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[nlopt.git] / api / nlopt.3

diff --git a/api/nlopt.3 b/api/nlopt.3
index 72fafd6ae9d6c3a801664c7e35e693c3d95a9177..709d48b3ff12dddbd66a0df7afd7281d5e486829 100644 (file)
--- a/api/nlopt.3
+++ b/api/nlopt.3
@@ -23,7 +23,7 @@ The "..." indicates any number of calls to NLopt functions, below, to
 set parameters of the optimization, constraints, and stopping
 criteria.  Here, \fBnlopt_set_ftol_rel\fR is merely an example of a
 possible stopping criterion.  You should link the resulting program
-with the linker flags -lnlopt -lm on Unix.
+with the linker flags \-lnlopt \-lm on Unix.
 .fi
 .SH DESCRIPTION
 NLopt is a library for nonlinear optimization.  It attempts to
@@ -177,7 +177,7 @@ If a lower/upper bound is not set, the default is no bound
 (unconstrained, i.e. a bound of infinity); it is possible to have
 lower bounds but not upper bounds or vice versa.  Alternatively, the
 user can call one of the above functions and explicitly pass a lower
-bound of -HUGE_VAL and/or an upper bound of +HUGE_VAL for some design
+bound of \-HUGE_VAL and/or an upper bound of +HUGE_VAL for some design
 variables to make them have no lower/upper bound, respectively.
 (HUGE_VAL is the standard C constant for a floating-point infinity,
 found in the math.h header file.)
@@ -316,15 +316,15 @@ DIRECT-L search algorithm by Jones et al. as modified by Gablonsky et
 al. to be more weighted towards local search.  Does not support
 unconstrainted optimization.  There are also several other variants of
 the DIRECT algorithm that are supported:
-.BR NLOPT_GLOBAL_DIRECT ,
+.BR NLOPT_GN_DIRECT ,
 which is the original DIRECT algorithm;
-.BR NLOPT_GLOBAL_DIRECT_L_RAND ,
+.BR NLOPT_GN_DIRECT_L_RAND ,
 a slightly randomized version of DIRECT-L that may be better in
 high-dimensional search spaces;
-.BR NLOPT_GLOBAL_DIRECT_NOSCAL ,
-.BR NLOPT_GLOBAL_DIRECT_L_NOSCAL ,
+.BR NLOPT_GN_DIRECT_NOSCAL ,
+.BR NLOPT_GN_DIRECT_L_NOSCAL ,
 and
-.BR NLOPT_GLOBAL_DIRECT_L_RAND_NOSCAL ,
+.BR NLOPT_GN_DIRECT_L_RAND_NOSCAL ,
 which are versions of DIRECT where the dimensions are not rescaled to
 a unit hypercube (which means that dimensions with larger bounds are
 given more weight).
@@ -350,7 +350,7 @@ is supported.  There is also another variant of this algorithm,
 .BR NLOPT_GD_STOGO_RAND ,
 which is a randomized version of the StoGO search scheme.  The StoGO
 algorithms are only available if NLopt is compiled with C++ code
-enabled, and should be linked via -lnlopt_cxx instead of -lnlopt (via
+enabled, and should be linked via \-lnlopt_cxx instead of \-lnlopt (via
 a C++ compiler, in order to link the C++ standard libraries).
 .TP 
 .B NLOPT_LN_NELDERMEAD
@@ -434,11 +434,14 @@ criteria/tolerances for the local searches, by
 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
@@ -517,7 +520,7 @@ Stop when an objective value of at least
 .I stopval
 is found: stop minimizing when a value <= \fIstopval\fR is found, or
 stop maximizing when a value >= \fIstopval\fR is found.  (Setting
-\fIstopval\fR to -HUGE_VAL for minimizing or +HUGE_VAL for maximizing
+\fIstopval\fR to \-HUGE_VAL for minimizing or +HUGE_VAL for maximizing
 disables this stopping criterion.)
 .TP
 .BI "nlopt_result nlopt_set_ftol_rel(nlopt_opt " "opt" ,
@@ -728,6 +731,6 @@ is implemented for up to 1111 dimensions.
 .SH AUTHORS
 Written by Steven G. Johnson.
 .PP
-Copyright (c) 2007-2012 Massachusetts Institute of Technology.
+Copyright (c) 2007-2014 Massachusetts Institute of Technology.
 .SH "SEE ALSO"
 nlopt_minimize(3)