Scilab Home Page | Wiki | Bug Tracker | Forge | Mailing List Archives | Scilab Online Help | File Exchange
ATOMS : Fmincon details

# Fmincon

Nonlinearily constrained multivariable optimization solver
(4651 downloads for this version - 27729 downloads for all versions)
Details
Version
1.0.3
A more recent valid version exists: 1.0.7
Author
Michael Baudin, Stéphane Motteet
Maintainers
Administrator ATOMS
Stéphane MOTTELET
Category
License
Dependencies
Creation Date
April 21, 2021
Source created on
Scilab 6.1.x
Binaries available on
Scilab 6.1.x:
Windows 64-bit Windows 32-bit Linux 64-bit Linux 32-bit macOS
Install command
`--> atomsInstall("fmincon")`
Report a bug
Description
```            Fmincon toolbox

Purpose
-------

The goal of this toolbox is to provide a fmincon function in Scilab.
The fmincon function is a linearly and nonlinearily constrained optimization
solver.
Currently, we use ipopt for the actual solver of fmincon but other solvers could
be added in the future.

We provide the optimoptions function (which superseeds the former optimset),
which manage options which are required by fmincon.

The current implementation is able to manage the following use cases. By default
we use a L-BFGS formula in order to compute an approximate of the Hessian of the
Lagrangian.

(0) The initial guess is provided in the x0 input argument.

(1) The nonlinear objective function and
the nonlinear constraints are provided.
The fun and nonlcon function can be customized to  configure the nonlinear
objective function and nonlinear constraints.
In this case, we use order two finite differences with optimal step size in
order to compute the gradient of the objective function and the gradient of the
constraints.

(2) The parameters are subject to bounds.
The lb and ub parameters can be configure to set
bounds on the parameters.

(3) Linear equalities and linear inequalities are  managed

(4) The objective function and constraints function can
provide the exact gradients as additionnal output arguments
of their function definition.

The two "SpecifyObjectiveGradient" and
"SpecifyConstraintGradient" options can be turned
on for that purpose.

(5) Efficient approximation of the sparse Hessian by finite differences taking
into account the sparsity pattern is now possible (1.0.2 feature)

(6) Hessian can now be computed in objective function
(HessianFcn="objective" option) (new 1.0.3 feature)

Features
--------

* fmincon : Solves a linearly and/or nonlinearily constrained optimization
problem.
* optimoptions : Configures and returns an updated optimization data
structure.

Authors
-------

Copyright (C) 2010 - DIGITEO - Michael Baudin
Copyright (C) 2020-2021 - Stephane Mottelet

Licence
-------

This toolbox is released under the GPL licence :

https://www.gnu.org/licenses/gpl-3.0.html

```
Files (3)
[913 bytes]
Miscellaneous file
```
```
[113.72 kB]
Source code archive
```
```
[757.20 kB]
OS-independent binary for Scilab 6.1.x
```
```
News (0)
Comments (0)
Leave a comment
You must register and log in before leaving a comment.
Login with
Email notifications
Send me email when this toolbox has changes, new files or a new release.
You must register and log in before setting up notifications.