2023
DOI: 10.3934/math.20231085
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A central local metric dimension on acyclic and grid graph

Abstract: <abstract><p>The local metric dimension is one of many topics in graph theory with several applications. One of its applications is a new model for assigning codes to customers in delivery services. Let $ G $ be a connected graph and $ V(G) $ be a vertex set of $ G $. For an ordered set $ W = \{ x_1, x_2, \ldots, x_k\} \subseteq V(G) $, the representation of a vertex $ x $ with respect to $ W $ is $ r_G(x|W) = \{(d(x, x_1), d(x, x_2), \ldots, d(x, x_k) \} $. The set $ W $ is said to be a local metr… Show more

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Cited by 2 publications
(5 citation statements)
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“…If 𝑆 = 𝑉(𝐺) then 𝑆 is a central local metric set of 𝐺 -π‘™π‘šπ‘‘ 𝑠 (𝐺) = 𝑛 if and only if π‘‘π‘–π‘Žπ‘š(𝐺) = π‘Ÿπ‘Žπ‘‘(𝐺)Listiana, et al in[12] also find another results of the central local metric dimension of tree 𝑇 and grid graph 𝑃 𝑛 Γ— 𝑃 π‘š . Let 𝑇 be a tree with π‘‘π‘–π‘Žπ‘š(𝑇) = π‘˜, then π‘™π‘šπ‘‘ 𝑠 (𝑇) = 1, for π‘˜ even, and π‘™π‘šπ‘‘ 𝑠 (𝑇) = 2, for π‘˜ add, where π‘‘π‘–π‘Žπ‘š(𝑇) is the largest eccentricity value in 𝑇 or we called it by diameter of 𝑇.…”
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confidence: 93%
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“…If 𝑆 = 𝑉(𝐺) then 𝑆 is a central local metric set of 𝐺 -π‘™π‘šπ‘‘ 𝑠 (𝐺) = 𝑛 if and only if π‘‘π‘–π‘Žπ‘š(𝐺) = π‘Ÿπ‘Žπ‘‘(𝐺)Listiana, et al in[12] also find another results of the central local metric dimension of tree 𝑇 and grid graph 𝑃 𝑛 Γ— 𝑃 π‘š . Let 𝑇 be a tree with π‘‘π‘–π‘Žπ‘š(𝑇) = π‘˜, then π‘™π‘šπ‘‘ 𝑠 (𝑇) = 1, for π‘˜ even, and π‘™π‘šπ‘‘ 𝑠 (𝑇) = 2, for π‘˜ add, where π‘‘π‘–π‘Žπ‘š(𝑇) is the largest eccentricity value in 𝑇 or we called it by diameter of 𝑇.…”
mentioning
confidence: 93%
“…The recent research about the local metric dimension can be found in [3][4][5]. The development of local metric dimension was explored by some author, such are the local fractional metric dimension [6], the local fractional strong metric dimension [7], the local complement metric dimension [8], the local strong metric dimension [9], the dominant local metric dimension [10,11], and central local metric dimension [12].…”
Section: Introductionmentioning
confidence: 99%
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