580 research outputs found

    Tight Bounds for Gomory-Hu-like Cut Counting

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    By a classical result of Gomory and Hu (1961), in every edge-weighted graph G=(V,E,w)G=(V,E,w), the minimum stst-cut values, when ranging over all s,tVs,t\in V, take at most V1|V|-1 distinct values. That is, these (V2)\binom{|V|}{2} instances exhibit redundancy factor Ω(V)\Omega(|V|). They further showed how to construct from GG a tree (V,E,w)(V,E',w') that stores all minimum stst-cut values. Motivated by this result, we obtain tight bounds for the redundancy factor of several generalizations of the minimum stst-cut problem. 1. Group-Cut: Consider the minimum (A,B)(A,B)-cut, ranging over all subsets A,BVA,B\subseteq V of given sizes A=α|A|=\alpha and B=β|B|=\beta. The redundancy factor is Ωα,β(V)\Omega_{\alpha,\beta}(|V|). 2. Multiway-Cut: Consider the minimum cut separating every two vertices of SVS\subseteq V, ranging over all subsets of a given size S=k|S|=k. The redundancy factor is Ωk(V)\Omega_{k}(|V|). 3. Multicut: Consider the minimum cut separating every demand-pair in DV×VD\subseteq V\times V, ranging over collections of D=k|D|=k demand pairs. The redundancy factor is Ωk(Vk)\Omega_{k}(|V|^k). This result is a bit surprising, as the redundancy factor is much larger than in the first two problems. A natural application of these bounds is to construct small data structures that stores all relevant cut values, like the Gomory-Hu tree. We initiate this direction by giving some upper and lower bounds.Comment: This version contains additional references to previous work (which have some overlap with our results), see Bibliographic Update 1.

    Evolutionary trees: an integer multicommodity max-flow-min-cut theorem

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    In biomathematics, the extensions of a leaf-colouration of a binary tree to the whole vertex set with minimum number of colour-changing edges are extensively studied. Our paper generalizes the problem for trees; algorithms and a Menger-type theorem are presented. The LP dual of the problem is a multicommodity flow problem, for which a max-flow-min-cut theorem holds. The problem that we solve is an instance of the NP-hard multiway cut problem

    Network Sparsification for Steiner Problems on Planar and Bounded-Genus Graphs

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    We propose polynomial-time algorithms that sparsify planar and bounded-genus graphs while preserving optimal or near-optimal solutions to Steiner problems. Our main contribution is a polynomial-time algorithm that, given an unweighted graph GG embedded on a surface of genus gg and a designated face ff bounded by a simple cycle of length kk, uncovers a set FE(G)F \subseteq E(G) of size polynomial in gg and kk that contains an optimal Steiner tree for any set of terminals that is a subset of the vertices of ff. We apply this general theorem to prove that: * given an unweighted graph GG embedded on a surface of genus gg and a terminal set SV(G)S \subseteq V(G), one can in polynomial time find a set FE(G)F \subseteq E(G) that contains an optimal Steiner tree TT for SS and that has size polynomial in gg and E(T)|E(T)|; * an analogous result holds for an optimal Steiner forest for a set SS of terminal pairs; * given an unweighted planar graph GG and a terminal set SV(G)S \subseteq V(G), one can in polynomial time find a set FE(G)F \subseteq E(G) that contains an optimal (edge) multiway cut CC separating SS and that has size polynomial in C|C|. In the language of parameterized complexity, these results imply the first polynomial kernels for Steiner Tree and Steiner Forest on planar and bounded-genus graphs (parameterized by the size of the tree and forest, respectively) and for (Edge) Multiway Cut on planar graphs (parameterized by the size of the cutset). Additionally, we obtain a weighted variant of our main contribution

    Fixed-parameter tractability of multicut parameterized by the size of the cutset

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    Given an undirected graph GG, a collection {(s1,t1),...,(sk,tk)}\{(s_1,t_1),..., (s_k,t_k)\} of pairs of vertices, and an integer pp, the Edge Multicut problem ask if there is a set SS of at most pp edges such that the removal of SS disconnects every sis_i from the corresponding tit_i. Vertex Multicut is the analogous problem where SS is a set of at most pp vertices. Our main result is that both problems can be solved in time 2O(p3)...nO(1)2^{O(p^3)}... n^{O(1)}, i.e., fixed-parameter tractable parameterized by the size pp of the cutset in the solution. By contrast, it is unlikely that an algorithm with running time of the form f(p)...nO(1)f(p)... n^{O(1)} exists for the directed version of the problem, as we show it to be W[1]-hard parameterized by the size of the cutset
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