[R] optim seems to be finding a local minimum

Hans W Borchers hwborchers at googlemail.com
Fri Nov 11 12:19:12 CET 2011


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.

Hans Werner



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