A golden ratio parameterized algorithm for Cluster Editing. Böcker, S. J Discrete Algorithms, 16:79–89, 2012.
doi  abstract   bibtex   
The Cluster Editing problem asks to transform a graph by at most k edge modifications into a disjoint union of cliques. The problem is NP-complete, but several parameterized algorithms are known. We present a novel search tree algorithm for the problem, which improves running time from O*(1.76^k) to O*(1.62^k). In detail, we can show that we can always branch with branching vector (2,1) or better, resulting in the golden ratio as the base of the search tree size. Our algorithm uses a well-known transformation to the integer-weighted counterpart of the problem. To achieve our result, we combine three techniques: First, we show that zero-edges in the graph enforce structural features that allow us to branch more efficiently. Second, by repeatedly branching we can isolate vertices, releasing costs. Finally, we use a known characterization of graphs with few conflicts.
@Article{boecker12golden,
  author    = {Sebastian B\"ocker},
  title     = {A golden ratio parameterized algorithm for Cluster Editing},
  journal   = {J Discrete Algorithms},
  year      = {2012},
  volume    = {16},
  pages     = {79--89},
  abstract  = {The Cluster Editing problem asks to transform a graph by at most k edge modifications into a disjoint union of cliques. The problem is NP-complete, but several parameterized algorithms are known. We present a novel search tree algorithm for the problem, which improves running time from O*(1.76^k) to O*(1.62^k). In detail, we can show that we can always branch with branching vector (2,1) or better, resulting in the golden ratio as the base of the search tree size. Our algorithm uses a well-known transformation to the integer-weighted counterpart of the problem. To achieve our result, we combine three techniques: First, we show that zero-edges in the graph enforce structural features that allow us to branch more efficiently. Second, by repeatedly branching we can isolate vertices, releasing costs. Finally, we use a known characterization of graphs with few conflicts.},
  doi       = {10.1016/j.jda.2012.04.005},
  file      = {Boecker_GoldenRatioParameterizedAlgorithm_JDiscreteAlgorithms_2012_preprint.pdf:2012/Boecker_GoldenRatioParameterizedAlgorithm_JDiscreteAlgorithms_2012_preprint.pdf:PDF},
  keywords  = {jena; linkpdf; PABI; fpt; cluster editing},
  owner     = {Sebastian},
  timestamp = {2011.01.29},
}

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