Advances in Mathematical Physics

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Theory and Applications of Riemannian Submersions

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Volume 2022 |Article ID 3182116 | https://doi.org/10.1155/2022/3182116

Zheng Kou, Maryam Akhoundi, Xiang Chen, Saber Omidi, "A Study on Vague Graph Structures with an Application", Advances in Mathematical Physics, vol. 2022, Article ID 3182116, 14 pages, 2022. https://doi.org/10.1155/2022/3182116

A Study on Vague Graph Structures with an Application

Academic Editor: Meraj Ali Khan
Received13 Jan 2022
Accepted10 Feb 2022
Published02 Mar 2022

Abstract

Fuzzy graph (FG) models take on the presence being ubiquitous in environmental and fabricated structures by human, specifically the vibrant processes in physical, biological, and social systems. Owing to the unpredictable and indiscriminate data which are intrinsic in real-life, problems being often ambiguous, so it is very challenging for an expert to exemplify those problems through applying an FG. Vague graph structure (VGS), belonging to FGs family, has good capabilities when facing with problems that cannot be expressed by FGs. VGSs have a wide range of applications in the field of psychological sciences as well as the identification of individuals based on oncological behaviors. Therefore, in this paper, we apply the concept of vague sets (VSs) to GS. We define certain notions, VGS, strong vague graph structure (SVGS), and vague -cycle and describe these notions by several examples. Likewise, we introduce -complement, self-complement (SC), strong self-complement (SSC), and totally strong self-complement (TSSC) in VGS and investigate some of their properties. Finally, an application of VGS is presented.

1. Introduction

The FG concept serves as one of the most dominant and extensively employed tools for multiple real-word problem representations, modeling, and analysis. To specify the objects and the relations between them, the graph vertices or nodes and edges or arcs are applied, respectively. Graphs have long been used to describe objects and the relationships between them. Many of the issues and phenomena around us are associated with complexities and ambiguities that make it difficult to express certainty. These difficulties were alleviated by the introduction of fuzzy sets by Zadeh [1]. A GS, proposed by Sampathkumar [2], refers to the generalization of undirected graph being relatively beneficial in investigating some structure including graphs, signed graphs, and graphs in which every edge is labeled or colored. A GS facilitates studying the different relations and the equivalent edges simultaneously. The FS focuses on the membership degree of an object in a particular set. The existence of a single degree for a true membership could not resolve the ambiguity on uncertain issues, so the need for a degree of membership was felt. Afterward, to overcome the existing ambiguities, Gau and Buehrer [3] introduced false-membership degrees and defined a VS as the sum of degrees not greater than 1. Kaufmann [4] represented FGs based on Zadeh’s fuzzy relation [5, 6]. Rosenfeld [7] described the structure of FGs obtaining analogs of several graph theoretical concepts. Harinath and Lavanya [8] studied new concepts in fuzzy graph structures. Bhattacharya [9] gave some remarks on FGs. Several concepts on FGs were introduced by Mordeson and Nair [10]. Dinesh [11] investigated the notion of a FGS and studied some related properties. Ghorai et al. [12, 13] presented fuzzy tolerance graphs and planarity in VGs. Ramakrishna [14] defined VGs. Kosari et al. [1518] investigated domination set, equitable domination set, and new concepts of domination in vague graphs and vague incidence graphs. Pal and Rashmanlou [19, 20] have given several concepts in FGs. Akram et al. [21, 22] introduced certain fuzzy graph structures. Sunitha and Vijayakumar [23] presented some properties of complement on FGs. Muhiuddin et al. [2426] investigated new results in cubic graphs.

A VGS is concerned with the generalized structure of an FG that expresses more exactness, adaptability, and compatibility to a system when synchronized with systems operating on FGs. Correspondingly, a VGS is capable of focusing on determining the uncertainly combined with the inconsistent and indeterminate information of any real-world problem, in which FGs may not lead to adequate results. Hence, in this paper, we define the certain notions including VGS, SVGS, and vague -cycle and describe these notions by several examples. We study -complement, SC, and SSC in VGSs and investigate some of their properties. Finally, an application of VGS has been presented.

2. Preliminaries

A GS , consists of a nonempty set together with relations on , which are mutually disjoint so that each is irreflexive and symmetric. If for some , , we name it an -edge and write it as “.

A GS is CGS, if,(i)every edge , appears at least once in (ii)among every pair of nodes in , is an -edge for some ,

Definition 1. (see [1]). A fuzzy subset on a set is a map . A fuzzy binary relation on is a fuzzy subset on . By a fuzzy relation, we mean a fuzzy binary relation given by .

Definition 2. (see [11]). Let be a GS and let be the fuzzy subset of , respectively, so that , , . Then, is an FGS of .

Definition 3. (see [11]). Let be an FGS of a GS . Then, is a PFSSGS of if , for .

Definition 4. (see [11]) The strength of a -path of a FGS is , for .

