An Optimization Algorithm for Cluster Analysis.
Given a set of [N] points and distances between all points, this paper presents an algorithm for determining an optimal partition of the points into [k] mutually exclusive and exhaustive subsets or clusters according to an objective function defined on the set of all partitions. The value of the objective function for a given partition is defined as the maximum within-cluster distance in the partition. The algorithm determines an optimal partition by solving a sequence of set-covering problems, which have no more than [N] constraints and typically less than 1.5 [N] variables. 14 pp. Ref.