Tolga,
Your issue seems to be a common one at present. While I am relatively new
to R (and would welcome being corrected), I haven't been able to find an
existing module to parse algebraic equations and build acyclic networks
(for the objective function and each constraint) to submit to solving
routines (such as optim, BB, Patrick Burns' genopt from S Poetry, Algencan
etc). Certainly there are the components to build one, for example
topological sort packages like mathgraph and Carter Butts' network. I have
implemented acyclic networks in three major projects and so I have started
to contemplate the missing package in both R and Mathematica. At this
point I am significantly further advanced in Mathematica, building from
Eric Swanson's excellent perturbationAIM package. Yet it seems slightly
odd to me that the required functionality hasn't been developed in R up to
this point in time. Many people need this functionality, the network
algorithms have been around for forty years and there are many solvers,
even open source ones like ipopt. Of course, the "big guns" in this field
are GAMS and AMPL and it is perhaps their overwhelming presence or respect
for the developers of these packages that has led R developers to be
somewhat cautious about releasing code in this area. However, there are
already alternatives. For a quasi open source version of AMPL you could
use Dr Ampl (http://www.gerad.ca/~orban/drampl/ ) or write your problem in
GAMS or AMPL format and submit to the Neos server either directly
(http://neos.mcs.anl.gov/neos/) or by using pyneos.py
(www.gerad.ca/~orban/pyneos/pyneos.py). I really hope this gets worked out
in R at some stage!
Stuart
On Sun, 20 Jul 2008 08:10:35 +1000, <[EMAIL PROTECTED]> wrote:
Dear R Users,
I am looking for some guidance on setting up an optimisation in R with
non-linear constraints.
Here is my simple problem:
- I have a function h(inputs) whose value I would like to maximise
- the 'inputs' are subject to lower and upper bounds
- however, I have some further constraints: I would like to constrain the
values for two other separate function f(inputs) and g(inputs) to be
within
certain bounds
This means the 'inputs' must not only lie within the bounds specified by
the 'upper' and 'lower' bounds, but they must also not take on values
such
that f(inputs) and g(inputs) take on values outside defined values. h, f
and g are all non-linear.
I believe constroptim would work if f and g were linear. Alas, they are
not. Is there any other way I can achieve this in R ?
Thanks in advance,
Tolga
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