Definition 5. (see [11]) In a FGS , , , , for any . Also, .

Definition 6. Reference [11] is a -cycle if and only if is a -cycle.

Definition 7. Reference [11] is a fuzzy -cycle if and only if is a -cycle and no unique in so that

Definition 8. (see [3]) A VS is a pair on set X where and are taken as real valued functions which can be defined on so that , .

Definition 9. (see [14]) A VG is a pair , where is a VS on and is a VS on so that and , for .
All the basic notations are shown in Table 1.


NotationMeaning

FGFuzzy graph
FSFuzzy set
VSVague set
GSGraph structure
CGSComplete graph structure
VGSVague graph structure
VSGSVague subgraph structure
SGSSubgraph structure
FGSFuzzy graph structure
SVGSStrong vague graph structure
UGUnderlying graph
ENEnd node
SCSelf-complementary
SSCStrong self-complementary
TSCTotally self-complementary
TSSCTotally strong self-complement
PFSSGSPartial fuzzy spanning subgraph structure
UVSUnderlying vertex set
TSSCTotally strong self-complementary

3. New Concepts in Vague Graph Structure

Definition 10. is said to be a VGS of a GS , if is a VS on and for every ; is a VS on so that. Note that , and , , , where and are named UVS and underlying -edge set of , respectively.

Example 1. Let be a GS so that , , and . Let , , and be vague subsets of , , and , respectively, so thatThen, is a VGS of drawn in Figure 1.

Definition 11. (i)AVGS is said to be a VSGS of a VGS with UVS , if and , , that is,and for ,(ii) is named a VSSGS of a VGS , if .(iii) is named a VPSSGS of a VGS , if it excludes some edges of .

Example 2. Consider a VGS as shown in Figure 1. LetIt is easy to see that , , and are the VSGS, VSSGS, and VPSSGS of , respectively.
Their corresponding graphs are drawn in Figures 24.

Definition 12. Let be a VGS with UVS . Then, there exists a -edge among two nodes and of so that we have(i), , or(ii), , or(iii), , for some .

Definition 13. For a VGS , the support of is described as

Definition 14. -path of a VGS with UVS is a sequence of distinct nodes (except the choice ) so that is a -edge, .

Definition 15. In a VGS with UVS , two nodes and called -connected, if they are connected by a -path, for some .

Definition 16. A VGS with UVS is called to be -strong, if -edges ,for some .

Example 3. Consider the VGS , drawn in Figure 1. Then,(i) are -edges and are -edges(ii) and are and paths, respectively(iii) and are -connected nodes of (iv) is a -strong since and we have

Definition 17. A VGS is named to be strong, if it is -strong, .

Definition 18. A VGS with UVS , is named complete or -complete if(i) is a SVGS(ii), (iii)For each nodes , should be a -edge

Example 4. Suppose drawn in Figure 5, be VGS of the GS where , , and . Then, is a SVGS, since it is both -strong and -strong. Moreover, , , and each nodes in , is either a -edge or a -edge, so is a complete or -complete-VGS as well.

Definition 19. In a VGS with UVS , and -strength of a -path “” are denoted by and , respectively, so that and .
Then, we write strength of the path .

Example 5. In shown in Figure 5, is a -path, and is a -path, we haveThus, strength of -path is , and strength of -path is .

Definition 20. In a VGS with UVS ,(i)-strength of connectedness between and is defined by , where , for and ;(ii)-strength of connectedness among and is described by , where , for and .

Example 6. Let be a VGS of GS as shown in Figure 6 so that , , and . Since , , and , therefore,Thus, we have,Since , , and , therefore,andThus, we haveBy similarity way, we can calculate , , and .

Definition 21. A VGS of a GS is a -cycle, if is an -cycle.

Definition 22. A VGS of a GS is a vague -cycle, for some , if we have(i) is a -cycle;(ii)There is no unique -edge in so that or .

Example 7. VGS in Figure 7 is a -cycle as well as vague -cycle, since is an -cycle and there are two -edges with minimum degree of membership and two -edges with maximum degree of membership of all -edges.

Definition 23. A VGS of GS is isomorphic to a VGS of if a bijective and a permutation on the set so that, , for all , .

Definition 24. A VGS of GS is identical to a VGS of if a bijection so thatand

Example 8. Let and be two VGSs of GS and , respectively, drawn in Figure 8. Here, is isomorphic (not identical) to under the mapping , defined by , , and and a permutation given by , so that

Example 9. Let and be two VGSs of GSs and , respectively, as shown in Figure 9. Here, is identical with under the mapping , defined by , , , , , and so that

Definition 25. Let be a VGS of a GS . Let denote a permutation on the set and the corresponding permutation on , i.e., if , . If for some and , , , then, while is chosen so that and , . Then, VGS denoted by , is named the -complement of VGS.

Example 10. Consider VGS shown in Figure 10 and let be a permutation on the set so that and . Now, for ,Clearly, and , so .So, . Also, for , we have