Abstract
The exploration of edge metric dimension and its applications has been an ongoing discussion, particularly in the context of nanosheet graphs formed from the octagonal grid. Edge metric dimension is a concept that involves uniquely identifying the entire edge set of a structure with a selected subset from the vertex set, known as the edge resolving set. Let's consider two distinct edge resolving sets, denoted as and , where . In such instances, it indicates that the graph G possesses a double-edge resolving set. This implies the existence of two different subsets of the vertex set, each capable of uniquely identifying the entire edge set of the graph. In this article, we delve into the edge metric dimension of nanosheet graphs derived from the octagonal grid. Additionally, we initiate a discussion on the exchange property associated with the edge resolving set. The exchange property holds significance in the study of resolving sets, playing a crucial role in comprehending the structure and properties of the underlying graph.
Keywords: Edge resolving set, Edge metric dimension, Nanosheet, Octogonal grid, Exchange property edge resolving set
1. Introduction
Chemical graph theory is a useful tool for explaining chemical structures and presenting molecular representations mathematically. It is essential for explaining the structural properties of different kinds of materials, including as molecules, polymers, processes, crystals, and clusters. In order to show how mathematical ideas and methods can be used to chemistry, this field of study has expanded to include the most recent advancements and discoveries in mathematical models of chemical conditions [1]. Simplifying and building intricate chemical structures that could be difficult to comprehend in their original form is one noteworthy use of chemical graph theory. Researchers can learn more about the characteristics and actions of various chemical substances by using mathematical representations.
In materials science, octagonal grid-derived nanosheets are crucial and well-researched materials [2], [3], [4]. Because of their thinness, these nanostructures are valued in a variety of sectors, including nanotechnology and medicine. These structures are resolved and their vertex-based metric dimensions are determined [5]. This study advances our knowledge of the special qualities and possible uses of nanosheet chemicals. Further insights and discussions regarding mathematical elements of graph theory and chemistry can be gained from recent works [6], [7]. These papers demonstrate how mathematical chemistry is interdisciplinary and how mathematical models and methods improve our understanding of chemical structures and events.
In graph theory, the idea of an edge-resolving set is essential, especially when discussing chemical structures. A subset of a graph vertex set known as an edge resolving set, or , is responsible for uniquely identifying each edge in G by measuring the distances between the vertices in and the edges. This distinctive identification highlights the importance of this idea in chemical graph theory by adding to a distinctive representation of chemical structures [8]. The edge metric dimension is defined as the cardinality of the smallest edge resolving set [9], [10], [11]. This metric gives an indication of how well a collection of vertices resolves the graph's edges. The idea of a locating set, which is a precursor to the metric dimension, was introduced by Slater in 1975 [12] and later termed the metric dimension by Harary in 1976 [13]. The concept of edge metric dimension is independently introduced by Aleksander Kelenc [14]. The exchange property is a significant characteristic associated with resolving sets. It states that for any two minimal resolving sets in a graph, there exists a vertex u in and a vertex v in such that replacing u with v in such that results in another minimal resolving set. This exchange property, explored in this study, contributes to the understanding of the set resolution property of graphs [15].
In daily life, the edge metric dimension is used in many ways, which has inspired researchers and has been thoroughly researched. They were specifically employed in pharmaceutical research to identify patterns resembling those of various drugs [16]. Other uses for the edge metric dimension include robot navigation [17], weighing issues, Sonar, coastguard Loran, communications networks [18], image analysis, facility layout issues, and sonar [19], combinatorial optimization [20], [21], and coding and decoding of mastermind games [22]. For more information on the physical and chemical characteristics of the metric dimension, see [23], [24], [25].
