Re: [Help-gsl] minimization with constraints

[Martin Jansche]

The easiest way is to smoothly transform your parameters.  E.g. if you have
a parameter y constrained to fall within [-1; 72], then define

  y = 73.0 / (1 + exp(-x)) - 1

in terms of a sigmoid function and optimize w.r.t. unconstrained x over the
real line.  Note that y goes to 72 for x->Inf and y goes to -1 for x->-Inf,
as desired.

Regards,
-- mj

On Fri, Sep 16, 2011 at 16:25, Srinivasan, Rajagopalan [ANMUS] <
address@hidden> wrote:

> Hope someone can help this "newbie" to gsl.
>
>
>
> I have a minimization problem but I cannot conceive of a way to come up
> with a gradient. Hence I am using gsl_multimin_fminimizer_nmsimplex.
> There are 5 variables in the range -1.0 - 72.0 with a desired step size
> of 0.01.
>
>
>
> Since I do have constraints (-1.0 .. 72.0) , in my cost function, I
> return GSL_NAN when the constraints are violated by the independent
> variables. I am not sure if this is the proper way to implement the
> constraints. The results so far are unsatisfactory.
>
>
>
> Couple of questions:
>
>
>
> -          What is the proper way to implement the constraints?
>
> -          I was hoping to use nmsimplex2 but does not appear to be in
> my gsl library. (My problem is of size 5 and performance is somewhat
> critical).
>
> -          Similarly how about nmsimplex2rand
>
>
>
> If there are other suggestions, I would welcome them as well.
>
>
>
> Cheers, srini
>
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