The JEGA library \cite Eddy2001 contains two global
optimization methods. The first is a Multi-objective Genetic Algorithm (MOGA)
which performs Pareto optimization. The second is a Single-objective
Genetic Algorithm (SOGA) which performs optimization on a single
objective function. Both methods support general constraints and a
mixture of real and discrete variables. The JEGA library was written 
by John Eddy, currently a member of the technical staff in the
System Readiness and Sustainment Technologies department at Sandia National
Laboratories in Albuquerque. These algorithms are accessed as \c moga and
\c soga within %Dakota.
