[Coin-ipopt] RE: Coin-ipopt Digest, Vol 19, Issue 5

Oliveira, Ivan B ivan.b.oliveira at intel.com
Thu Jun 15 12:43:05 EDT 2006

Hi Damien,

I'm a user of Ipopt and we also do a lot of nonlinear least-squares
fitting around here (including of the black-box variety as in your
case), so you might be interested in our experience.  This is an issue
that we come back to occasionally but I think we've come to one definite
conclusion (I'd be very interested in other experiences of members of
this list).

Ipopt has done an excellent job for us in solving general nonlinear
optimization problems.  But we've found that it's a bit of an unfair
comparison when we benchmark it on least-squares problems versus a
specialized algorithm like Levenberg-Marquardt *because of the data
structures involved*.  For model-fitting, the latter will (for our
benchmarks) always beat Ipopt and other IPM codes without exception, but
again - this is an unfair comparison since L-M is highly specialized for
these problems and IPMs are very general.  One place where L-M falls
short (and where Ipopt excels) is in handling nonlinear constraints, but
these usually don't show up for us in model-fitting since our parameters
are typically decoupled.  Our L-M implementation is proprietary so I'm
not familiar with free code that you can use, but I'm sure they do exist
(implementation is pretty straight forward so you can experiment
easily).  Just one suggestion if you decide to go this route - take
advantage of the data structures in the L-M implementation, otherwise it
really isn't that different from bound-constrained interior point

Now perhaps someone can actually answer your question ;) (about good
parameter choices for Ipopt) - I'd like to hear that too.  Also very
interested in others' experience re L-M vs Ipopt for LS.

Ivan B. Oliveira
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Today's Topics:

   1. Ipopt for nonlinear least-squares (damien at khubla.com)


Message: 1
Date: Wed, 14 Jun 2006 12:34:59 -0600 (MDT)
From: damien at khubla.com
Subject: [Coin-ipopt] Ipopt for nonlinear least-squares
To: coin-ipopt at list.coin-or.org
Message-ID: <39255. at mail.khubla.com>
Content-Type: text/plain;charset=iso-8859-1

Hi all,

we've been using Ipopt with good success for the last few months with a
view to replacing our commercial license for Dash.  So far it's been
great, and we're extending the use to some nonlinear least-squares
problems.  The performance is generally good, but I was wondering if
anyone has any experience finding a good set of solver parameters that
might do weel on least-squares problems.  We treat the problem to be
fitted as a black-box and use numerical differences to calculate
derivatives, and use the quasi-newton Hessian approximation.  Most
problems have between 5 and 50 variables and 10 or less constraints.



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