Due to the vast range of applications for which it is put, the concept of edge metric dimension is usually used to solve complex problems. Resolving set and exchange property in nanotube discussed in [26]. The metric dimensions of various chemical structures have been studied in numerous articles. Metric dimensions have many applications in chemistry Hollow coronoid's Edge Metric dimension is discussed in [27]. Edge metric dimension and barycentric partition of the Cayley graph were both examined in [28]. In [29], contains groundbreaking work on the edge metric dimension. The structure of curved polytopes is discussed in [30]. Our study can benefit from understanding some fundamental definitions of distance, resolving set, and metric dimension. The concept of metric dimension is applied to resolve a wide range of challenging issues due to its diversity. For variables relating to the resolvability of different chemical graphs, we refer to [31], [32]. For more in-depth exploration of the chemical and physical properties of octagonal grids, please consult the works cited in [33], [34], [35].
Definition 1.1
In a simple, undirected graph G, the distance, also known as a geodesic, between any two vertices is equal to the length of the shortest path in G between those vertices. The symbol for it is ζ(. A collection of edges and vertices are represented by E(G) and V(G) respectively.
Definition 1.2
The edge metric dimension of G, represented by , is the least cardinality of an edge resolving set, operating as an edge metric basis for G. Let an ordered set of the edges of G (vertices of line graph ) and , then impression of n about to is the k-tuple , is called edge resolving set if is distinct for all .
Theorem 1.3
Let be a sunlet graph. Then the edge metric dimension for the sunlet graph is denoted by and changes with even and odd values of n have the following edge metric dimension
Here E shows the even number and O is used for the odd number and is the sunlet graph.
Theorem 1.4
Let be the family of the prism graph. Then .
We have discussed the edge metric dimension of the nanosheet graphs generated from the octagonal grid in this post. We have also spoken about this new structure's exchange characteristics. There is no exchange property stated for such chemical networks or structures in the literature. For the first time, we have attempted to start a conversation on the edge resolving the set's exchange attribute.
2. Construction of nanosheet derived by octagonal grid
The thickness of the 2D nanostructures is what makes them so significant. They are employed in nanotechnology, nanomedicine, and gene transfer. Their thicknesses range from 1 to 100 nm because of their incredibly thin architectures, nanosheets differ from their bulk counterparts. They are best suited for the administration of various medications along with therapeutic DNA and RNAs due to the high surface-to-volume ratio. Fluid mechanics also use nanosheets. In fluid mechanics, there are numerous papers on nanosheets. Some scholars in the field of graph theory discover topological indices of this nanosheet driven by the octagonal grid, such as the Schultz and Wiener indices by [36], the connective eccentric index, the eccentric connective index, and the eccentric Zagreb index, which was financed by [37]. However, we seek to identify the resolving parameter of this sheet.
In Fig. 1, the color scheme is as follows: red color is used for edges with endpoints of degree 2 and 3, blue color indicates edges with endpoints of degree 2, and black is assigned to edges with endpoints of degree 3. Green color represents vertices of degree 2, while the black-colored vertex has a degree of 3. Double-colored vertices, such as and , are part of the resolving set, marked in green and red due to their degree 2. Let h and v denote the horizontal and vertical numbers of , where . The number of vertices with degree 2 is , and the number of vertices with degree 3 is . The order of is , and the size of is .
Figure 1.
Generalize Nanosheet.
In labeling, two parameters, , and two indices, , are employed. changes 4 time with h, and two time varies with v. In addition, the labeling described above in vertex and edge sets is displayed in Fig. 1 and is used in our primary findings. Furthermore, the margins are labeled as , and . The vertex and edge set of the nanosheet is respectively.
3. Double edge resolving sets of nanosheet derived from octagonal grid
Theorem 3.1
Ifis an octagonal nanosheet with, then double edge resolving sets of cardinality 2 exist.
Proof
To prove the double edge resolving set for nanosheet, we define two sets and . Now we want to show that and both are edge resolving sets for nanosheet. The prove of is in Theorem 3.2 and prove of present in Theorem 3.3 □
3.1. is a resolving set of nanosheet
Theorem 3.2
Ifis a nanosheet with, thenis a minimal edge-resolving set of cardinality 2.
