Evolutionary Algorithms (EA) have demonstrated
their ability to solve optimization tasks in a wide range of
applications. In this paper, after outlining the basics of such algorithms,
the possibilities of one of the latest to emerge, the Breeder Genetic
Algorithm (BGA) are exemplified by addressing a classical numerical
optimization problem: the Fletcher-Powell pseudo-random function.