Generalized Flow in Nearly-linear Time on Moderately Dense Graphs
Shunhua Jiang, Michael Kapralov, Lawrence Li, Aaron Sidford
Abstract
In this paper we consider generalized flow problems where there is an m-edge n-node directed graph and each edge has a loss factor governing whether the flow is increased or decreased as it crosses edge e. We provide a randomized time algorithm for solving the generalized maximum flow and generalized minimum cost flow problems in this setting where 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 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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