Optimization with Linear Inequality Constraints

Is there an algo in mathdotnet Numerics that I could use to minimize a convex function of n variables f(x) with m linear inequality constraints of the type Ax<b (with A mxn matrix and b m-dim vector).
I do see one for x bounded in a box (lower and upper bounds on each x_i), but cannot see any for the more general case I am looking at.

If you are looking for a method such as the one described here, I think the answer is no. You could try using an unconstrained optimization method as part of a Penalty Method as described here.I’m sure it would clunky.