A mixed-integer programming approach to the clustering problem

A mixed-integer programing formulation for clustering is proposed, one that encompasses a wider range of objectives--and side conditions--than standard clustering approaches. The flexibility of the formulation is demonstrated in diagrams of sample problems and solutions. Preliminary computational tests in a practical setting confirm the usefulness of the formulation.