From b75f3ca6f7ac3771ec052f26811bb985aaf7ec80 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=C3=89ric=20Thi=C3=A9baut?= Date: Tue, 17 Oct 2023 18:12:32 +0200 Subject: [PATCH] Update doc. --- README.md | 36 ++++++++++++++++++------------------ 1 file changed, 18 insertions(+), 18 deletions(-) diff --git a/README.md b/README.md index fe4868b..3c5c642 100644 --- a/README.md +++ b/README.md @@ -49,7 +49,7 @@ package: equality constraints, and linear inequality constraints. All these algorithms are trust region methods where the variables are updated -according to an affine or quadratic local approximation interpolating the +according to an affine or a quadratic local approximation interpolating the objective function at a given number of points (set by keyword `npt` by some of the algorithms). No derivatives of the objective function are needed. These algorithms are well suited to problems with a non-analytic objective function @@ -130,19 +130,19 @@ end The keywords allowed by the different algorithms are summarized by the following table. -| Keyword | Description | Algorithms | -|:-------------|:---------------------------------------|:-----------------------------| -| `rhobeg` | Initial trust region radius | all | -| `rhoend` | Final trust region radius | all | -| `ftarget` | Target objective function value | all | -| `maxfun` | Maximum number of function evaluations | all | -| `iprint` | Verbosity level | all | -| `npt` | Number of points in local model | `bobyqa`, `lincoa`, `newuoa` | -| `xl` | Lower bound | `bobyqa`, `cobyla`, `lincoa` | -| `xu` | Upper bound | `bobyqa`, `cobyla`, `lincoa` | -| `nlconstr` | Non-linear constraints | `cobyla` | -| `eqconstr` | Linear equality constraints | `cobyla`, `lincoa` | -| `ineqconstr` | Linear inequality constraints | `cobyla`, `lincoa` | +| Keyword | Description | Algorithms | +|:-----------------|:---------------------------------------|:-----------------------------| +| `rhobeg` | Initial trust region radius | all | +| `rhoend` | Final trust region radius | all | +| `ftarget` | Target objective function value | all | +| `maxfun` | Maximum number of function evaluations | all | +| `iprint` | Verbosity level | all | +| `npt` | Number of points in local model | `bobyqa`, `lincoa`, `newuoa` | +| `xl` | Lower bound | `bobyqa`, `cobyla`, `lincoa` | +| `xu` | Upper bound | `bobyqa`, `cobyla`, `lincoa` | +| `nonlinear_ineq` | Non-linear inequality constraints | `cobyla` | +| `linear_eq` | Linear equality constraints | `cobyla`, `lincoa` | +| `linear_ineq` | Linear inequality constraints | `cobyla`, `lincoa` | Assuming `n = length(x)` is the number of variables, then: @@ -174,11 +174,11 @@ Assuming `n = length(x)` is the number of variables, then: elementwise lower and upper bounds for the variables. Feasible variables are such that `xl ≤ x ≤ xu` (elementwise). -- `nonlinear_ineq` (default `0`) may be specified with the number `m` of +- `nonlinear_ineq` (default `nothing`) may be specified with the number `m` of non-linear inequality constraints expressed `c(x) ≤ 0`. If the caller is - interested in the values of `c(x)` at the returned solution the keyword may - be set with a vector of `m` double precision floating-point values - to store `c(x)`. This keyword only exists for `cobyla`. + interested in the values of `c(x)` at the returned solution, the keyword may + be set with a vector of `m` double precision floating-point values to store + `c(x)`. This keyword only exists for `cobyla`. - `linear_eq` (default `nothing`) may be specified as a tuple `(Aₑ,bₑ)` to represent linear equality constraints. Feasible variables are such that `Aₑ⋅x