[R] Increasing precision of rgenoud solutions

[Paul Smith]

Thanks a lot, Jasjeet. That is it.

Paul


On 5/10/07, Jasjeet Singh Sekhon <sekhon at berkeley.edu> wrote:
>
> Hi Paul,
>
> I see.  You want to increase the population size (pop.size)
> option---of lesser importance are the max.generations,
> wait.generations and P9 options.  For more details, see
> http://sekhon.berkeley.edu/papers/rgenoudJSS.pdf.
>
> For example, if I run
>
> a <- genoud(myfunc, nvars=2,
>             Domains=rbind(c(0,1),c(0,1)),max=TRUE,boundary.enforcement=2,solution.tolerance=0.0000001,
>             pop.size=6000, P9=50)
>
> options("digits"=12)
>
> I obtain:
>
> #approx analytical solution
> sum(c(0.707106781186548,0.707106781186548))
> [1] 1.41421356237
>
> #genoud solution
> #a$value
> [1] 1.41421344205
>
> #difference
> a$value-sum(c(0.707106781186548,0.707106781186548))
>
> [1] -2.91195978441e-09
>
> If that's not enough precision, increase the options (and the
> run-time).  This would be faster with analytical derivatives.
>
> Cheers,
> Jas.
>
> =======================================
> Jasjeet S. Sekhon
>
> Associate Professor
> Travers Department of Political Science
> Survey Research Center
> UC Berkeley
>
> http://sekhon.berkeley.edu/
> V: 510-642-9974  F: 617-507-5524
> =======================================
>
>
>
> Paul Smith writes:
> >Thanks, Jasjeet, for your reply, but maybe I was not enough clear.
> >
> >The analytical solution for the optimization problem is the pair
> >
> >(sqrt(2)/2,sqrt(2)/2),
> >
> >which, approximately, is
> >
> >(0.707106781186548,0.707106781186548).
> >
> >The solution provided by rgenoud, with
> >
> >solution.tolerance=0.000000001
> >
> >was
> >
> >$par
> >[1] 0.7090278 0.7051806
> >
> >which is not very precise comparing with the values of the
> >(analytical) solution. Is it possible to increase the degree of
> >closeness of the rgenoud solutions with the analytical ones?
> >
> >Paul
> >
> >Paul Smith writes:
> > > Dear All
> > >
> > > I am using rgenoud to solve the following maximization problem:
> > >
> > > myfunc <- function(x) {
> > >   x1 <- x[1]
> > >   x2 <- x[2]
> > >   if (x1^2+x2^2 > 1)
> > >     return(-9999999)
> > >   else x1+x2
> > > }
> > >
> > > genoud(myfunc, nvars=2,
> > > Domains=rbind(c(0,1),c(0,1)),max=TRUE,boundary.enforcement=2,solution.tolerance=0.000001)
> > >
> > > How can one increase the precision of the solution
> > >
> > > $par
> > > [1] 0.7072442 0.7069694
> > >
> > > ?
> > >
> > > I have tried solution.tolerance but without a significant improvement.
> > >
> > > Any ideas?
> > >
> > > Thanks in advance,
> > >
> > > Paul
> > >
> > >
> >
>