[R] Non-linearly constrained optimisation

[Stuart Nettleton]

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, <tolga.i.uzuner at jpmorgan.com> 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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