Let $\Xi=\{1,2,\ldots,N\}^2$, and let $\nu$ be a uniform distribution on $\Xi$, namely, $\nu_{ij}:=\nu(\{(i,j)\})=\frac{1}{N^2}$, for all $1\leq i,j\leq N$. For any probability distribution $\mu:=\{\mu_{ij}\}_{1\leq i,j\leq N}$ on $\Xi$, the Wasserstein distance $W(\mu,\nu)$ is defined as
    \begin{aligned}
        &W(\mu,\nu) :=\\
        &\min_{\pi\geq0} \bigg\{\sum_{1\leq i,j,i',j' \leq N} ||(i,j)-(i',j')||\cdot \pi_{(i,j),(i',j')}:\ \sum_{i,j} \pi_{(i,j),(i',j')} = \nu_{i'j'},\forall i',j',\   \sum_{i',j'} \pi_{(i,j),(i',j')} = \mu_{ij},\ \forall i,j\bigg\},
        \end{aligned}
    where $||\cdot||$ denotes $\ell_p$-norm ($p\in[1,\infty]$).
    Consider the problem
    $$
        \max_{\mu\geq0} \bigg \{ W(\mu,\nu):\ \sum_{i}\mu_{ij} = \frac{1}{N}, \forall j,\ \sum_{j} \mu_{ij}=\frac{1}{N}, \forall i \bigg\}.
    $$
Namely, I am looking for the longest Wasserstein distance to the uniform distribution among all probability distributions with uniform marginals.
    My conjecture is that the maximizer of this problem is given by $\mu_{ij}=\frac{1}{N}{1}_{\{i=j\}}$, or $\mu_{ij}=\frac{1}{N}{1}_{\{i+j=N+1\}}$, namely, the comonotonic or countermonotonic distribution. But how to prove/disprove it? I am not sure if the correctness of this conjecture depends on $p$. Also, if it is true, could the result be extended to the multivariate case, namely, $\Xi=\{1,2,\ldots,N\}^K$ for $K>2$ ?