Being based on the theory of evolution and natural selection, the
Genetic Algorithms (GA) represent a technique that has been proved as good
enough for the resolution of those problems that require a search through a
complex space of possible solutions. The maintenance of a population of
possible solutions that are in constant evolution may lead to its diversity being
lost, consequently it would be more difficult, not only the achievement of a
final solution but also the supply of more than one solution The method that is
described here tries to overcome those difficulties by means of a modification
in traditional GA?s. Such modification involves the inclusion of an additional
population that might avoid the mentioned loss of diversity of classical GA?s.
This new population would also provide the piece of exhaustive search that
allows to provide more than one solution.