Multi-parameter Analysis for Local Graph Partitioning Problems: Using Greediness for Parameterization

Abstract : We study the parameterized complexity of a broad class of problems called “local graph partitioning problems” that includes the classical fixed cardinality problems as max k-vertex cover, k-densest subgraph, etc. By developing a technique that we call “greediness-for-parameterization”, we obtain fixed parameter algorithms with respect to a pair of parameters k, the size of the solution (but not its value) and Δ, the maximum degree of the input graph. In particular, greediness-for-parameterization improves asymptotic running times for these problems upon random separation (that is a special case of color coding) and is more intuitive and simple. Then, we show how these results can be easily extended for getting standard-parameterization results (i.e., with parameter the value of the optimal solution) for a well known local graph partitioning problem.
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https://hal.archives-ouvertes.fr/hal-01200582
Contributeur : Bruno Escoffier <>
Soumis le : mercredi 16 septembre 2015 - 16:44:03
Dernière modification le : lundi 10 décembre 2018 - 01:23:43

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Edouard Bonnet, Bruno Escoffier, Vangelis Paschos, Emeric Tourniaire. Multi-parameter Analysis for Local Graph Partitioning Problems: Using Greediness for Parameterization. Algorithmica, Springer Verlag, 2015, 71 (3), pp.566-580. 〈http://link.springer.com/article/10.1007/s00453-014-9920-6〉. 〈10.1007/s00453-014-9920-6〉. 〈hal-01200582〉

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