let $(\mathcal{X},d)$ be a Polish space. For $p\geq1$ let $\mathcal{P}_p(\mathcal{X})$ be the space of all Borel probability measures $\mu$ on $\mathcal{X}$ such that
\begin{equation} \mathbb{E}_\mu\left[ d^p(X,x_0) \right]<\infty \end{equation}
On this space we can define the Wasserstien distance (turns out to be a metric) as
\begin{equation} W_{p}(\mu,\nu) = \inf_{\pi \in \Pi(\mu,\nu)}\left(\int_{\mathcal{X}\times\mathcal{X}}d^p(x,y) \pi(dx,dy) \right)^{1/p} \end{equation}
where $\Pi(\mu,\nu)$ is the set of all probability measures on the space $\mathcal{X}\times \mathcal{X}$ with marginals $\mu$ and $\nu$.
Raginsky Sason 2014 Concentration of Measure Inequalities in Information Theory, Communications and coding, page 109, states that the inf is actually attained and therefore is a minimum. Does anyone know a proof for this? or point me in the direction of one? I cant seem to find it.
One possible reference has been given in the comments, another one is Theorem 4.1 in Villani, Optimal transport, old and new. However, the argument is simple enough to reproduce it here.
First note that the set $\Pi(\mu,\nu)$ is tight and weakly closed, hence weakly compact by Prokhorov's theorem. Moreover, since $d^p$ is the supremum of bounded continuous functions, the functional $$ I\colon \Pi(\mu,\nu)\to[0,\infty],\,I(\pi)=\int d(x,y)^p\,d\pi(x,y) $$ is weakly lower semicontinuous. Thus $I$ attains its minimum.
(More explicitly, take a minimizing sequence $(\mu_n)$. Since $\Pi(\mu,\nu)$ is weakly compact and metrizable, we can extract a weakly convergent subsequence $(\mu_{n_k})$ with limit $\mu$ in $\Pi(\mu,\nu)$. Since $I$ is weakly lower semicontinuous, we have $$ I(\mu)\leq\lim_{k\to\infty}I(\mu_{n_k}). $$ Thus $\mu$ is a minimizer.)