Selection in Genetic Algorithms

Friday, January 18, 2008 | Labels: , | |

We had seen the basic Genetic Algorithms operations in the previous post. In this post, let us see, in detail, how the selection or reproduction operator works.

Selection is the procedure by which candidate solutions are determined for recombination to generate offsprings for the next generation. The chance that a particular candidate solution or string will be selected is based on the string's fitness value.

There are many types of selection operators. For example, a selection operator always selects the fittest individuals and discards the remaining solutions. Depending on the domain, many variants of the selection operators are being used. It is difficult to determine which is better.

The most common selection method used in Genetic Algorithms is the Roulette Wheel Method, which selects the strings statistically based on their relative fitness value, calculated from a fitness function. At the time of offspring creation, a simple spin of the roulette wheel yields the lucky candidate. In Roulette Wheel, highly fit candidate solutions get more chances of being selected for the next generation.

We will see the Roulette Wheel method of selection, in detail, later on.