AM_CPPFLAGS = -I$(top_srcdir)/api -I$(top_srcdir)/util
-MFILES = NLOPT_GN_DIRECT.m NLOPT_GN_DIRECT_L.m NLOPT_GN_DIRECT_L_RAND.m NLOPT_GN_DIRECT_NOSCAL.m NLOPT_GN_DIRECT_L_NOSCAL.m NLOPT_GN_DIRECT_L_RAND_NOSCAL.m NLOPT_GN_ORIG_DIRECT.m NLOPT_GN_ORIG_DIRECT_L.m NLOPT_GD_STOGO.m NLOPT_GD_STOGO_RAND.m NLOPT_LD_LBFGS_NOCEDAL.m NLOPT_LD_LBFGS.m NLOPT_LN_PRAXIS.m NLOPT_LD_VAR1.m NLOPT_LD_VAR2.m NLOPT_LD_TNEWTON.m NLOPT_LD_TNEWTON_RESTART.m NLOPT_LD_TNEWTON_PRECOND.m NLOPT_LD_TNEWTON_PRECOND_RESTART.m NLOPT_GN_CRS2_LM.m NLOPT_GN_MLSL.m NLOPT_GD_MLSL.m NLOPT_GN_MLSL_LDS.m NLOPT_GD_MLSL_LDS.m NLOPT_LD_MMA.m NLOPT_LN_COBYLA.m NLOPT_LN_NEWUOA.m NLOPT_LN_NEWUOA_BOUND.m NLOPT_LN_NELDERMEAD.m NLOPT_LN_SBPLX.m
+MFILES = NLOPT_GN_DIRECT.m NLOPT_GN_DIRECT_L.m NLOPT_GN_DIRECT_L_RAND.m NLOPT_GN_DIRECT_NOSCAL.m NLOPT_GN_DIRECT_L_NOSCAL.m NLOPT_GN_DIRECT_L_RAND_NOSCAL.m NLOPT_GN_ORIG_DIRECT.m NLOPT_GN_ORIG_DIRECT_L.m NLOPT_GD_STOGO.m NLOPT_GD_STOGO_RAND.m NLOPT_LD_LBFGS_NOCEDAL.m NLOPT_LD_LBFGS.m NLOPT_LN_PRAXIS.m NLOPT_LD_VAR1.m NLOPT_LD_VAR2.m NLOPT_LD_TNEWTON.m NLOPT_LD_TNEWTON_RESTART.m NLOPT_LD_TNEWTON_PRECOND.m NLOPT_LD_TNEWTON_PRECOND_RESTART.m NLOPT_GN_CRS2_LM.m NLOPT_GN_MLSL.m NLOPT_GD_MLSL.m NLOPT_GN_MLSL_LDS.m NLOPT_GD_MLSL_LDS.m NLOPT_LD_MMA.m NLOPT_LN_COBYLA.m NLOPT_LN_NEWUOA.m NLOPT_LN_NEWUOA_BOUND.m NLOPT_LN_NELDERMEAD.m NLOPT_LN_SBPLX.m NLOPT_LN_AUGLAG.m NLOPT_LD_AUGLAG.m NLOPT_LN_AUGLAG_EQ.m NLOPT_LD_AUGLAG_EQ.m NLOPT_LN_BOBYQA.m NLOPT_GN_ISRES.m
#######################################################################
# dummy C program to fool automake into making sure that CPPFLAGS etc.
--- /dev/null
+% NLOPT_GN_ISRES: ISRES evolutionary constrained optimization (global, no-derivative)
+%
+% See nlopt_minimize for more information.
+function val = NLOPT_GN_ISRES
+ val = 35;
--- /dev/null
+% NLOPT_LD_AUGLAG: Augmented Lagrangian method (local, derivative)
+%
+% See nlopt_minimize for more information.
