I have an optimization problem:
$\max_{\bf{x}} Z(\bf{x})$,
s.t. $\bf{x} \in conv(\bf{S})$
where $\bf{x}$ is an $n$-dimensional vector, $Z(\bf{x})$ is a non-linear function. The domain of $\bf{x}$ is defined by the convex hull of a set $\bf{S}$ of $m$ $n$-dimensional points. m is as large as about $2^n$.
I tried to convert the convex hull defined by the point set $\bf{S}$ into a set of linear inequalities, but it seems to be infeasible because of the dimension is not low (around 20 - 30 dimension), and the size of $\bf{S}$ is very large.
Does anyone know how to solve such an optimization program? I think maybe some approximation of $conv(\bf{S})$ would be helpful, but I don't know how to approximate it. I also thought about some branch method, but no idea on how to adopt it to this case.
Thanks!
