Fitness (genetic algorithm)

From Wikipedia, the free encyclopedia

It has been suggested that this article or section be merged with Fitness function. (Discuss)

This article needs additional citations for verification. Please help improve this article by adding reliable references. Unsourced material may be challenged and removed. (May 2008)

In optimisation techniques an objective measure is how good the solutions it finds are, e.g. a way of building a bridge across the M4 will cost 400,000. In genetic algorithms and genetic programming, by analogy with natural selection this is called fitness. Fitness is used to guide the search by deciding which individuals will be used as future points to look for better solutions.

Fitness in Biology means the extent to which an organism is adapted to or able to produce offspring in a particular environment.