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Re: multidimensional optimization


We don't have a design document for multidimensional optimization, so
this list is the right place to discuss the design.

Here is the general plan that I have followed in the past...

The starting point is to list and classify all the existing
techniques, and determine an appropriate API for each class of
problem.

(There is a nice little summary of minimisation techniques in the book
"Numerical Computation (Volume 2)" by Ueberhuber.)

Each API should aim to support a variety of different interchangeable
algorithms within the problem class. For iterative algorithms we have
adopted an initialise-iterate-test structure by convention.

The 1-d root finding and minimisation directories give the general
idea.

Fabrice Rossi writes:
 > Hi All.
 >  I've read in "The Plan" that multidimensional optimization is
 > considered as one of the priority one targets for GSL future. I'm
 > working in the field of artifical neural networks and I need to
 > implement simple multilayer perceptrons in order to test a new
 > method I've designed.
 >  As I need multidimensional optimization to train my neural
 > networks, I'll be pleased to help coding traditionnal algorithms in
 > GSL (I've already implemented nn training algorithm in both C and
 > C++). If I'm correct the work as not started on this part.
 >  I would like to know if there are any design documents about
 > multidimensional optimization implementation in GSL and if the
 > mailing list might be a correct place to discuss about this design.
 >  Fabrice Rossi

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