Proof
To prove that is a minimal edge-resolving set for , we will show that is an edge-resolving set. Let e be an arbitrary edge in , and let d denote the distance between e and the vertices in . We will show that this representation is unique. Consider the edges adjacent to the vertices in . The vertices and are of degree 2, so they are connected to two edges each. Specifically, is connected to edges and , while is connected to edges and . Now, observe the structure of the nanosheet. The vertices and are the only vertices of degree 2, and they are part of the outer cycle of the nanosheet. All other vertices, including those in the inner cycles, have degree 3. Since the nanosheet is constructed in an octagonal pattern, there are no other vertices of degree 2 in the outer cycle. Therefore, any edge e must be incident on or or both. Now, consider the distances between the edge e and the vertices in . Without loss of generality, let e be incident on . The distances are as follows: is the distance along the cycle containing . is the distance along the outer cycle to and then back to . Since the nanosheet is constructed with an octagonal pattern, the distances along these cycles will be distinct. Therefore, the representation is unique, and is an edge-resolving set. Since is an edge-resolving set, and it has cardinality 2, it is a minimal edge-resolving set for . The representation for present in Table 1
Generalized Results
Now, considering the generalized values of h and v where , the distinct representation of all vertices from is presented below. The formulas for distances across all edges in the octagonal nanosheet reveal that the minimal edge resolving set possesses a cardinality of two, as each distance is distinct. Let , , and . Or .
where
where
So the formula explains the uniques representations of edges with respect to the R. Let , , and
where
where
Let , , and
where
where
Let and be two any arbitrary vertices on nanosheet , and d use for distance. Suppose WLOG represents without loss of generality and let
Case I: When and then further three cases arise.
subcase1: If , then WLOG say that then because where so .
subcase2: If , then WLOG say that then because where so .
subcase3: If , then WLOG say that , then because so .
Case II: When and then also three cases more.
subcase1: If , then WLOG say that then because where so .
subcase2: If , then WLOG say that then because where so .
subcase3: If , then WLOG say that , then because so .
Case III: When and then further four cases arise.
subcase1: If , then because least is comparable to so .
subcase2: If , then WLOG say that then because least is comparable to so .
subcase3: If , then WLOG say that then because least is comparable to so .
Case 4: If , then WLOG say that , then because least is comparable to so .
When , the positions of and where then .
One can note from the Fig. 2 when then also then .
we discuss all cases where while
or , No, any possibility showing two representations are the same. So has cardinality 2.
Contrary Case
In all the above discussion we have proven that the cardinality of the resolving set is less or equal to 2. Now we want to show that the cardinality of the resolving set is not greater than 2.
contradiction the edge resolving set of is possible if and only if it is a path graph, and also it contains cycle and the minimum edge metric dimension 2 if a graph contains a cycle so the minimal edge resolving a set of cardinality 1 is not possible.
→ the minimal edge resolving set of . Hence prove that the minimal edge resolving set of has cardinality 2. □
Table 1.
Edge representation of Fig. 2.
| Edges | e1,1 | e1,2 | e1,3 | c1,1 | c1,2 | |||
| (0,2) | (1,1) | (2,0) | (1,3) | (2,2) | (3,1) | (0,4) | (4,0) | |
Figure 2.

Octagone for sheet.
3.2. is also edge resolving set of nanosheet
In this section, we discuss the other edge resolving set of nanosheet derived by octagonal grid.
3.2.1. Construction of nanosheet derived by octagonal grid
Red color is used in Fig. 3 to indicate edges with endpoints of degrees 2 and 3. For edges with degree 2 endpoints, the color is blue, and for edges with degree 3 endpoints, the color is black. For vertices of degree two, the color green is utilized, and for vertices of degree three, the color black. The vertices with double colors, such as and , are crucial points in the resolving set. These vertices are marked with green and red colors, indicating a degree of 2, and they are essential members of the resolving set. Let h and v represent the horizontal and vertical numbers in the context of , where . The count of vertices with a degree of 2 is , and the count of nodes with a degree of 3 is . The order of is given by , and the size of is yet to be determined. . The edges are labeled as , and . The size and order of the graph are the same as the above graph.
