1. Introduction
The concept of graph theory was introduced by Euler. A crisp graph shows the relations between the elements of the vertex set. A weighted graph gives the extent of these relations. Many problems can be solved if proper weights are given. However, in many situations, the weights may not known, and the relationship is uncertain. Hence, a fuzzy relation can be used to handle such situations. Rosenfeld [
1] developed the concept of a fuzzy graph. He also discussed several concepts like edges, paths, bridges and connectedness in a fuzzy graph. Most of the theoretical development of fuzzy graph theory is based on Rosenfeld’s initial work. Bhutani et al. [
2,
3] introduced the advance concepts in fuzzy graphs.
Sometimes when the relationship between the elements of the vertex set is indeterminate, the fuzzy graph and its extension fails. This indeterminacy can be overcome by using single-valued neutrosophic graphs [
4].
Dinesh, in [
5], introduced the concept of unordered pairs of vertices which are not incident with end vertices. The fuzzy incidence graph not just shows the relations between vertices, but also provides information about the influence of a vertex on an edge. Dinesh extended the idea of the fuzzy incidence graph in [
6] by introducing new concepts in this regard. Later, Methew et al. [
7] discussed the connectivity concepts in fuzzy incidence graphs. Malik et al. [
8] applied the notion of the fuzzy incidence graph in problems involving human trafficking. They discussed the role played by the vulnerability of countries and their government’s response to human trafficking. Methew et al. [
9] studied fuzzy incidence blocks and their applications in illegal migration problems. They used fuzzy incidence graphs as a model for a nondeterministic network with supporting links. They used fuzzy incidence blocks to avoid the vulnerable links in the network.
The paper is organized as follows: In
Section 1, we give some preliminary notions and terminologies of fuzzy incidence graphs which are needed to understand the extended concept of the single-valued neutrosophic incidence graph. In
Section 2, we present the definition of a single-valued neutrosophic incidence graph. We also discuss the edge-connectivity, vertex-connectivity and pair-connectivity in neutrosophic incidence graphs. In
Section 3, we give a mathematical model of the situation of illegal migration from Pakistan to Europe. Finally, the paper is concluded by some remarks in
Section 4. Below we present some preliminary definitions from [
6] and [
4]. For further study on these topics, the readers are referred to references [
1,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16].
Let be a graph on a nonempty set, V. Then, is called an incidence graph, where . The elements of I are called incidence pairs or simply, pairs.
A fuzzy incidence graph of an incidence graph,
, is an ordered-triplet,
=
, where
is a fuzzy subset of
V,
is a fuzzy relation of
V, and
is a fuzzy subset of
I such that
We may compare elements of two neutrosophic sets
A and
B, that is
2. Single-Valued Neutrosophic Incidence Graphs
Definition 1. A single-valued neutrosophic incidence graph of an incidence graph, , is an ordered-triplet, , such that
- 1.
A is a single-valued neutrosophic set on V.
- 2.
B is a single-valued neutrosophic relation on V.
- 3.
C is a single-valued neutrosophic subset of such that
Here, we discuss an example of a single-valued neutrosophic incidence graph (SVNIG).
Example 1. Consider an incidence graph, , such that , and , as shown in Figure 1. Let be a single-valued neutrosophic incidence graph associated with G, as shown in Figure 2, where
Definition 2. The support of an SVNIG is denoted by where Now we introduce the concepts of edge, pair, walk, trail, path and connectedness in an SVNIG.
Definition 3. If ∈ , then is an edge of the SVNIG and if , then and are called pairs of .
Definition 4. A sequenceof vertices, edges and pairs in is a walk. It is a closed walk if . In the above sequence, if all edges are distinct, then it is a trail, and if the pairs are distinct, then it is an incidence trail. P is called a path if the vertices are distinct. A path is called a cycle if the initial and end vertices of the path are same. Any two vertices of are said to be connected if they are joined by a path.
Example 2. In the example presented earlieris a walk. It is a closed walk since the initial and final vertices are same, i.e., it is not a path, but it is a trail and an incidence trail. is a walk, path, trail and an incidence trail.
Definition 5. Let be a nSVNIG. Then, = is a single-valued neutrosophic incidence subgraph of if , and . is a single-valued neutrosophic incidence spanning subgraph of if .
Definition 6. In an SVNIG, the strength of a path, P, is an ordered triplet denoted by , where Similarly, the incidence strength of a path, P, in an SVNIG is denoted by , where Example 3. Let be an incidence graph, as shown in Figure 3, and is an SVNIG associated with G, which is shown in Figure 4. Clearly, is a path in .
