22,602 research outputs found

    Minimum cycle and homology bases of surface embedded graphs

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    We study the problems of finding a minimum cycle basis (a minimum weight set of cycles that form a basis for the cycle space) and a minimum homology basis (a minimum weight set of cycles that generates the 11-dimensional (Z2\mathbb{Z}_2)-homology classes) of an undirected graph embedded on a surface. The problems are closely related, because the minimum cycle basis of a graph contains its minimum homology basis, and the minimum homology basis of the 11-skeleton of any graph is exactly its minimum cycle basis. For the minimum cycle basis problem, we give a deterministic O(nω+22gn2+m)O(n^\omega+2^{2g}n^2+m)-time algorithm for graphs embedded on an orientable surface of genus gg. The best known existing algorithms for surface embedded graphs are those for general graphs: an O(mω)O(m^\omega) time Monte Carlo algorithm and a deterministic O(nm2/log⁥n+n2m)O(nm^2/\log n + n^2 m) time algorithm. For the minimum homology basis problem, we give a deterministic O((g+b)3nlog⁥n+m)O((g+b)^3 n \log n + m)-time algorithm for graphs embedded on an orientable or non-orientable surface of genus gg with bb boundary components, assuming shortest paths are unique, improving on existing algorithms for many values of gg and nn. The assumption of unique shortest paths can be avoided with high probability using randomization or deterministically by increasing the running time of the homology basis algorithm by a factor of O(log⁥n)O(\log n).Comment: A preliminary version of this work was presented at the 32nd Annual International Symposium on Computational Geometr

    Convex Cycle Bases

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    Convex cycles play a role e.g. in the context of product graphs. We introduce convex cycle bases and describe a polynomial-time algorithm that recognizes whether a given graph has a convex cycle basis and provides an explicit construction in the positive case. Relations between convex cycles bases and other types of cycles bases are discussed. In particular we show that if G has a unique minimal cycle bases, this basis is convex. Furthermore, we characterize a class of graphs with convex cycles bases that includes partial cubes and hence median graphs. (authors' abstract)Series: Research Report Series / Department of Statistics and Mathematic

    On Minimum Average Stretch Spanning Trees in Polygonal 2-trees

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    A spanning tree of an unweighted graph is a minimum average stretch spanning tree if it minimizes the ratio of sum of the distances in the tree between the end vertices of the graph edges and the number of graph edges. We consider the problem of computing a minimum average stretch spanning tree in polygonal 2-trees, a super class of 2-connected outerplanar graphs. For a polygonal 2-tree on nn vertices, we present an algorithm to compute a minimum average stretch spanning tree in O(nlog⁥n)O(n \log n) time. This algorithm also finds a minimum fundamental cycle basis in polygonal 2-trees.Comment: 17 pages, 12 figure

    The Salesman's Improved Tours for Fundamental Classes

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    Finding the exact integrality gap α\alpha for the LP relaxation of the metric Travelling Salesman Problem (TSP) has been an open problem for over thirty years, with little progress made. It is known that 4/3≀α≀3/24/3 \leq \alpha \leq 3/2, and a famous conjecture states α=4/3\alpha = 4/3. For this problem, essentially two "fundamental" classes of instances have been proposed. This fundamental property means that in order to show that the integrality gap is at most ρ\rho for all instances of metric TSP, it is sufficient to show it only for the instances in the fundamental class. However, despite the importance and the simplicity of such classes, no apparent effort has been deployed for improving the integrality gap bounds for them. In this paper we take a natural first step in this endeavour, and consider the 1/21/2-integer points of one such class. We successfully improve the upper bound for the integrality gap from 3/23/2 to 10/710/7 for a superclass of these points, as well as prove a lower bound of 4/34/3 for the superclass. Our methods involve innovative applications of tools from combinatorial optimization which have the potential to be more broadly applied

    Fast Computation of Small Cuts via Cycle Space Sampling

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    We describe a new sampling-based method to determine cuts in an undirected graph. For a graph (V, E), its cycle space is the family of all subsets of E that have even degree at each vertex. We prove that with high probability, sampling the cycle space identifies the cuts of a graph. This leads to simple new linear-time sequential algorithms for finding all cut edges and cut pairs (a set of 2 edges that form a cut) of a graph. In the model of distributed computing in a graph G=(V, E) with O(log V)-bit messages, our approach yields faster algorithms for several problems. The diameter of G is denoted by Diam, and the maximum degree by Delta. We obtain simple O(Diam)-time distributed algorithms to find all cut edges, 2-edge-connected components, and cut pairs, matching or improving upon previous time bounds. Under natural conditions these new algorithms are universally optimal --- i.e. a Omega(Diam)-time lower bound holds on every graph. We obtain a O(Diam+Delta/log V)-time distributed algorithm for finding cut vertices; this is faster than the best previous algorithm when Delta, Diam = O(sqrt(V)). A simple extension of our work yields the first distributed algorithm with sub-linear time for 3-edge-connected components. The basic distributed algorithms are Monte Carlo, but they can be made Las Vegas without increasing the asymptotic complexity. In the model of parallel computing on the EREW PRAM our approach yields a simple algorithm with optimal time complexity O(log V) for finding cut pairs and 3-edge-connected components.Comment: Previous version appeared in Proc. 35th ICALP, pages 145--160, 200
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