Convex optimization with linear constraint?

[liu chang]

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 * 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? If so how should I use it? If not can anyone
recommend an optimization library for me? It doesn't need to be
distributed like PETSc.

Any suggestion is greatly appreciated.

Liu Chang