Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs
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We present an Õ(m+n^1.5)-time randomized algorithm for maximum cardinality bipartite matching and related problems (e.g. transshipment, negative-weight shortest paths, and optimal transport) on m-edge, n-node graphs. For maximum cardinality bipartite matching on moderately dense graphs, i.e. m = Ω(n^1.5), our algorithm runs in time nearly linear in the input size and constitutes the first improvement over the classic O(m√(n))-time [Dinic 1970; Hopcroft-Karp 1971; Karzanov 1973] and Õ(n^ω)-time algorithms [Ibarra-Moran 1981] (where currently ω≈ 2.373). On sparser graphs, i.e. when m = n^9/8 + δ for any constant δ>0, our result improves upon the recent advances of [Madry 2013] and [Liu-Sidford 2020b, 2020a] which achieve an Õ(m^4/3+o(1)) runtime. We obtain these results by combining and advancing recent lines of research in interior point methods (IPMs) and dynamic graph algorithms. First, we simplify and improve the IPM of [v.d.Brand-Lee-Sidford-Song 2020], providing a general primal-dual IPM framework and new sampling-based techniques for handling infeasibility induced by approximate linear system solvers. Second, we provide a simple sublinear-time algorithm for detecting and sampling high-energy edges in electric flows on expanders and show that when combined with recent advances in dynamic expander decompositions, this yields efficient data structures for maintaining the iterates of both [v.d.Brand et al.] and our new IPMs. Combining this general machinery yields a simpler Õ(n √(m)) time algorithm for matching based on the logarithmic barrier function, and our state-of-the-art Õ(m+n^1.5) time algorithm for matching based on the [Lee-Sidford 2014] barrier (as regularized in [v.d.Brand et al.]).
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