Theorem 3.3
Letbe a nanosheet withthen an other edge resolving setof cardinality 2 exist.
Proof
To prove that the other edge resolving set of has minimum cardinality is also 2. Now to prove this claim we will follow the definition of edge resolving set. The edge resolving set is defined as . Given below are the unique representation of all edges of for . The representation for present in Table 2
Generalized Results
Now, considering the generalized values of h and v where , the distinct representation of all vertices from is presented below. The formulas for distances across all edges in the octagonal nanosheet reveal that the minimal edge resolving set possesses a cardinality of two, as each distance is distinct. Let , , and
where
where
Let , , and
where
where
Let , , and
where
where
Let and be two any arbitrary vertices on nanosheet . Let
Case I: When and then three more Subcases emerge.
Subcase 1: If , then WLOG (w.l.o.g) implication would be that , because where so .
Subcase 2: If , then WLOG say implication would be that , because where so .
Subcase 3: If , then WLOG say , implication would be that , because so .
Case II: When and then also three Subcases more.
Subcase 1: If , then WLOG say implication would be that , because where so .
Subcase 2: If , then WLOG say implication would be that , because where so .
Subcase 3: If , then WLOG say , implication would be that , because so .
Case III: When and then four more Subcases emerge.
Subcase 1: If , implication would be that , because least is comparable to so .
Subcase 2: If , then WLOG say implication would be that , because least is comparable to so .
Subcase 3: If , then WLOG say implication would be that , because least is comparable to so .
Subcase 4: If , then WLOG say , implication would be that , because least is comparable to so .
When , the positions of and where , then .
One can note from the Fig. 2 when implication would be that also implication would be that .
we discuss all cases where while
or , From all the above cases, there is no possibility that the two representations are identical.
Contrary Case
contradiction the resolving set of cardinality one is possible if and only if it is a path graph, it contains a cycle and the minimum edge metric dimension 2 if a graph contains a cycle so the dimension 1 is not possible.
implies the resolving set has minimum cardinality two. Hence prove that is also the resolving set of nanosheet. □
Figure 4.

Octagone for sheet.
Figure 3.
Generalize Nanosheet.
Table 2.
Edge representation of Fig. 4.
| Edges | e1,1 | e1,2 | e1,3 | c1,1 | c1,2 | |||
| (0,1) | (1,2) | (2,3) | (1,0) | (2,1) | (3,2) | (0,0) | (3,3) | |
4. Exchange property
In finite-dimensional spaces, each vector is uniquely defined by elements constituting a vector space's basis, expressed through a linear combination. Similar to a linear basis in a vector space, the basis of a vector space is characterized by the exchange property. Likewise, each vertex in a finite graph can be uniquely identified through the vertices of a minimal resolving set. Consequently, resolving sets in finite graphs exhibit characteristics akin to bases in finite-dimensional vector spaces. However, unlike the linear basis of a vector space, the exchange property is not universally applicable to minimal resolving sets. Various studies in the literature have explored the presence of the exchange property in different graphs. For example, the exchange property holds for resolving sets in tree graphs, and it holds for determining sets but is false for resolving sets in wheel graphs for [38].
Theorem 4.1
The exchange property holds for an octagonal nanosheetif.
To establish the exchange property, let's consider the minimal edge resolving set and another vertex belonging to . According to the exchange property, should also form a minimal resolving set, where . Let's denote this set as K. Now, let's prove that K is indeed a minimal edge resolving set for . Since , removing u from results in . Adding vertex v to this set, we get . Now, by Theorem 3.3, we know that is a minimal resolving set. Therefore, K is also a minimal resolving set. This demonstrates that the exchange property holds for as the sets and can exchange the vertices u and v while maintaining the minimal edge resolving set property. The exchange property is valuable in various applications, such as network localization, defect diagnostics, and graph reconstruction. It facilitates the efficient creation and modification of resolving sets, enhancing the analysis and understanding of graph structures. It's important to note that not all resolving sets possess the exchange property, although it is beneficial when present.
