  This work presents the first application of the method of Genetic Algorithms
(GAs) to data analysis for the Laser Interferometer Space Antenna (LISA). In
the low frequency regime of the LISA band there are expected to be tens of
thousands galactic binary systems that will be emitting gravitational waves
detectable by LISA. The challenge of parameter extraction of such a large
number of sources in the LISA data stream requires a search method that can
efficiently explore the large parameter spaces involved. As signals of many of
these sources will overlap, a global search method is desired. GAs represent
such a global search method for parameter extraction of multiple overlapping
sources in the LISA data stream. We find that GAs are able to correctly extract
source parameters for overlapping sources. Several optimizations of a basic GA
are presented with results derived from applications of the GA searches to
simulated LISA data.
