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Computing discrete optimal transport

MathOverflow Asked by Soumya Basu on November 16, 2021

I am trying to find a combinatorial approach to solve the following optimization problem.

begin{align}
&max_{x_{ij}} C_{ij} x_{ij}, \
&text{such that},\
&sum_{j} x_{ij} leq r_i~forall i in [N],\
&sum_{i} x_{ij} leq c_j~forall j in [M],\
&x_{ij} geq 0~forall i,j,
end{align}

where the constants satisfy: $C_{ij} geq 0$, $sum_i r_i = 1$.

If $sum_j c_j = 1$ then, I think, this problem is similar to the discrete (finite) optimal transport problem.

I am not interested in the most efficient solution approach. I am interested in an approach that reveals any interesting structure of a solution if such a structure exists.

In particular, is there a greedy algorithm (after sorting the weights $C_{ij}$) that solves this problem?

One Answer

As is, the minimum is zero... If the inequalities in the first two constraints are replaced by equalities, then the problem is indeed optimal transportation. In my experience the fastest and most scalable algorithm in practice is the one based on Sinkhorn algorithm using entropic regularization. This algorithm is described in:

https://arxiv.org/abs/1306.0895

some code can be found online as well.

Answered by alesia on November 16, 2021

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