Rolf Turner <rolf.turner <at> xtra.co.nz> writes: > > On 11/11/11 08:55, Dimitri Liakhovitski wrote: > > Bert, > > that's exactly where I started. I found optim in the first paragraph > > under "General Purpose Continuous Solvers" and used bounded BFGS for a > > constrained optimization for a situation with more than 1 parameters. > > Again, not being an engineer / mathematician - would greatly > > appreciate any pointers. > > I'm no expert on numerical optimisation (though I've done quite > a bit of it in my own ham-fisted way ). Anyway, it seems to me > that the only strategy that anyone can use in seeking a global > optimum when there are multiple local optima is to use a wide > variety of starting values. Possibly placed on a (relatively coarse) > grid.
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 ... ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
