Genetic Algorithm Concepts and Working
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Genetic Algorithm is a search based optimization algorithm used to solve problems were traditional methods fails. It is an randomized algorithm where each step follows randomization principle. Genetic Algorithm was developed by John Holland, from the University of Michigan, in 1960.
He proposed this algorithm based on the Charles Darwin's theory on Evolution of organism. Genetic Algorithm follows the principal of "Survival of Fittest". Only the fittest individual has the possibility to survive to the next generation and hence when the generations evolve only the fittest individuals survive.
Genetic Algorithms operates on Solutions, hence called as search based optimization algorithm. It search for an optimal solution from the existing set of solutions in search space. The process of Genetic Algorithm is given as,1.
Randomly choose some individuals (Solutions) from the existing population2. Calculate the fitness function3. Choose the fittest individuals as parental chromosomes4.
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