The strength of the path, P, is , and the incidence strength of P is .
Definition 7. In an SVNIG, the greatest strength of the path from l to m, where l,m is the maximum of strength of all paths from l to m.(l,m) is sometimes called the connectedness between l and m. Similarly, the greatest incidence strength of the path from l to m, where l,m is the maximum incidence strength of all paths from l to m.where , are different paths from l to m. is sometimes referred as the incidence connectedness between l and m.
Example 4. In the SVNIG given in Figure 4, the total paths from vertex u to w are as follows:
The corresponding incidence strengths of each path are Now, the greatest incidence strength of the path from u to w is calculated as follows: Definition 8. An SVNIG, , is a cycle if, and only if, the underlying graph, , is a cycle.
Definition 9. The SVNIG is a neutrosophic cycle if, and only if, is a cycle and there exists no unique edge, , such that Definition 10. The SVNIG is a neutrosophic incidence cycle if, and only if it is a neutrosophic cycle and there exists no unique pair, , such that Example 5. Let be an SVNIG, as shown in Figure 5. is a cycle, since (support of ) is clearly a cycle. So, is a neutrosophic cycle.
Furthermore, is a neutrosophic incidence cycle since there is more than one pair, namely, and , such that The concepts of bridges, cutvertices and cutpairs in SVNIG are defined as follows.
Definition 11. Let be an SVNIG. An edge, , in is called a bridge if, and only if, is a bridge in —that is, the removal of disconnects .
An edge is called a neutrosophic bridge ifwhere and denote the connectedness between x and y in and , respectively. An edge, , is called a neutrosophic incidence bridge ifwhere and denote the incidence connectedness between x and y in and , respectively. Definition 12. Let be an SVNIG. A vertex, v, in is a cutvertex if, and only if, it is a cutvertex in —that is is a disconnect graph.
A vertex, v, in an SVNIG is called a neutrosophic cutvertex if the connectedness between any two vertices in is less than the connectedness between the same vertices in —that is, A vertex, v, in SVNIG is a neutrosophic incidence cutvertex if for any pair of vertices, x, y, other than v, the following condition holds:where and denote the incidence connectedness between x and y in and , respectively. Definition 13. Let be an SVNIG. A pair is called a cutpair if, and only if, is a cutpair in —that is, after removing the pair , there is no path between u and .
Let be an SVNIG. A pair is called a neutrosophic cutpair if deleting the pair reduces the connectedness between , that is,where and denote the connectedness between u and in and , respectively. A pair is called neutrosophic incidence cutpair ifwhere and denote the incidence connectedness between u and in and , respectively. Example 6. In the SVNIG, , given in Figure 6, and are bridges, since their removal disconnects the underlying graph, . In , , , and are neutrosophic bridges, since, for a, e ,after the removal of each of the bridges. The edges—, , and —are neutrosophic incidence bridges in as well. b and c are cutvertices. In addition, all the vertices of are neutrosophic cutvertices, except for a, since the removal of a does not affect the connectedness of . b, c, d and e are neutrosophic incidence cutvertices in .
The pairs , , and are the cutpairs, neutrosophic cutpairs and also neutrosophic incidence cutpairs in the given graph.
Theorem 1. Let be a SVNIG. If is a neutrosophic bridge, then is not a weakest edge in any cycle.
Proof. Let be a neutrosophic bridge and suppose, on the contrary, that is the weakest edge of a cycle. Then, in this cycle, we can find an alternative path, , from u to v that does not contain the edge , and is greater than or equal to , where is the path involving the edge . Thus, removal of the edge from does not affect the connectedness between u and v—a contradiction to our assumption. Hence, is not the weakest edge in any cycle. ☐
Theorem 2. If is a neutrosophic incidence cutpair, then is not the weakest pair in any cycle.
