[Top][All Lists]

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: [Help-gsl] Numerical Minimization in multidimensions without derivat

From: Gilberto Noronha
Subject: Re: [Help-gsl] Numerical Minimization in multidimensions without derivatives and constraints
Date: Wed, 11 Nov 2015 08:57:54 -0500

Hi Philipp,

One way to deal with your problem is to make your function return a very
large value when the combination of v1, v2 and v3 is not acceptable (where
"large" depends on your particular problem).
In my experience, this usually works well with the Nelder-Mead method.


On Nov 11, 2015 8:43 AM, "Philipp Basler" <address@hidden>

> Hello to all,
> I am using gsl_multimin_fminimizer_nmsimplex2 to minimize a function V (
> v1,v2,v3) in those 3 variables v1,v2,v3. The function itself has a few more
> parameters but those are constant during an Minimizationsprocess.
> Also I can not calculate any derivatives of this function.
> Normally you could just use the nmsimplex2 method to minimize this but I
> have a further constraint :
> In the process of calculating V(v1,v2,v3) there are two 4x4 real and
> symmetric Matrices from whom I need the Eigenvalues, those are calculated
> numerically with the Eigen package. All entries of those both Matrices are
> functions of v1,v2 and v3 and therefore the Eigenvalues are too.
> Now my constraint: If any of those 8 Eigenvalues is negativ I need  to
> discard this combination of v1,v2,v3 and it is not allowed to enter my
> search for a minimum.
> Is there a way to do this?
> Cheers,
> Philipp

reply via email to

[Prev in Thread] Current Thread [Next in Thread]