evolved. In a genetic algorithm, a population of strings (called chromosomes or the genotype of the gen me), which encode candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem, is evolved toward better solutions. Traditionally, solutions are represented in the form of binary strings, composed of 0s and 1s, the same way other encoding schemes can also be applied.
