#else
"original NON-FREE L-BFGS code by Nocedal et al. (NOT COMPILED)",
#endif
- "Low-storage BFGS (LBFGS) (local, derivative-based)",
+ "Limited-memory BFGS (L-BFGS) (local, derivative-based)",
"Principal-axis, praxis (local, no-derivative)",
"Limited-memory variable-metric, rank 1 (local, derivative-based)",
"Limited-memory variable-metric, rank 2 (local, derivative-based)",
potentially inefficient method).
.TP
.B NLOPT_LD_LBFGS
-Local (L) gradient-based (D) optimization using the low-storage BFGS
-(LBFGS) algorithm. (The objective function must supply the
+Local (L) gradient-based (D) optimization using the limited-memory BFGS
+(L-BFGS) algorithm. (The objective function must supply the
gradient.) Unconstrained optimization is supported in addition to
simple bound constraints (see above). Based on an implementation by
Luksan et al.
-% NLOPT_LD_LBFGS: Low-storage BFGS (LBFGS) (local, derivative-based)
+% NLOPT_LD_LBFGS: Limited-memory BFGS (L-BFGS) (local, derivative-based)
%
% See nlopt_minimize for more information.
function val = NLOPT_LD_LBFGS