We work over $\mathbb{R}^N$. Let $\mathbf{P}_1$ denote the hyperplane constructed using $N$ points, each of which is on a different axis (there are $N$ axes). We denote by $\mathbf{P}_2$ the convex hull of a set of $M$ points, but we don't know which of these points are the vertices. I am trying to find the minimum distance between $\mathbf{P}_1$, which can also be seen as a convex hull, and $\mathbf{P}_2$.
My approach is to define an optimization problem having an acceptable computational complexity. My question is how can we define such a problem ?