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On the Parameterized and Approximation Hardness of Metric Dimension
38
Citations
11
References
2013
Year
Unknown Venue
EngineeringComputational ComplexityApproximation HardnessStructural Graph TheoryParameterized AlgorithmExtremal CombinatoricsGomory-chvátal TheoryDiscrete MathematicsCombinatorial OptimizationApproximation TheoryGraph GComputer ScienceMetric DimensionGraph MinorGraph TheoryShortest PathParameterized ComplexityMetric Graph TheoryExtremal Graph Theory
The NP-hard Metric Dimension problem is to decide for a given graph G and a positive integer k whether there is a vertex subset of size at most k that separates all vertex pairs in G. Herein, a vertex v separates a pair {u, w} if the distance (length of a shortest path) between v and u is different from the distance of v and w. We give a polynomial-time computable reduction from the Bipartite Dominating Set problem to Metric Dimension on maximum degree three graphs such that there is a one-to-one correspondence between the solution sets of both problems. There are two main consequences of this: First, it proves that Metric Dimension on maximum degree three graphs is W[2]-hard with respect to the parameter k. This answers an open question concerning the parameterized complexity of Metric Dimension posed by Lokshtanov [Dagstuhl seminar, 2009] and also by Diaz et al. [ESA'12]. Additionally, it implies that a trivial n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O(k)</sup> -time algorithm cannot be improved to an n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o(k)</sup> -time algorithm, unless the assumption FPT≠W[1] fails. Second, as Bipartite Dominating Set is inapproximable within o(log n), it follows that Metric Dimension on maximum degree three graphs is also inapproximable by a factor of o(log n), unless NP=P. This strengthens the result of Hauptmann et al. [JDA'12] who proved APX-hardness on bounded-degree graphs.
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