Li Chen, Rasmus Kyng, Yang P. Liu, Richard Peng, M. Gutenberg, Sushant Sachdeva
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Almost-Linear-Time Algorithms for Maximum Flow and Minimum-Cost Flow
We present an algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with m edges and polynomially bounded integral demands, costs, and capacities in m1+o(1) time. Our algorithm builds the flow through a sequence of m1+o(1) approximate undirected minimum-ratio cycles, each of which is computed and processed in amortized mo(1) time using a new dynamic graph data structure. Our framework extends to algorithms running in m1+o(1) time for computing flows that minimize general edge-separable convex functions to high accuracy. This gives almost-linear time algorithms for several problems including entropy-regularized optimal transport, matrix scaling, p-norm flows, and p-norm isotonic regression on arbitrary directed acyclic graphs.
期刊介绍:
Communications of the ACM is the leading print and online publication for the computing and information technology fields. Read by computing''s leading professionals worldwide, Communications is recognized as the most trusted and knowledgeable source of industry information for today’s computing professional.
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