  Let $K$ be a full-dimensional convex subset of $\mathbb{R}^n$. We describe a
new polynomial-time Turing reduction from the weak separation problem for $K$
to the weak optimization problem for $K$ that is based on a geometric
heuristic. We compare our reduction, which relies on analytic centers, with the
standard, more general reduction.
