Maximum Flow by Augmenting Paths in $n^2+o(1)$ Time
<|reference_start|>Maximum Flow by Augmenting Paths in $n^2+o(1)$ Time: We present a combinatorial algorithm for computing exact maximum flows in directed graphs with $n$ vertices and edge capacities from $\{1,\dots,U\}$ in $n^{2+o(1)}\log U$ time, which is almost optimal in dense graphs. Our algorithm is a novel implementation of the classical augmenting-path framework; we list augmenting paths more efficiently using a new variant of the push-relabel algorithm that uses additional edge weights to guide the algorithm, and we derive the edge weights by constructing a directed expander hierarchy.   Even in unit-capacity graphs, this breaks the long-standing $O(m\cdot\min\{\sqrt{m},n^{2/3}\})$ time bound of the previous combinatorial algorithms by Karzanov (1973) and Even and Tarjan (1975) when the graph has $m=\omega(n^{4/3})$ edges. Notably, our approach does not rely on continuous optimization nor heavy dynamic graph data structures, both of which are crucial in the recent developments that led to the almost-linear time algorithm by Chen et al. (FOCS 2022). Our running time also matches the $n^{2+o(1)}$ time bound of the independent combinatorial algorithm by Chuzhoy and Khanna (STOC 2024) for computing the maximum bipartite matching, a special case of maximum flow.<|reference_end|>
@article{bernstein2024maximum,
    title={Maximum Flow by Augmenting Paths in $n^{2+o(1)}$ Time},
    author={Aaron Bernstein, Joakim Blikstad, Thatchaphol Saranurak, Ta-Wei Tu},
    journal={arXiv preprint arXiv:2406.03648},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.03648},
    primaryClass={cs.DS}
}