[R] optim seems to be finding a local minimum

[Ben Bolker]

Hans W Borchers <hwborchers <at> googlemail.com> writes:

> 
> Ben Bolker <bbolker <at> gmail.com> writes:
> 
> > 
> >   Simulated annealing and other stochastic global optimization 
> > methods are also possible solutions, although they may or may not
> > work better than the many-starting-points solution -- it depends
> > on the problem, and pretty much everything has to be tuned.  Tabu
> > search <http://en.wikipedia.org/wiki/Tabu_search> is another possibility,
> > although I don't know much about it ...
> > 
> 
> It is known that the Excel Solver has much improved during recent years.
> Still there are slightly better points such as
> 
>     myfunc(c(0.889764228112319, 94701144.5712312))   # 334.18844
> 
> restricting the domain to [0, 1] x [0, 10^9] for an evolutionary approach,
> for instance DEoptim::DEoptim().
> 
> Finding a global optimum in 2 dimensions is not so difficult. Here the scale
> of the second variable could pose a problem as small local minima might be
> overlooked easily.
> 

  Have taken a (quick) second look at the problem, I agree that scaling
and centering are more likely to be useful solutions than stochastic
global optimization stuff.  Even using 'parscale' (see the optim
help page) may clear up the problem.

  Ben Bolker