Proof. Let be a neutrosophic incidence cutpair in . On contrary suppose that is a weakest pair of a cycle. Then we can find an alternative path from u to having incidence strength greater than or equal to that of the path involving the pair . Thus, removal of the pair does not affect the incidence connectedness between u and but this is a contradiction to our assumption that is a neutrosophic incidence cutpair. Hence is not a weakest pair in any cycle. ☐
Theorem 3. Let be a SVNIG. If is a neutrosophic bridge in , then Proof. Let
be an SVNIG, and
uv is a neutrosophic bridge in
. On the contrary, suppose that
Then, there exists a
u-
v path,
P, with
and
for all edges on path
P. Now,
P, together with the edge,
, forms a cycle in which
is the weakest edge, but it is a contradiction to the fact that
is a neutrosophic bridge. Hence,
☐
Theorem 4. If is a neutrosophic incidence cutpair in an SVNIG = , then Proof. The proof is on the same line as Theorem 3. ☐
Theorem 5. Let be an SVNIG and is a cycle. Then, an edge, , is a neutrosophic bridge of if, and only if, it is an edge common to two neutrosophic incidence cutpairs.
Proof. Suppose that is a neutrosophic bridge of . Then, there exist vertices u and v with the edge lying on every path with the greatest incidence strength between u and v. Consequently, there exists only one path, P, (say) between u and v which contains a edge and has the greatest incidence strength. Any pair on P will be a neutrosophic incidence cutpair, since the removal of any one of them will disconnect P and reduce the incidence strength.
Conversely, let
be an edge common to two neutrosophic incidence cutpairs
and
. Thus both
and
are not the weakest cutpairs of
. Now,
being a cycle, there exist only two paths between any two vertices. Also the path
from the vertex
u to
v not containing the pairs
and
has less incidence strength than the path containing them. Thus, the path with the greatest incidence strength from
u to
v is
Therefore, is a neutrosophic bridge. ☐
Definition 14. Let = be an SVNIG. An edge, , of is called a strong edge ifwhere represents the connectedness between u and v in . In particular, an edge, , is said to be an α-strong edge ifand it is called a β-strong edge if Definition 15. A pair in an SVNIG, , is called a strong pair ifwhere represents the incidence connectedness between u and in In particular, is called α-strong pair ifand it is called β-strong pair if It is not necessary for all edges and pairs to be strong. Edges and pairs exist which are not strong in an SVNIG. Such edges and pairs are given in the following definition.
Definition 16. Let be an SVNIG. An edge, , is said to be a δ-edge if Similarly, a pair in is called a δ-pair if Theorem 6. In an SVNIG, every neutrosophic incidence cutpair is a strong pair.
Proof. Let
=
be an SVNIG. Let
be a neutrosophic incidence cutpair. Then, by Definition 13, we have
On the contrary, suppose that
is not a strong incidence pair. Then, it follows that
Let P be the path from u to in with the greatest incidence strength. Then, P together with , forms a cycle in . Now, in this cycle, is the weakest pair, but, based on Theorem 2, it is not possible, since is a neutrosophic incidence cutpair. Hence, our assumption is wrong, and is a strong incidence pair. ☐
Theorem 7. In an SVNIG = The pair is a neutrosophic incidence cutpair if, and only if, it is α-strong.
Proof. Let
be a neutrosophic incidence cutpair in
. Then, according to the Definition 13 of cutpair,
Then, based on Theorem 4, it follows that
which is the definition of
-strong pair. Hence,
is an
-strong pair in
.
Conversely, let
be an
-strong pair in
. Then, by definition
It follows that
is a unique path from
u to
which has the greatest incidence strength of all paths.Therefore, any other path from
u to
will have a lower incidence strength.
Hence, is a neutrosophic incidence cutpair. ☐
Definition 17. Let be an SVNIG.
- (i)
is called a block if is block. That is, there are no cutvertices in .
- (ii)
is called a neutrosophic block if has no neutrosophic cutvertices.
- (iii)
is called a neutrosophic incidence block if it has no neutrosophic incidence cutvertices.
Example 7. Consider the SVNIG shown in Figure 7 with and . is a block, since the crisp graph, , has no cutvertex and it is a neutrosophic incidence block. is not a neutrosophic block, since it has a neutrosophic cutvertex, namely, a. Theorem 8. Let be a neutrosophic incidence block. A pair, , in , such thatfor all , is a strong pair. Proof. Let
be a neutrosophic incidence block. By definition, there are no neutrosophic incidence cutvertices in
. Let
be a pair in
, such that
We will prove that
is a strong pair by showing that
The incidence strength of any path,
P, from
u to
will be less than or equal to
. If
is the only pair in
with
then every other path from
x to
in
will have less incidence strength than
, and hence,
Thus, is an -strong pair.
If
is not unique, then the maximum possible value for the incidence strength of any path in
will be equal to
. Therefore, there exists a path from
u to
with an incidence strength equal to
, that is
Then, is -strong. ☐