Thus only a few of the genes are changed. This number is dependent upon the length of the string since a string of five characters will require less change, while a string of 40 characters will use more. Thus logic makes sense since it is easier for our bodies and other things to copy short strands of information without making a mistake than to copy a big, long chain of information without making a mistake. Once the alterations are done, the chromosomes are mated and the process repeats until the optimal solution is found. So now that you now what a genetic algorithm is and how it works, you're no doubt wondering what can it be used for.
Genetic algorithms have several different applications areas.
One of the most common one of these is in multidimensional optimization problems, in which the character string of the chromosome can be used to encode the values for the different parameters being optimized. The reason behind this is that GAs were pretty much designed to be used in such areas. Their imitation of the evolutionary process makes them ideal for finding the optimal solution to a problem, since the theory of evolution is set up to leave only the best possible members of a species alive so they can make more. However, since the algorithm also reflects a human chromosome in some aspects, it also has applications in the field of biology. GAs are used in biocomputing in order to analyze a set of experimental, usually sequencing data.