Conclusion
This article explores two nanosheet structures derived from the octagonal grid. The minimal edge resolving sets for these nanosheets have been identified based on graph distances, and they have a cardinality of 2. Additionally, the study investigates the transformation of a nanosheet into a nanotube, observing that the conversion from 2D to 3D increases the cardinality of the edge resolving set by one. The analysis confirms the presence of the exchange property in this structural transformation.
4.1. Future study
We computed the exchange property and the single edge resolving set in this draught. It is also possible to talk about additional resolving set variations, such as fault-tolerant resolving sets [39], [40], [41], the chemical compounds' partition resolvability [42], [43], and other related theoretical parameters.
CRediT authorship contribution statement
Ali N.A. Koam: Writing – review & editing, Data curation, Conceptualization. Ali Ahmad: Writing – review & editing, Funding acquisition, Formal analysis. Sikander Ali: Writing – original draft, Resources, Project administration. Muhammad Kamran Jamil: Writing – review & editing, Methodology, Investigation. Muhammad Azeem: Writing – review & editing, Visualization, Validation, Supervision.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgement
The authors extend their appreciation to Deanship of Scientific Research, Jazan University, for supporting this research work through the Research Unit Support Program Support Number: RUP2-02.
Contributor Information
Ali N.A. Koam, Email: akoum@jazanu.edu.sa.
Ali Ahmad, Email: ahmadsms@gmail.com, aimam@jazanu.edu.sa.
Sikander Ali, Email: sikanderalicui@gmail.com.
Muhammad Kamran Jamil, Email: m.kamran.sms@gmail.com.
Muhammad Azeem, Email: azeemali7009@gmail.com.
Data availability
No data was used for the research described in the article
References
- 1.Nadeem M.F., Hassan M., Azeem M., Khan S.U.D., Shaik M.R., Sharaf M.A.F., Abdelgawad A., Awwad E.M. Application of resolvability technique to investigate the different polyphenyl structures for polymer industry. J. Chem. 2021;2021:8. doi: 10.1155/2021/6633227. [DOI] [Google Scholar]
- 2.Siddiqui H.M.A., Imran N. Computation of metric dimension and partition dimension of nanotubes. J. Comput. Theor. Nanosci. 2015;12:199–203. doi: 10.1166/jctn.2015.3717. [DOI] [Google Scholar]
- 3.Hussain Z., Kang S.M., Rafique M., Munir M., Ali U., Zahid A., Saleem M.S. Bounds for partition dimension of m-wheels. Open Phys. 2019;17 doi: 10.1515/Phys-2019-0037. [DOI] [Google Scholar]
- 4.Shabbir A., Azeem M. On the partition dimension of the tri-hexagonal alpha-boron nanotube. IEEE Access. 2021;9:55644–55653. doi: 10.1109/ACCESS.2021.3071716. [DOI] [Google Scholar]
- 5.Alshehri H., Ahmad A., Alqahtani Y., Azeem M. Vertex metric-based dimension of generalized perimantanes diamondoid structure. IEEE Access. 2022;4 [Google Scholar]
- 6.Ahmad Al-N.Al-H., Ahmad A. Generalized perimantanes diamondoid structure and their edge-based metric dimensions. AIMS Math. 2022;7:11718–11731. doi: 10.3934/math.2022653. [DOI] [Google Scholar]
