Offspring produced by crossover cannot contain information that is not already in the population, so an additional operator, mutation, is required. Mutation generates an offspring by randomly changing the values of genes at one or more gene positions of a selected chromosome. The number of offspring produced for each new generation depends on how members are introduced so as to maintain a fixed population size. In a pure replacement strategy, the whole population is replaced by a new one. In an elitist strategy, a proportion of the population survives to the next generation.
Mutation is a background operator which helps to sustain exploration.
Each offspring produced by crossover has a probability of 0.01 of being mutated before it enters the population. Mates are chosen at random among the survivors. Of course, this may not be the only way of encoding the problem for a genetic algorithm and so a faster solution may be possible. However, this requires effort on the part of the user to devise a clever encoding.