Min sum clustering with penalties

Given a complete graph G=(V,E), a weight function on its edges, and a penalty function on its vertices, the penalized k-min-sum problem is the problem of finding a partition of V to k+1 sets, S1,...,Sk+1, minimizing , where for , and p(S)=[summation operator]i[set membership, variant]Spi. Our main result is a randomized approximation scheme for the metric version of the penalized 1-min-sum problem, when the ratio between the minimal and maximal penalty is bounded. For the metric penalized k-min-sum problem where k is a constant, we offer a 2-approximation.