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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.
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.: SABIA :. Sistemas Adaptativos y Bioinspirados en Inteligencia Artificial