17 research outputs found

    Maximum Skew-Symmetric Flows and Matchings

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    The maximum integer skew-symmetric flow problem (MSFP) generalizes both the maximum flow and maximum matching problems. It was introduced by Tutte in terms of self-conjugate flows in antisymmetrical digraphs. He showed that for these objects there are natural analogs of classical theoretical results on usual network flows, such as the flow decomposition, augmenting path, and max-flow min-cut theorems. We give unified and shorter proofs for those theoretical results. We then extend to MSFP the shortest augmenting path method of Edmonds and Karp and the blocking flow method of Dinits, obtaining algorithms with similar time bounds in general case. Moreover, in the cases of unit arc capacities and unit ``node capacities'' the blocking skew-symmetric flow algorithm has time bounds similar to those established in Even and Tarjan (1975) and Karzanov (1973) for Dinits' algorithm. In particular, this implies an algorithm for finding a maximum matching in a nonbipartite graph in O(nm)O(\sqrt{n}m) time, which matches the time bound for the algorithm of Micali and Vazirani. Finally, extending a clique compression technique of Feder and Motwani to particular skew-symmetric graphs, we speed up the implied maximum matching algorithm to run in O(nmlog(n2/m)/logn)O(\sqrt{n}m\log(n^2/m)/\log{n}) time, improving the best known bound for dense nonbipartite graphs. Also other theoretical and algorithmic results on skew-symmetric flows and their applications are presented.Comment: 35 pages, 3 figures, to appear in Mathematical Programming, minor stylistic corrections and shortenings to the original versio

    Linear Time Parameterized Algorithms via Skew-Symmetric Multicuts

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    A skew-symmetric graph (D=(V,A),σ)(D=(V,A),\sigma) is a directed graph DD with an involution σ\sigma on the set of vertices and arcs. In this paper, we introduce a separation problem, dd-Skew-Symmetric Multicut, where we are given a skew-symmetric graph DD, a family of T\cal T of dd-sized subsets of vertices and an integer kk. The objective is to decide if there is a set XAX\subseteq A of kk arcs such that every set JJ in the family has a vertex vv such that vv and σ(v)\sigma(v) are in different connected components of D=(V,A(Xσ(X))D'=(V,A\setminus (X\cup \sigma(X)). In this paper, we give an algorithm for this problem which runs in time O((4d)k(m+n+))O((4d)^{k}(m+n+\ell)), where mm is the number of arcs in the graph, nn the number of vertices and \ell the length of the family given in the input. Using our algorithm, we show that Almost 2-SAT has an algorithm with running time O(4kk4)O(4^kk^4\ell) and we obtain algorithms for {\sc Odd Cycle Transversal} and {\sc Edge Bipartization} which run in time O(4kk4(m+n))O(4^kk^4(m+n)) and O(4kk5(m+n))O(4^kk^5(m+n)) respectively. This resolves an open problem posed by Reed, Smith and Vetta [Operations Research Letters, 2003] and improves upon the earlier almost linear time algorithm of Kawarabayashi and Reed [SODA, 2010]. We also show that Deletion q-Horn Backdoor Set Detection is a special case of 3-Skew-Symmetric Multicut, giving us an algorithm for Deletion q-Horn Backdoor Set Detection which runs in time O(12kk5)O(12^kk^5\ell). This gives the first fixed-parameter tractable algorithm for this problem answering a question posed in a paper by a superset of the authors [STACS, 2013]. Using this result, we get an algorithm for Satisfiability which runs in time O(12kk5)O(12^kk^5\ell) where kk is the size of the smallest q-Horn deletion backdoor set, with \ell being the length of the input formula

    Navigating Central Path with Electrical Flows: from Flows to Matchings, and Back

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    We present an O~(m10/7)=O~(m1.43)\tilde{O}(m^{10/7})=\tilde{O}(m^{1.43})-time algorithm for the maximum s-t flow and the minimum s-t cut problems in directed graphs with unit capacities. This is the first improvement over the sparse-graph case of the long-standing O(mmin(m,n2/3))O(m \min(\sqrt{m},n^{2/3})) time bound due to Even and Tarjan [EvenT75]. By well-known reductions, this also establishes an O~(m10/7)\tilde{O}(m^{10/7})-time algorithm for the maximum-cardinality bipartite matching problem. That, in turn, gives an improvement over the celebrated celebrated O(mn)O(m \sqrt{n}) time bound of Hopcroft and Karp [HK73] whenever the input graph is sufficiently sparse
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