Exact pseudopolinomial algorithms for a balanced $2$-clustering problem

We consider the strongly NP-hard problem of partitioning a set of Euclidean points into two clusters so as to minimize the sum (over both clusters) of the weighted sum of the squared intracluster distances from the elements of the clusters to their centers. The weights of sums are the sizes of the clusters. The center of one cluster is given as input, while the center of the other cluster is unknown and determined as the average value over all points in the cluster (the geometric center). The two versions of the problems are analyzed in which the cluster sizes are either parts of the input or optimization variables. We present and prove exact pseudopolynomial algorithms in the case of integer components of the input points and fixed space dimension. Bibliogr. 24.