daga is an experimental release of a 2-level genetic algorithm compatible with the GALOPPS GA software. It is a meta-GA which dynamically evolves a population of GAs to solve a problem presented to the lower-level GAs. When multiple GAs (with different operators, parameter settings, etc.) are simultaneously applied to the same problem, the ones showing better performance have a higher probability of surviving and "breeding" to the next macro-generation (i.e., spawning new "daughter"-GAs with characteristics inherited from the parental GA or GAs. In this way, we try to encourage good problem-solving strategies to spread to the whole population of GAs.

Because the operation of DAGA2 also acts as an island (coarse-grain) parallel GA, with non-homogeneous islands, it can solve some relatively difficult (for serial or "standard" island-parallel GAs) problems without paying a major penalty for its second-level evolution. On many problems, DAGA2 appears to be relatively robust, and quite insensitive to the settings of the level-two parameters, while very effective in solving the problem. For more information, please see our papers and technical reports, GARAGe97-02-01, GARAGe96-06-01, and GARAGe96-03-01, describing DAGA2 and its performance.

DAGA2 has been tested only under Sun Solaris using PVM. You may download a gzipped tar file of DAGA2 Release 3.2 from our ftp site. Its differences from GALOPPS are documented via README files in each directory.