The fitness function is applied to the candidate solutions and any subsequent offspring.

The concept of a fitness function (or objective function) is central to artificial life systems.

In general, evaluating a fitness function for every individual is frequently the most costly operation of this algorithm.

What generations the fitness function applies to can also be set.

This population is then repeatedly modified according to a fitness function.

The fitness function determines the good solutions and the solutions that can be eliminated.

Genic capture does not require any particular fitness function.

At each step, the individuals are evaluated according to the given fitness function (survival of the fittest).

Therefore, it can be beneficial to selectively use the original fitness function together with the approximate model.

The fitness function is defined over the genetic representation and measures the quality of the represented solution.