[R] optim seems to be finding a local minimum
bbolker at gmail.com
Fri Nov 11 14:08:15 CET 2011
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.
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