On the Structure of Optimal Transportation Plans between Discrete Measures

Abstract

In this paper, we prove a structure theorem for discrete optimal transportation plans. We show that, given any pair of discrete probability measures and a cost function, there exists an optimal transportation plan that can be expressed as the sum of two deterministic plans. As an application, we estimate the infinity-Wasserstein distance between two discrete probability measures $\mu$ and $\nu$ with the $p$-Wasserstein distance, times a constant depending on $\mu$, $\nu$, and the fixed cost function.