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The simplified Wasserstein barycenter problem, also known as the cheapest hub problem, consists in selecting one point from each of \(k\) given sets, each set consisting of \(n\) points, with the aim of minimizing the sum of distances to the barycenter of the \(k\) chosen points. This problem is also known as the cheapest hub problem. This problem is known to be NP-hard. We compute the Wasserstein barycenter by exploiting the Euclidean distance matrix structure to obtain a facially reduced doubly nonnegative, DNN, relaxation. The facial reduction provides a natural splitting for applying the symmetric alternating directions method of multipliers (sADMM) to the DNN relaxation. The sADMM method exploits structure in the subproblems to find strong upper and lower bounds. In addition, we extend the problem to allow varying \(n_j\) points for the \(j\)-th set.
The purpose of this paper is twofold. First we want to illustrate the strength of this DNN relaxation with a splitting approach. Our numerical tests then illustrate the surprising success on random problems, as we generally, efficiently, find the provable exact solution of this NP-hard problem. Comparisons with current commercial software illustrate this surprising efficiency. However, we demonstrate and prove that there is a duality gap for problems with enough multiple optimal solutions, and that this arises from problems with highly symmetrized structure.