Research Article
On the Constant Edge Resolvability of Some Unicyclic and
Multicyclic Graphs
Dalal Alrowaili ,
1
Zohaib Zahid ,
2
Imran Siddique ,
2
Sohail Zafar,
2
Muhammad Ahsan ,
2
and Muhammad Sarwar Sindhu
3
1
Department of Mathematics, College of Science, Jouf University, P.O. Box: 2014, Sakaka, Saudi Arabia
2
Department of Mathematics, University of Management and Technology, Lahore 54770, Pakistan
3
Department of Mathematics, Virtual University of Pakistan, Lahore 54770, Pakistan
Correspondence should be addressed to Imran Siddique; imransmsrazi@gmail.com
Received 16 April 2022; Revised 23 June 2022; Accepted 24 June 2022; Published 19 July 2022
Academic Editor: Gohar Ali
Copyright © 2022 Dalal Alrowaili et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Assume that G (V(G),E(G)) is a connected graph. For a set of vertices W
E
⊆V(G), two edges g
1
,g
2
∈ E(G) are distinguished by
a vertex x
1
∈ W
E
, if d(x
1
,g
1
) ≠ d(x
1
,g
2
). W
E
is termed edge metric generator for G if any vertex of W
E
distinguishes every two
arbitrarily distinct edges of graph G. Furthermore, the edge metric dimension of G, indicated by edim(G), is the cardinality of the
smallest W
E
for G. e edge metric dimensions of the dragon, kayak paddle, cycle with chord, generalized prism, and necklace
graphs are calculated in this article.
1. Introduction and Preliminaries
A chemical compound’s structure is typically seen as a col-
lection of functional groups arranged on a substructure. e
structure is a labeled graph from a graph-theoretic outlook,
with the vertex and edge labels indicating the atom and bond
types, respectively. Functional groupings and substructure are
essentially subgraphs of the labeled graph representation from
this perspective. A collection of compounds described by the
substructure common to them is fundamentally defined by
modifying the set of functional groups and permuting their
locations. Chartrand et al. defined chemistry as the appli-
cation of graphs to illustrate the structure of diverse chemical
compounds (see [1, 2]). We employ graph principles to ex-
plain chemical structures in chemical graph theory. Chemical
compounds’ atomic structure can be presented using graphs.
Johnson has worked on the application of structure-activity
relationships by labeled graphs (see [3]).
By establishing the concept of metric dimension, Slater
was able to locate the invader in a computer network (see
[4]). Harary and Melter extended the work of Slater in [5].
Hosamani et al. studied the connection to chemical
problems in [6]. Berhe and Wang calculated topological
coindices for nanotubes and graphene sheets in [7]. Goyal
et al. focused on the new composition of graphs in [8].
Ranjini et al. investigated the applications of molecular
topology by degree sequence of graph operator in [9]. Imran
et al. investigated chemistry problems in order to create
mathematical representations of various chemical sub-
stances, with each compound having its own representation
(see [10]). Navigation can be understood within a graphical
structure in which the point robot or navigating agent moves
from vertex to vertex of a graph. e robot can find its
location by finding the distance from a fixed set of vertices
also called landmarks. ere is no idea of direction and
visibility in a graph, but the point robot can find the dis-
tances from a fixed set of landmarks (see [11]). Melter and
Tomescu worked on the metric distances used in image
processing, for example, chessboard distance and the city
block distance, and they also studied the applications to
pattern recognition problems (see [12]). Raza investigated
the chemistry application of polyphenyl and spiro chains
(see [13]). Caceres et al. described the metric dimensions of
graphs in coin weighing and mastermind games (see [14]).
Hindawi
Journal of Mathematics
Volume 2022, Article ID 6738129, 9 pages
https://doi.org/10.1155/2022/6738129