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An O (n √ n log log n) average case algorithm for the maximum induced matching problem in permutation graphs

机译:一个(n√n log log n)置换图中最大感应匹配问题的平均案例算法

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Let G = (V, E) be an undirected graph, where V is the vertex set and E is the edge set. A subset M of E is an induced matching of G if M is a matching of G and no two edges in M are joined by an edge. Finding a maximum induced matching is a NP-Hard problem on general graphs, even on bipartite graphs. However, this problem can be solved in polynomial time in some special graph classes such as weakly chordal, chordal, interval and circular-arc graphs. In this paper, we introduce a maximum induced matching algorithm in permutation graphs with O(|V |k(G) log log(|V|)) time in worst V case complexity and O(|V|√|V| log log(|V |)) time in average case complexity, where k(G) is the cardinality of the minimum clique cover set. The approach is to reduce the size of vertex set of L(G)2 without changing the cardinality of its maximum independent set. Our algorithm has better time complexity than the best known algorithm in both worst case and average case.
机译:设G =(v,e)是一个无向图,其中V是顶点集,e是边缘集。 E的子集M是G的诱导匹配,如果m是G的匹配,并且在M中没有两个边缘通过边缘连接。找到最大诱导匹配是一般图中的NP难题,即使是二分的图形。然而,在一些特殊图表类别中的多项式时间中可以解决这个问题,例如弱弦,曲线,间隔和圆弧图。在本文中,我们在最差V类复杂度和O(| v |√| v |日志日志中的o(| v | k(g)log log(| v |))时间在禁用图中引入最大诱导匹配算法。 (| v |))平均案例复杂度的时间,其中k(g)是最小集团封面集的基数。该方法是减小L(g)的顶点集的大小 2 在不改变其最大独立集的基数。我们的算法在最坏情况和平均案例中具有比最佳已知算法更好的时间复杂性。

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