with or without derivatives, and determines whether the objective
function needs gradients.)
.TP
-.B NLOPT_LD_MMA
+\fBNLOPT_LD_MMA\fR, \fBNLOPT_LD_CCSAQ\fR
Local (L) gradient-based (D) optimization using the method of moving
asymptotes (MMA), or rather a refined version of the algorithm as
published by Svanberg (2002). (NLopt uses an independent
-free-software/open-source implementation of Svanberg's algorithm.)
+free-software/open-source implementation of Svanberg's algorithm.) CCSAQ
+is a related algorithm from Svanberg's paper which uses a local quadratic
+approximation rather than the more-complicated MMA model; the two usually
+have similar convergence rates.
The
.B NLOPT_LD_MMA
algorithm supports both bound-constrained and unconstrained