Multiset metric dimension of binomial random graphs

For a graph G = ( V , E ) and a subset R ⊆ V , we say that R is multiset resolving for G if for every pair of vertices v , w , the multisets [ d ( v , r ) : r ∈ R ] and [ d ( w , r ) : r ∈ R ] are distinct, where d ( x , y ) is the graph distance between vertices x and y . The multiset metric dimension of G is the size of a smallest set R ⊆ V that is multiset resolving (or ∞ if no such set exists). This graph parameter was introduced by Simanjuntak, Siagian, and Vitrík in 2017 Rinovia Simanjuntak et al. (2017), and has since been studied for a variety of graph families. We prove bounds which hold with high probability for the multiset metric dimension of the binomial random graph G ( n , p ) in the regime d = ( n − 1 ) p = Θ ( n x ) for fixed x ∈ ( 0,1 ) .

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Publication Details

Journal
Discrete Applied Mathematics
Published
2026-09-18
DOI
https://doi.org/10.1016/j.dam.2026.09.010
Primary Topic
Graph Labeling and Dimension Problems
Type
article
Field-Weighted Citation Impact
0.00

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article

Multiset metric dimension of binomial random graphs

Paweł Prałat, Austin Eide
Discrete Applied Mathematics
Graph Labeling and Dimension Problems
article

Multiset metric dimension of binomial random graphs

Paweł Prałat, Austin Eide
article en

Abstract

For a graph G = ( V , E ) and a subset R ⊆ V , we say that R is multiset resolving for G if for every pair of vertices v , w , the multisets [ d ( v , r ) : r ∈ R ] and [ d ( w , r ) : r ∈ R ] are distinct, where d ( x , y ) is the graph distance between vertices x and y . The multiset metric dimension of G is the size of a smallest set R ⊆ V that is multiset resolving (or ∞ if no such set exists). This graph parameter was introduced by Simanjuntak, Siagian, and Vitrík in 2017 Rinovia Simanjuntak et al. (2017), and has since been studied for a variety of graph families. We prove bounds which hold with high probability for the multiset metric dimension of the binomial random graph G ( n , p ) in the regime d = ( n − 1 ) p = Θ ( n x ) for fixed x ∈ ( 0,1 ) .

Discrete Applied MathematicsVol. 397
Toronto Metropolitan University (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 96%
Graph Labeling and Dimension Problems
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