Convex optimization with linear constraint?

[liu chang]

Thanks.

I made LMVM optimize over a reduced number of variables and solve the
rest from the linear equations.

On Thu, Apr 30, 2009 at 3:37 AM, David Fuentes <fuentesdt at gmail.com> wrote:
>
> Liu,
>
> Unless I'm missing something, I don't think you will directly find what
> you are looking for.  You will prob have to solve
>
>   A * vec_x = vec_b
>
> directly in your FormObjective function then use an adjoint method or
> something to compute your gradient directly
> in your FormGradient routine.
>
>
>
>
> On Thu, 30 Apr 2009, liu chang wrote:
>
>> I'm using PETSc + TAO's LMVM method for a convex optimization problem.
>> As the project progresses, it's clear that some linear constraints are
>> also needed, the problem now looks like:
>>
>> minimize f(vec_x) (f is neither linear or quadratic, but is convex)
>> subject to
>> A * vec_x = vec_b
>>
>> As LMVM does not support linear constraints, I'm looking for another
>> solver. TAO lists several functions dealing with constraints, but
>> they're all in the developer section, and in the samples linked from
>> the manual I haven't found one that's linearly constrained. Is there a
>> suitable one in TAO?
>>
>> Liu Chang
>>
>