Optimal Transport in One Dimension

In this article, we explore the optimal transport problem on the real line along with some examples.

Linear Cost Example

For this example, consider the cost function $c(x,y)=L(x-y)$ along with a given linear map $A:\mathbb {R} ^{d}\rightarrow \mathbb {R}$. Moreover, if let $\gamma$ be any transport plan, then by direct computation we see that

                                                                     $\int L(x-y)d\gamma =\int L(x)d\gamma -\int L(y)d\gamma =\int L(x)d\mu -\int L(y)d\nu$

which suggests that this result only depends on the marginals of $\gamma$ (wherein $\mu$ and $\nu$ are compactly supported probability measures). In fact, in such cases, every transport plan/map is optimal.

Distance Cost Example

Consider the cost function $c(x,y)=|x-y|$ along with $\mu ={\frac {1}{2}}\lambda _{[0,2]}$ and $\nu ={\frac {1}{2}}\lambda _{[1,3]}$ wherein $\sup spt(\mu )<\inf spt(\nu )$ (where $\lambda$ is the one-dimensional Lebesgue measure). Then, for any $(x,y)\in spt(\mu )\times spt(\nu )$, notice that $c(x,y)=y-x$, which then immediately puts us in the linear cost position so any transport map/plan is also optimal for such costs.