This work deals with the application of Memetic Algorithms to the
Microarray Gene Ordering problem, a NP-hard problem with strong
implications in Medicine and Biology. It consists in ordering a
set of genes, grouping together the ones with similar behavior. We
propose a MA, and evaluate the influence of several features, such
as the intensity of local searches and the utilization of multiple
populations, in the performance of the MA. We also analyze the
impact of different objective functions on the general aspect of
the solutions. The instances used for experimentation are
extracted from the literature and represent real biological
systems.