
Revised: August 29, 2020
Published: September 20, 2021
Abstract: [Plain Text Version]
We investigate the time-complexity of the \APMF problem: Given a graph with n nodes and m edges, compute for all pairs of nodes the maximum-flow value between them. If \MF (the version with a given source-sink pair s,t) can be solved in time T(m), then O(n^2) \cdot T(m) is a trivial upper bound. But can we do better?
For directed graphs, recent results in fine-grained complexity suggest that this time bound is essentially optimal. In contrast, for undirected graphs with edge capacities, a seminal algorithm of Gomory and Hu (1961) runs in much faster time, O(n)\cdot T(m). Under the plausible assumption that \MF can be solved in near-linear time m^{1+o(1)}, this half-century old algorithm yields an nm^{1+o(1)} bound. Several other algorithms have been designed through the years, including {\tO}(mn) time for unit-capacity edges (unconditionally), but none of them break the O(mn) barrier. Meanwhile, no super-linear lower bound is known for undirected graphs.
We design the first hardness reductions for \APMF in undirected graphs, giving an essentially optimal lower bound for the node-capacities setting. For edge capacities, our efforts to prove similar lower bounds have failed, but we have discovered a surprising new algorithm that breaks the O(mn) barrier for graphs with unit-capacity edges! Assuming T(m)=m^{1+o(1)}, our algorithm runs in time m^{3/2 +o(1)} and outputs a cut-equivalent tree (similarly to the Gomory--Hu algorithm). Even with current \MF algorithms we improve the state of the art as long as m=O(n^{5/3-\varepsilon}). Finally, we explain the lack of lower bounds by proving a non-reducibility result. This result is based on a new near-linear time \tO(m) nondeterministic algorithm for constructing a cut-equivalent tree and may be of independent interest.
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A conference version of this paper appeared in the Proceedings of the 31st ACM-SIAM Symposium on Discrete Algorithms (SODA'20).