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Given a matrix $A_{n\times n} = \{a_{ij}\}$ such that $a_{ij}$ is a non-negative number and given 2 vectors $(r_1,r_2,...,r_n)$ , $(c_1,c_2,...,c_n)$ such that $r_i,c_i\in \mathbb{Z}$ define an efficient algorithm that will determine if there's a matrix $B_{n\times n} = \{b_{ij}\}$ , $b_{ij} \in \mathbb{Z}$ and

for every $1\leq i \leq n \sum b_{ij} = r_i$

for every $1\leq j \leq n \sum b_{ij} = c_j$

and

$0 \leq b_{ij} \leq a_{ij}$

Thought something with dynamic programming but didn't manage to solve it.

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    $\begingroup$ $b_{ij} \leq a_{ij}$ is where they are used. Since your constraints are all linear, do you mean an algorithm more efficient than linear programming? $\endgroup$ Jan 10, 2020 at 6:53
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    $\begingroup$ Linear programming does not help a lot here since you are looking for integers. Unless you can prove that the polytope of this problem is integral.. $\endgroup$ Jan 10, 2020 at 6:56
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    $\begingroup$ However, total unimodularity of the constraint matrix can be doable. I did not say it is not the case. Write down the LP formulation and look-up the proof of unimodularity of the incidence matrix of bipartite graphs. This should be a similar proof (if it was unimodular) $\endgroup$ Jan 10, 2020 at 7:08
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    $\begingroup$ Such matrices are known as contingency tables, and even when $a_{ij} = \infty$, counting them is #P-hard, even for only two rows! $\endgroup$ Jan 10, 2020 at 10:53
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    $\begingroup$ @narekBojikian Same issue as with perfect matchings (which is a special case). Counting is hard, determining if any exists is easy. $\endgroup$ Jan 10, 2020 at 11:23

1 Answer 1

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Hint #1:

This can be solved with network flow.

Hint #2:

Imagine $r_i$ units of flow entering the $i$th row, and $c_j$ units of flow leaving the $j$th column. Does that give you any hints how to set up the graph for a network flow problem?

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    $\begingroup$ What kind of train of thought was it that identified network flows a plausible solution? $\endgroup$
    – Sudix
    Jan 11, 2020 at 9:09
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    $\begingroup$ @Sudix, for me, I think that I tried to solve it for the special case of 0-or-1 instead of arbitrary integers; and I think I noticed that there was summing of variables and upper/lower bounds on the variables and the variables were integers, which reminded me of network flow. In retrospect, a more direct path to it would have been the comments about linear programming and total unimodularity: network flow is a special case of linear programming where total unimodularity holds. $\endgroup$
    – D.W.
    Jan 11, 2020 at 17:11

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