This new group of chromosomes has one other process performed on it called mutation. The GA takes each of the chromosomes and reads through the list of genes. At random, the GA will change the value in the gene. The probability of this change occuring is pretty low though since the GA only makes the change 0.001% of the time. So, what's the point of doing the cross-over and mutate steps? The cross-over step is basically the same as cross-breeding to produce plants or animals with desired characteristics. The mutate step is analogous to the mutation process that occurs in nature. Mutations don't happen very often and when they do the organism is usually worse off for it. Mutations that do work can create an organism or chromosome that is more fit then it's peers. At this point, we have three groups of chromosomes. The the original randomly created group, most-fit group and the group that resulted from the cross-over/mutate step. We're well on the to creating a new generation here but it needs to be filled out a bit. In a typical GA, the number of chromosomes the are selected to be in the most-fit group equals 40% of the original group. Since the cross-over/mutate step created an equal number of chromosomes, we now have 80% of the necessary total. The last 20% is created at random just like the original generation of chromosomes. These three groups are combined to form the next generation of chromosomes. This new generation is then graded using the fitness function and the whole process of most-fit selection and cross-over/mutate chromosome creation is repeated through a pre-determined number of generations. To recap: 1. Create the first generation of chromosomes. 2. Test the chromosomes with a fitness function. Rank according to fitness. 3. Select the top 40% based on rank and save the chromosomes. This is the most-fit group. 4. Use copies of the most-fit group chromosomes to do cross-over and mutation till the number of new chromosomes is equal to the number in the most-fit group. 5. Combine the most-fit group and the cross-over/mutate group then pad with new random chromosomes till the number is equal to the original generation of chromosomes. 6. Go back to step #2 with the new generation of chromosomes. Repeat until the pre-determined number of generations have been processed. 7. Do the fitness function one more time. The chromosome that ranks highest is the fittest of all tested. The result of this whole process is a single chromosome that is the most fit of all the chromosomes created during the time the GA was operating. (more)