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The complete question is as follows:

An edge of a flow network is called critical if decreasing the capacity of this edge results in a decrease in the maximum flow. Give an efficient algorithm that finds a critical edge in a network.

I believe some variation of Ford-Fulkerson would have to be used over here, however I am not too sure. Also I am a little confused by the wording of the question. What does efficient mean? In linear time i.e. $O(|V| + |E|)$?

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1 Answer 1

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By the max-flow min-cut theorem the (maximum) flow $f$ between two vertices $s$ and $t$ in the network is equal to the overall weight of the edges in a minimum $s$-$t$-cut $C$.

The means that it suffices to find a minimum $s$-$t$-cut $C$ and return any edge $e \in C$ (decreasing the capacity $e$ reduces the weight of the minimum cut and hence the flow from $s$ to $t$).

A way to find $C$ using again the relation with the maximum flow is as follows: find a maximum flow from $s$ to $t$ (using the algorithm of your choice) and let $S$ be the set of saturated edges, i.e., edges such that the flow across them matches their capacity. Choose $C$ as the set of all edges $(u,v)$ such that $u$ is reachable from $s$ and $v$ can reach $t$ in $G-S$.

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  • $\begingroup$ Can we use the residual graph to get $C$? $\endgroup$
    – Jash Shah
    Aug 14, 2022 at 17:09
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    $\begingroup$ The saturated edges of $G$ are exactly those that are not in the residual graph $G'$. Still, you cannot simply pick $C$ as all edges in $G-G'$ since this set might be too big (think for example of a graph $G$ consisting of a single path from $s$ to $t$ where all edges have the same capacity). However the set of vertices reachable from $s$ in $G-S$ is exactly the set of vertices reachable from $s$ in the residual graph $G'$. Similarly, the set of vertices that can reach $t$ in $G-S$ are exactly those that can reach $t$ in $G'$, so you can simply perform two visits on $G'$ to discover $C$. $\endgroup$
    – Steven
    Aug 14, 2022 at 21:40
  • $\begingroup$ I believe this finds the so called "bottleneck edges" -- edges if we increase their flows it would increase the max flow. In the single path with equal flow edge example, every edge is a critical edge. $\endgroup$ Feb 29 at 0:14

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