+function val = NLOPT_LD_AUGLAG
+ val = 31;
--- /dev/null
+% NLOPT_LD_AUGLAG_EQ: Augmented Lagrangian method for equality constraints (local, derivative)
+%
+% See nlopt_minimize for more information.
+function val = NLOPT_LD_AUGLAG_EQ
+ val = 33;
--- /dev/null
+% NLOPT_LN_AUGLAG: Augmented Lagrangian method (local, no-derivative)
+%
+% See nlopt_minimize for more information.
+function val = NLOPT_LN_AUGLAG
+ val = 30;
--- /dev/null
+% NLOPT_LN_AUGLAG_EQ: Augmented Lagrangian method for equality constraints (local, no-derivative)
+%
+% See nlopt_minimize for more information.
+function val = NLOPT_LN_AUGLAG_EQ
+ val = 32;
--- /dev/null
+% NLOPT_LN_BOBYQA: BOBYQA bound-constrained optimization via quadratic models (local, no-derivative)
+%
+% See nlopt_minimize for more information.
+function val = NLOPT_LN_BOBYQA
+ val = 34;
% optimization. Names with _*N_ are derivative-free, while names
% with _*D_ are gradient-based algorithms. Algorithms:
%
-% NLOPT_GD_MLSL_LDS, NLOPT_GD_MLSL, NLOPT_GD_STOGO, NLOPT_GD_STOGO_RAND,
-% NLOPT_GN_CRS2_LM, NLOPT_GN_DIRECT_L, NLOPT_GN_DIRECT_L_NOSCAL,
-% NLOPT_GN_DIRECT_L_RAND, NLOPT_GN_DIRECT_L_RAND_NOSCAL, NLOPT_GN_DIRECT,
-% NLOPT_GN_DIRECT_NOSCAL, NLOPT_GN_MLSL_LDS, NLOPT_GN_MLSL,
-% NLOPT_GN_ORIG_DIRECT_L, NLOPT_GN_ORIG_DIRECT, NLOPT_LD_LBFGS,
-% NLOPT_LD_MMA, NLOPT_LD_TNEWTON, NLOPT_LD_TNEWTON_PRECOND,
-% NLOPT_LD_TNEWTON_PRECOND_RESTART, NLOPT_LD_TNEWTON_RESTART,
-% NLOPT_LD_VAR1, NLOPT_LD_VAR2, NLOPT_LN_COBYLA, NLOPT_LN_NELDERMEAD,
+% NLOPT_GD_MLSL_LDS, NLOPT_GD_MLSL, NLOPT_GD_STOGO, NLOPT_GD_STOGO_RAND,
+% NLOPT_GN_CRS2_LM, NLOPT_GN_DIRECT_L, NLOPT_GN_DIRECT_L_NOSCAL,
+% NLOPT_GN_DIRECT_L_RAND, NLOPT_GN_DIRECT_L_RAND_NOSCAL, NLOPT_GN_DIRECT,
+% NLOPT_GN_DIRECT_NOSCAL, NLOPT_GN_ISRES, NLOPT_GN_MLSL_LDS, NLOPT_GN_MLSL,
+% NLOPT_GN_ORIG_DIRECT_L, NLOPT_GN_ORIG_DIRECT, NLOPT_LD_AUGLAG_EQ,
+% NLOPT_LD_AUGLAG, NLOPT_LD_LBFGS, NLOPT_LD_LBFGS_NOCEDAL, NLOPT_LD_MMA,
+% NLOPT_LD_TNEWTON, NLOPT_LD_TNEWTON_PRECOND,
+% NLOPT_LD_TNEWTON_PRECOND_RESTART, NLOPT_LD_TNEWTON_RESTART,
+% NLOPT_LD_VAR1, NLOPT_LD_VAR2, NLOPT_LN_AUGLAG_EQ, NLOPT_LN_AUGLAG,
+% NLOPT_LN_BOBYQA, NLOPT_LN_COBYLA, NLOPT_LN_NELDERMEAD,
% NLOPT_LN_NEWUOA_BOUND, NLOPT_LN_NEWUOA, NLOPT_LN_PRAXIS, NLOPT_LN_SBPLX
%
-% For more information on individual functions, see their individual
-% help pages (e.g. "help NLOPT_LN_SUBPLEX").
