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[Help-gsl] methods for multi-dimensional minimization
From: |
Robert Jack |
Subject: |
[Help-gsl] methods for multi-dimensional minimization |
Date: |
Thu, 5 Aug 2010 03:53:26 -0700 (PDT) |
Hi...
Not sure if this is the right forum for this but here goes...
I am doing multi-dimensional minimization via conjugate gradients. According
to
the GSL reference manual, these algorithms proceed by successive line
minimizations. Once it has converged along a given direction, it chooses a new
direction in which to search.
My question is: what method is used for the line minimization? Does the user
have any control over this? From the example at
http://www.gnu.org/software/gsl/manual/html_node/Multimin-Examples.html
it looks like there is simply a step size that increases as we move downhill...
eventually we overshoot the minimum, and then it backtracks. Is this right?
I'm not sure why one would do this instead of some kind of Brent method or
something based on parabolas. Nor is it clear to me what it does during the
backtracking step. And when there is a change of direction, what step size is
used for the first step along that direction?
I have in mind a function with many minima and I am interested in how the
minimum that is found depends on the starting point used. I guess this depends
on the implementation, so it would be useful if a few more details of the
minimization algorithm were available somewhere.
Sorry if this is addressed somewhere and I missed it -- thanks for any help
Rob
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