The problem of choosing an optimal signal set for non-Gaussian detection wa
s reduced to a smooth inequality constrained mini-max nonlinear programming
problem by Gockenbach and Kearsley. Here we consider the application of se
veral optimization algorithms, both global and local, to this problem. The
most promising results are obtained when special-purpose sequential quadrat
ic programming (SQP) algorithms are embedded into stochastic global algorit
hms.