Re: [Help-gsl] Numerical Minimization in multidimensions without derivatives and constraints

[Philipp Basler]

Hi Gilberto, hi Benjamin

@Gilberto : I tried this before, but this lead to the problem of
artificially created local minima in which the routine ended because you
compare one legal point (one you don't want to discard) with 3 illegal
points. Did you have any problems like that in your cases?

@Benjamin : Thanks for the paper, I will read through it and see if it can
help.

Cheers,
Philipp



2015-11-11 14:57 GMT+01:00 Gilberto Noronha <address@hidden>:

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