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 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 s
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
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.
Hi all,
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
vec_x[i] >= 0 for all i
A *
