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Parameterized Measure & Conquer for Problems with No Small Kernels

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Abstract

Measure & Conquer (M&C) is a prominent technique for analyzing exact algorithms for computationally hard problems, in particular, graph problems. It tries to balance worse and better situations within the algorithm analysis. This has led, e.g., to algorithms for Minimum Vertex Cover with a running time of \(\mathcal{O}(c^{n})\) for some constant c≈1.2, where n is the number of vertices in the graph.

Several obstacles prevent the application of this technique in parameterized algorithmics, making it rarely applied in this area. However, these difficulties can be handled in some situations. We will exemplify this with two problems related to Vertex Cover, namely Connected Vertex Cover and Edge Dominating Set. For both problems, several parameterized algorithms have been published, all based on the idea of first enumerating minimal vertex covers. Using M&C in this context will allow us to improve on the hitherto published running times. In contrast to some of the earlier suggested algorithms, ours will use polynomial space.

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  1. FB 4—Abteilung Informatik, Univ. Trier, 54286, Trier, Germany

    Daniel Binkele-Raible & Henning Fernau

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  1. Daniel Binkele-Raible
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  2. Henning Fernau
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Correspondence to Henning Fernau.

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Binkele-Raible, D., Fernau, H. Parameterized Measure & Conquer for Problems with No Small Kernels. Algorithmica 64, 189–212 (2012). https://doi.org/10.1007/s00453-011-9566-6

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