From: stevenj Date: Wed, 12 May 2010 02:13:51 +0000 (-0400) Subject: slight man page corrections X-Git-Url: http://www.chiark.greenend.org.uk/ucgi/~ianmdlvl/git?a=commitdiff_plain;h=3dc14747a99faba030e64215d56455778e620688;p=nlopt.git slight man page corrections darcs-hash:20100512021351-c8de0-47f32de74b4d6dbe029d07fd0f1356b4408b5dd3.gz --- diff --git a/api/nlopt.3 b/api/nlopt.3 index 2307c73..755cb9a 100644 --- a/api/nlopt.3 +++ b/api/nlopt.3 @@ -33,7 +33,7 @@ of .I n design variables, using the specified .IR algorithm , -possibly subject to linear or nonlinear constraints. The minimum +possibly subject to linear or nonlinear constraints. The optimum function value found is returned in \fIopt_f\fR (type double) with the corresponding design variable values returned in the (double) array .I x @@ -66,8 +66,8 @@ between a variety of minimization algorithms. Some of these algorithms require the gradient (derivatives) of the function to be supplied via .IR f , and other algorithms do not require derivatives. Some of the -algorithms attempt to find a global minimum within the given bounds, -and others find only a local minimum. Most of the algorithms only +algorithms attempt to find a global optimum within the given bounds, +and others find only a local optimum. Most of the algorithms only handle the case where there are no nonlinear constraints. The NLopt library is a wrapper around several free/open-source minimization packages, as well as some new implementations of published @@ -287,7 +287,7 @@ Constants with in their names refer to global optimization methods, whereas .B _L{N,D}_ -refers to local optimization methods (that try to find a local minimum +refers to local optimization methods (that try to find a local optimum starting from the starting guess .IR x ). Constants with @@ -427,7 +427,7 @@ Global (G) derivative-based (D) or derivative-free (N) optimization using the multi-level single-linkage (MLSL) algorithm with a low-discrepancy sequence (LDS). This algorithm executes a quasi-random (LDS) sequence of local searches, with a clustering heuristic to -avoid multiple local searches for the same local minimum. The local +avoid multiple local searches for the same local optimum. The local search uses the derivative/nonderivative algorithm set by .I nlopt_set_local_optimizer (currently defaulting to @@ -506,10 +506,10 @@ disables this stopping criterion.) .BI " double " tol ); .sp Set relative tolerance on function value: stop when an optimization step -(or an estimate of the minimum) changes the function value by less +(or an estimate of the optimum) changes the function value by less than .I tol -multiplied by the absolute value of the function value. (If there is any chance that your minimum function value is close to zero, you might want to set an absolute tolerance with +multiplied by the absolute value of the function value. (If there is any chance that your optimum function value is close to zero, you might want to set an absolute tolerance with .B nlopt_set_ftol_abs as well.) Criterion is disabled if \fItol\fR is non-positive. .TP @@ -518,7 +518,7 @@ as well.) Criterion is disabled if \fItol\fR is non-positive. .BI " double " tol ); .sp Set absolute tolerance on function value: stop when an optimization step -(or an estimate of the minimum) changes the function value by less +(or an estimate of the optimum) changes the function value by less than .IR tol . Criterion is disabled if \fItol\fR is non-positive. @@ -528,7 +528,7 @@ Criterion is disabled if \fItol\fR is non-positive. .BI " double " tol ); .sp Set relative tolerance on design variables: stop when an optimization step -(or an estimate of the minimum) changes every design variable by less +(or an estimate of the optimum) changes every design variable by less than .I tol multiplied by the absolute value of the design variable. (If there is @@ -545,7 +545,7 @@ Set absolute tolerances on design variables. \fItol\fR is a pointer to an array of length .I n giving the tolerances: stop when an -optimization step (or an estimate of the minimum) changes every design +optimization step (or an estimate of the optimum) changes every design variable .IR x [i] by less than @@ -631,6 +631,9 @@ unknown algorithm was specified, etcetera). .TP .B NLOPT_OUT_OF_MEMORY Ran out of memory. +.TP +.B NLOPT_ROUNDOFF_LIMITED +Halted because roundoff errors limited progress. .SH LOCAL OPTIMIZER Some of the algorithms, especially MLSL and AUGLAG, use a different optimization algorithm as a subroutine, typically for local @@ -642,7 +645,7 @@ the local search algorithm and its tolerances by calling: .br .BI " const nlopt_opt " "local_opt" ); .sp -Here, \fIlocal_opt\fR is another \fBnlopt_opt\fB object whose +Here, \fIlocal_opt\fR is another \fBnlopt_opt\fR object whose parameters are used to determine the local search algorithm and stopping criteria. (The objective function and nonlinear-constraint parameters of \fIlocal_opt\fR are ignored.) The dimension \fIn\fR of