  Since the inception of genetic algorithmics the identification of
computational efficiencies of the simple genetic algorithm (SGA) has been an
important goal. In this paper we distinguish between a computational competency
of the SGA--an efficient, but narrow computational ability--and a computational
proficiency of the SGA--a computational ability that is both efficient and
broad. Till date, attempts to deduce a computational proficiency of the SGA
have been unsuccessful. It may, however, be possible to inductively infer a
computational proficiency of the SGA from a set of related computational
competencies that have been deduced. With this in mind we deduce two
computational competencies of the SGA. These competencies, when considered
together, point toward a remarkable computational proficiency of the SGA. This
proficiency is pertinent to a general problem that is closely related to a
well-known statistical problem at the cutting edge of computational genetics.