- 7.Manzoor S., Siddiqui M.K., Ahmad S. On entropy measures of polycyclic hydroxychloroquine used for novel Coronavirus (COVID-19) treatment. Polycycl. Aromat. Compd. 2022;42(6):2947–2969. doi: 10.1080/10406638.2020.1852289. [DOI] [Google Scholar]
- 8.Alatawi M.S., Ahmad A., Koam A.N.A., Husain S., Azeem AIMS M. Mathematics. 2022;7:6971–6983. [Google Scholar]
- 9.Siddiqui M.K., Imran M. Computing the metric and partition dimension of H-Naphtalenic and VC5C7 nanotubes. J. Optoelectron. Adv. Mater. 2016;17:790–794. [Google Scholar]
- 10.Mehreen N., Farooq R., Akhter S. On partition dimension of fullerene graphs. AIMS Math. 2018;3:343–352. [Google Scholar]
- 11.Yang B., Rafiullah M., Siddiqui H.M.A., Ahmad S. On resolvability parameters of some wheel related graphs. J. Chem. 2019:1–9. [Google Scholar]
- 12.Slater P.J. Proceeding of the 6th Southeastern Conference on Combinatorics, Graph Theory, and Computing, Congressus Numerantium, vol. 14. 1975. Leaves of trees; pp. 549–559. [Google Scholar]
- 13.Harary F., Melter R.A. On the metric dimension of graphs. Ars Comb. 1976;2:191–195. [Google Scholar]
- 14.Kelenc A., Tratnik N., Yero I.G. Uniquely identifying the edges of a graph: the edge metric dimension. Discrete Appl. Math. 2018;251:204–220. doi: 10.1016/j.dam.2018.05.052. [DOI] [Google Scholar]
- 15.Boutin D.L. Determining set, resolving sets, and the exchange property. Graphs Comb. 2009;25:789–806. doi: 10.1007/s00373-010-0880-6. [DOI] [Google Scholar]
- 16.Johnson M.A. Structure-activity maps for visualizing the graph variables arising in drug design. J. Biopharm. Stat. 1993;3:203–236. doi: 10.1080/10543409308835060. [DOI] [PubMed] [Google Scholar]
- 17.Khuller S., Raghavachari B., Rosenfeld A. Landmarks in graphs. Discrete Appl. Math. 1996;70:217–229. [Google Scholar]
- 18.Manuel P., Bharati R., Rajasingh I., Monica M.C. On minimum metric dimension of honeycomb networks. J. Discret. Algorithms. 2008;6:20–27. [Google Scholar]
- 19.Söderberg S., Shapiro H. A combinatory detection problem. Am. Math. Mon. 1963;70:1066–1070. [Google Scholar]
- 20.Sebö A., Tannier E. On metric generators of graphs. Math. Oper. Res. 2004;29:383–393. [Google Scholar]
- 21.Ahmad A., Koam A.N.A., Siddiqui M.H.F., Azeem M. Resolvability of the starphene structure and applications in electronics. Ain Shams Eng. J. 2021 doi: 10.1016/j.asej.2021.09.014. [DOI] [Google Scholar]
- 22.Chvatal V. Mastermind. Combinatorica. 1983;3:125–129. [Google Scholar]
- 23.Perc M., Gomez-Gardens J., Szolnoki A., Floria L.M., Moreno Y. Evolutionary dynamics of group interactions on structured populations: a review. J. R. Soc. Interface. 2013;10(80) doi: 10.1098/rsif.2012.0997. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Perc M., Szolnoki A. Coevolutionary games-a mini-review. Biosystems. 2010;99:109–125. doi: 10.1016/j.biosystems.2009.10.003. [DOI] [PubMed] [Google Scholar]
- 25.Javaid I., Shokat S. On the partition dimension of some wheel related graphs. J. Prime Res. Math. 2008;4:154–164. [Google Scholar]
- 26.Koam Ali N.A., Ali Sikander, Ahmad Ali, Azeem Muhammad, Kamran Jamil Muhammad. Resolving set and exchange property in nanotube. AIMS Math. 2023;8(9):20305–20323. doi: 10.3934/math.20231035. [DOI] [Google Scholar]
