There are also several projects on r-forge.r-project.org that deal with
optimization, including one I'm involved with that has been putting up a
number of new or reworked methods so that they can be tested, evaluated
and improved. These all deal with unconstrained or box-constrained
minimization problems (minimize -f(x) to maximize). In particular, we
have an implementation of Mike Powell's BOBYQA (derivative-free
box-constrained method using quadratic approximation) that seems quite
interesting. See package minqa in the project
http://r-forge.r-project.org/R/?group_id=395.
There is also a reworking of conjugate gradients with a rather better
automated choice of generation formula (using Dai and Yuan, 2001 ideas)
with box-constraints. It handles very large problems, often amazingly
quickly e.g., an n=5000 generalized Rosenbrock problem, with analytic
gradients, in <3 secs on an Asus Eee 900 netbook. And that is an all-R
implementation.
Caveat: all these are developmental codes. We believe they "work", but
we are trying to torture test them and are finding some situations where
they have glitches. We welcome use and comments to improve them. I
expect the same applies to other codes on r-forge.
John Nash
Message: 98
Date: Thu, 20 Aug 2009 11:08:29 -0700
From: Gaspar N??ez <nuroga...@gmail.com>
Subject: [R] optimization free software
To: r-help@r-project.org
Message-ID:
<9cd4bb290908201108x554ad8a3h520417208a330...@mail.gmail.com>
Content-Type: text/plain
Hi
i´m starting to work with free software
(with free as in freedom)
i've been working with GAMS
(General Algebraic Modeling System)
to solve static and dynamic optimization problems
and non-linear large systems of equations
i'm wondering if there is any free software
and documentation on the subject,
wether in R, Maxima, or something else
i will appreciate any help
and any references about this issue
thanks in advance
gaspar
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
