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On optimal approximability results for computing the strong metric dimension

Authors: Bhaskar DasGupta; Nasim Mobasheri;

On optimal approximability results for computing the strong metric dimension

Abstract

The strong metric dimension of a graph was first introduced by Sebö and Tannier (Mathematics of Operations Research, 29(2), 383-393, 2004) as an alternative to the (weak) metric dimension of graphs previously introduced independently by Slater (Proc. 6th Southeastern Conference on Combinatorics, Graph Theory, and Computing, 549-559, 1975) and by Harary and Melter (Ars Combinatoria, 2, 191-195, 1976), and has since been investigated in several research papers. However, the exact worst-case computational complexity of computing the strong metric dimension has remained open beyond being NP-complete. In this communication, we show that the problem of computing the strong metric dimension of a graph of $n$ nodes admits a polynomial-time $2$-approximation, admits a $O^\ast\big(2^{\,0.287\,n}\big)$-time exact computation algorithm, admits a $O\big(1.2738^k+n\,k\big)$-time exact computation algorithm if the strong metric dimension is at most $k$, does not admit a polynomial time $(2-\varepsilon)$-approximation algorithm assuming the unique games conjecture is true, does not admit a polynomial time $(10\sqrt{5}-21-\varepsilon)$-approximation algorithm assuming P$\neq$NP, does not admit a $O^\ast\big(2^{o(n)}\big)$-time exact computation algorithm assuming the exponential time hypothesis is true, and does not admit a $O^\ast\big(n^{o(k)}\big)$-time exact computation algorithm if the strong metric dimension is at most $k$ assuming the exponential time hypothesis is true.

revised version based on reviewer comments; to appear in Discrete Applied Mathematics

Keywords

FOS: Computer and information sciences, unique games conjecture, Distance in graphs, Discrete Mathematics (cs.DM), Analysis of algorithms and problem complexity, approximability, 68Q17, 68Q25, 68R10, G.2.2, G.2.2; F.2.2, Computational Complexity (cs.CC), Computer Science - Computational Complexity, Graph algorithms (graph-theoretic aspects), minimum node cover, strong metric dimension, F.2.2, exponential time hypothesis, parameterized complexity, Computer Science - Discrete Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Top 10%
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