+% For more information on individual algorithms, see their individual
+% help pages (e.g. "help NLOPT_LN_SBPLX").
function [xopt, fmin, retcode] = nlopt_minimize(algorithm, f, f_data, lb, ub, xinit, stop)
[xopt, fmin, retcode] = nlopt_minimize_constrained(algorithm, f, f_data, {}, {}, lb, ub, xinit, stop);
% optimization. Names with _*N_ are derivative-free, while names
% with _*D_ are gradient-based algorithms. Algorithms:
%
-% NLOPT_GD_MLSL_LDS, NLOPT_GD_MLSL, NLOPT_GD_STOGO, NLOPT_GD_STOGO_RAND,
-% NLOPT_GN_CRS2_LM, NLOPT_GN_DIRECT_L, NLOPT_GN_DIRECT_L_NOSCAL,
-% NLOPT_GN_DIRECT_L_RAND, NLOPT_GN_DIRECT_L_RAND_NOSCAL, NLOPT_GN_DIRECT,
-% NLOPT_GN_DIRECT_NOSCAL, NLOPT_GN_MLSL_LDS, NLOPT_GN_MLSL,
-% NLOPT_GN_ORIG_DIRECT_L, NLOPT_GN_ORIG_DIRECT, NLOPT_LD_LBFGS,
-% NLOPT_LD_MMA, NLOPT_LD_TNEWTON, NLOPT_LD_TNEWTON_PRECOND,
-% NLOPT_LD_TNEWTON_PRECOND_RESTART, NLOPT_LD_TNEWTON_RESTART,
-% NLOPT_LD_VAR1, NLOPT_LD_VAR2, NLOPT_LN_COBYLA, NLOPT_LN_NELDERMEAD,
+% NLOPT_GD_MLSL_LDS, NLOPT_GD_MLSL, NLOPT_GD_STOGO, NLOPT_GD_STOGO_RAND,
+% NLOPT_GN_CRS2_LM, NLOPT_GN_DIRECT_L, NLOPT_GN_DIRECT_L_NOSCAL,
+% NLOPT_GN_DIRECT_L_RAND, NLOPT_GN_DIRECT_L_RAND_NOSCAL, NLOPT_GN_DIRECT,
+% NLOPT_GN_DIRECT_NOSCAL, NLOPT_GN_ISRES, NLOPT_GN_MLSL_LDS, NLOPT_GN_MLSL,
+% NLOPT_GN_ORIG_DIRECT_L, NLOPT_GN_ORIG_DIRECT, NLOPT_LD_AUGLAG_EQ,
+% NLOPT_LD_AUGLAG, NLOPT_LD_LBFGS, NLOPT_LD_LBFGS_NOCEDAL, NLOPT_LD_MMA,
+% NLOPT_LD_TNEWTON, NLOPT_LD_TNEWTON_PRECOND,
+% NLOPT_LD_TNEWTON_PRECOND_RESTART, NLOPT_LD_TNEWTON_RESTART,
+% NLOPT_LD_VAR1, NLOPT_LD_VAR2, NLOPT_LN_AUGLAG_EQ, NLOPT_LN_AUGLAG,
+% NLOPT_LN_BOBYQA, NLOPT_LN_COBYLA, NLOPT_LN_NELDERMEAD,
% NLOPT_LN_NEWUOA_BOUND, NLOPT_LN_NEWUOA, NLOPT_LN_PRAXIS, NLOPT_LN_SBPLX
%
-% For more information on individual functions, see their individual
-% help pages (e.g. "help NLOPT_LN_SUBPLEX").
+% For more information on individual algorithms, see their individual
+% help pages (e.g. "help NLOPT_LN_SBPLX").