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Generalized Flow in Nearly-linear Time on Moderately Dense Graphs

Shunhua Jiang, Michael Kapralov, Lawrence Li, Aaron Sidford

2025Year
1Citations
1Top-tier citations

Abstract

In this paper we consider generalized flow problems where there is an m-edge n-node directed graph G=(V,E)G=(V, E) and each edge e∈Ee \in E has a loss factor γe>0\gamma_{e}\gt 0 governing whether the flow is increased or decreased as it crosses edge e. We provide a randomized O~((m+n1.5)⋅polylog⁡(Wδ))\widetilde{O}\left(\left(m+n^{1.5}\right) \cdot \operatorname{polylog}\left(\frac{W}{\delta}\right)\right) time algorithm for solving the generalized maximum flow and generalized minimum cost flow problems in this setting where δ\delta is the target accuracy and W is the maximum of all costs, capacities, and loss factors and their inverses. This improves upon the previous state-of-the-art O~(mn⋅log⁡2(Wδ))\widetilde{O}\left(m \sqrt{n} \cdot \log ^{2}\left(\frac{W}{\delta}\right)\right) time algorithm, obtained by combining the algorithm of [17] with techniques from [29]. To obtain this result we provide new dynamic data structures and spectral results regarding the matrices associated to generalized flows and apply them through the interior point method framework of [39].1.1The full version of this paper is available at https://arxiv.org/abs/2510.17740.

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