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Fmincon

Nonlinearily constrained multivariable optimization solver
(56 downloads for this version - 26644 downloads for all versions)
Details
Version
1.0.7
Author
Michael Baudin, Stéphane Mottelet
Maintainers
Stéphane MOTTELET
Vincent COUVERT
Category
License
Dependencies
Creation Date
January 4, 2024
Source created on
Scilab 2024.0.x
Binaries available on
Scilab 2024.0.x:
Windows 64-bit Windows 32-bit Linux 64-bit Linux 32-bit macOS
Install command
--> atomsInstall("fmincon")
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) 2020-2024 - Stephane Mottelet

Licence
-------

This toolbox is released under the GPL licence :

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

            
Files (2)
[104.25 kB]
Source code archive

[656.21 kB]
OS-independent binary for Scilab 2024.0.x

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