Genetic algorithms: The optimization events motivated by the biological analogies. The prime idea is to try to mimic the 'survival of the fittest' rule of the genetic mutation in the development of the optimization algorithms. The procedure starts with a population of the potential solutions to a problem and a method of measuring the fitness or the value of each solution. A new generation of the solutions is then produced by permitting existing solutions to 'mutate' (change a bit) or cross over (two solutions combine to obtain a new solution with both the aspects). The target is to produce new generations of solutions that have higher values.