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After the initial generations of a GA, it is often the case that the most fit individuals are near a solution. In this case, some GAs will initiate local searches around the most fit individual. One way to accomplish this is to create a set of slight mutations of the most fit individual. Let us refer to the most fit individual as individual A, and refer to the population of mutations of this individual as P_A. If the most fit individual in P_A is more fit than individual A, then the most fit individual of P_A replaces individual Α in the population.