- 27.Koam A.N.A., Ahmad A., Ibrahim M., Azeem M. Edge metric and fault-tolerant edge metric dimension of hollow coronoid. MDPI. 2021;9:1405. [Google Scholar]
- 28.Koam A.N.A., Ahmad A., Azeem M., Nadeem M.F. Bounds on the partition dimension of one pentagonal carbon nanocone structure. Arab. J. Chem. April 2022 [Google Scholar]
- 29.Yero I.G. Vertices, edges, distances, and metric dimensions are in the graphs. Electron. Notes Discrete Math. 2016;55:191–194. [Google Scholar]
- 30.Ahsan M., Zahid Z., Zafar S., Rafiq A., Sindhu M.S., Umar M. Computing the edge metric dimension of convex polytopes-related graphs. J. Math. Comput. Sci. 2021;22:174–188. [Google Scholar]
- 31.Hussain Z., Munir M., Choudhary M., Kang S.M. Computing metric dimension and metric basis of the 2D lattice of alpha-boron nanotubes. Symmetry. 2018;10 [Google Scholar]
- 32.Ahmad A., Bača M., Sultan S. Computing the metric dimension of kayak paddle graph and cycles with chord. Proyecciones J. Math. 2020;39(2):287–300. [Google Scholar]
- 33.Siddiqui M.K., Naeem M., Rahman N.A., Imran M. Computing topological indices of certain networks. J. Optoelectron. Adv. Mater. 2016;18:884–892. [Google Scholar]
- 34.Ashrafi A.R., Doslic T., Saheli M. The eccentric connectivity index of nanotubes. MATCH Commun. Math. Comput. Chem. 2011;65:221–230. [Google Scholar]
- 35.Siddiqui H.M.A., Arshad M.A., Nadeem M.F., Azeem M., Haider A., Malik M.A. Topological properties of a supramolecular chain of different complexes of N-salicylidene-L-Valine. Polycycl. Aromat. Compd. 2022;42(9):6185–6198. doi: 10.1080/10406638.2021.1980060. [DOI] [Google Scholar]
- 36.Siddiqui M.K., Naeem M., Rahman N.A., Imran M. Computing topological indices of specific networks. J. Optoelectron. Adv. Mater. 2016;18:9–10. [Google Scholar]
- 37.Heydari A., Taeri B. Szeged index of (S) nanotubes. Eur. J. Comb. 2009;30:1134–1141. [Google Scholar]
- 38.Boutin D.L. 2018. Determining Sets, Resolving Sets, and the Exchange Property. Arxiv. org. [Google Scholar]
- 39.Raza H., Hayat S., Pan X. -Feng. On the fault-tolerant metric dimension of convex polytopes. Appl. Math. Comput. 15 December 2018;339:172–185. doi: 10.1016/j.amc.2018.07.010. [DOI] [Google Scholar]
- 40.Raza H., Hayat S., Imran M., Pan X.-Feng. Fault-tolerant resolvability and extremal structures of graphs. Mathematics. 2019;7(1):78. doi: 10.3390/math7010078. [DOI] [Google Scholar]
- 41.Raza H., Hayat S., Pan X. -Feng. On the fault-tolerant metric dimension of certain interconnection networks. J. Appl. Math. Comput. 2019;60:517–535. [Google Scholar]
- 42.Siddiqui H.M.A., Hayat S., Khan A., Imran M., Razzaq A., Liu J. -Bao. Resolvability and fault-tolerant resolvability structures of convex polytopes. Theor. Comput. Sci. 3 December 2019;796:114–128. doi: 10.1016/j.tcs.2019.08.032. [DOI] [Google Scholar]
- 43.Hayat S., Khan A., Malik M.Y.H., Imran M., Siddiqui M.K. Fault-tolerant metric dimension of interconnection networks. IEEE Access. 2020;8:145435–145445. doi: 10.1109/ACCESS.2020.3014883. [DOI] [Google Scholar]
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