[SciPy-dev] ticket 390 ("scipy.optimize.fmin_bfgs fails without warning", Reported by: ycopin)
Wed Jul 18 07:51:26 CDT 2007
Thank you, however, there are no needs to read anything for to
understand that classic bfgs is for local minimum only. Even 2 first
lines of your url already says
/BFGS method/The unconstrained optimization problem is to minimize a
real-valued function of variables. That is, to find a *local* minimizer,
i.e. a point such that ...
We can talk about global convergence of some bfgs modifications ONLY if
some assumptions (usually very strong) about objfunc are known, for
example f is Lipschitz twice continuously differentiable.
BFGS uses gradient and is intended for medium and rather large scale
objfunc, it's already enough for to understand that it's for local
minimum only (w/o any other assumptions about f, any global solver is
capable only for small-scale funcs, nVars up to 10-12).
BTW in ticket 344 you were right about the bug, but on the other hand if
you intend to find global minimum then you also use incorrect solver(s)
(fmin_cg and fmin_powell) to your objfunc, that has 2 global
(x=1.32733353855 and x=-1.32733353855, because your objfunc d(x) is
zero-symmetric), non-convex and lots of local minima.
Nils Wagner wrote:
> Alan G Isaac wrote:
>> On Wed, 18 Jul 2007, dmitrey apparently wrote:
>>> So, since user has sin(const/b), the func is
>>> 1) non-convex
>>> 2) has lots of local minimum
>>> So I guess it's nothing special that sometimes fmin_bfgs yields other
>>> solution (from other start points) than the one the user mentioned.
>>> So I think the ticket should be closed.
>> Yannick, can you comment please? Nils too.
>> I read the ticket as concerning not the particular point
>> found but that stopping was away from a local
>> minimum without warning, even though the Jacobian was ok.
>> Alan Isaac
>> PS Dmitrey is working on these tickets this week and needs
>> very quick feedback.
>> Scipy-dev mailing list
> Hi Alan,
> I am not an expert wrt. optimization.
> The following link might be useful to gain further insight into local
> and global
> convergence properties of BFGS.
> Scipy-dev mailing list
More information about the Scipy-dev