[Coin-ipopt] a question

[damien at khubla.com]

Do you mean that you have to solve another smaller problem iteratively in
order to calculate the objective?  If so, you probably will need to use
finite differences as Carl suggested to get the gradient.  Generally, an
optimisation will still solve quite well with finite differences.  The
only issue will be that it might take a while to solve, because you have
to solve for the objective for each finite difference.

One very important thing:  is your objective a continuous function in x1
and x2?  If it has lumps or bumps in it, IPOPT might struggle a bit.

Damien

> I am not sure what you mean by "get the objective function through another
> iteration". If your objective function is a particular subroutine, then it
> is certainly possible to use the Fortran interface (or Matlab if it is a
> Matlab subroutine) to define the problem. If you do not know the form of
> the objective function however, you will need to find some way to estimate
> the derivatives (at least first derivatives). This might mean using
> automatic differentiation or finite difference approximations.
>
> Hope this helps,
>
> Carl.
>
> On Fri, 31 Mar 2006 zwerhu at graduate.shu.edu.cn wrote:
>
>>
>> Hi, all
>>
>> I want to ask a question about the entering of the objective function in
>> using IPOPT. I am faced with
>> the NLP problem in which the objective function doesn't have a unique or
>> known form. In fact, I must
>> get the objective function through another iteration which can be
>> realized by a separated subroutine.
>> I mean, i must use a function "f=f(x1,x2)" to get the objective
>> function, where x1,x2 are unknown
>> variables of the NLP problem and the function "f" is an iteration which
>> doesn't have a unique form.
>> So, I wonder whether this can be realized by IPOPT Matlab interface or
>> otherwise, in the Fortran
>> interface directly. Thanks a lot!
>>
>>
>>             Best Regards,
>>             W. Zhang
>>
>>
>>
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