[SciPy-user] constrained optimization

[A.J. Rossini]

Travis Oliphant <oliphant.travis at ieee.org> writes:

> John Hunter wrote:
>> I need to do a bounded nonlinear minimization problem.  I've been
>> using scipy.optimize.leastsq, and apply artificial bounds by increasing
>> the error when then params escape their bounds, but this isn't working
>> well enough.
>> I see that scipy.optimize.anneal has bounds, but am wondering if
>> there
>> are any bounded optimizers available for general nonlinear least
>> squares, like a bounded Lev-Marq alogirithm.
>
> My brief investigations into this matter did not turn anything up that
> was open source.  It would appear that bounded optimizers are a
> current research area and the good algorithms are somewhat closely
> guarded.

One possibility might be Will Naylor's library (wnlib) which had one
based on a conjugate gradient approach.

I can't vouch (good/bad) on code quality/performance, though; would be
interested in others experiences

http://www.willnaylor.com/wnlib.html

best,
-tony

-- 
A.J. Rossini rossini at u.washington.edu http://software.biostat.washington.edu/ 
Biostatistics, U Washington and Fred Hutchinson Cancer Research Center

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