More specifically, using mixed integer linear programming.<p>I've never seen an MILP used this way, to characterize the entire feasible set (or "solution pool"). Is this one of the fastest ways to do so? The usual branch-and-bound type methods won't apply, since the solver has to enumerate every feasible solution.<p>The CPLEX docs (<a href="https://www.ibm.com/docs/en/icos/22.1.1?topic=solutions-how-enumerate-all" rel="nofollow noreferrer">https://www.ibm.com/docs/en/icos/22.1.1?topic=solutions-how-...</a>) mention the potential slowness and also the numerical issues the author faces in the article.