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Articles

On m-Polar Interval-valued Fuzzy Graph and its Application

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Pages 71-96 | Received 19 Sep 2019, Accepted 15 Jun 2020, Published online: 08 Feb 2021

Abstract

In this paper, the concept of the m-polar fuzzy graph (m-PFG) and interval-valued fuzzy graph (IVFG) is integrated and introduced an unprecedented kind of fuzzy graph designated as m-polar interval-valued fuzzy graph (m-PIVFG). Complement of the m-PIVFG is defined and the failure of this definition in some cases are highlighted. Various examples are cited and then redefined the notation of complement such that it applies to all m-PIVFGs. The other algebraic properties such as isomorphism, weak isomorphism, co-weak isomorphism of the m-PIVFG are investigated. Moreover, some basic results on the isomorphic property of m-PIVFG are proved. Finally, an application of m-PIVFG is explored.

Abbreviations: The following abbreviations are employed in this study: FS: Fuzzy set; FG: Fuzzy graph; IVFS: Interval-valued fuzzy sets; IVFG: Interval-valued fuzzy graph; m-PFS: m-polar fuzzy sets; m-PFG: m-polar fuzzy graph; m-PIVFS: m-polar interval-valued fuzzy sets; m-PIVFG: m-polar interval-valued fuzzy graph.

1. Introduction

A graph is a mathematical structure used to represent pairwise relations between objects. It is defined as an ordered pair G=(V,E) consisting of a set of vertices, designated as V and a set of edges, denoted by E. When there is a vagueness either in vertices or in edges or in both then a fuzzy model is needed to describe a fuzzy graph. With the Konigsberg bridge problem, the graph theory was started in 1735. The concept was first introduced by Swiss Mathematician Euler in 1736. Then, Euler studied and incorporated a structure that solves the Konigsberg bridge problem which is also known as a Eulerian graph. Thereafter, the complete and bipartite graphs were proposed by Mobius in 1840. Recently, applications of graph theory are mostly promoted to the areas of computer networks, electrical networks, coding theory, operational research, architecture, data mining, etc.

Observing the vast application of graph theory motivated to explain fuzzy graph which is a non-empty set V together with a fuzzy set and a fuzzy relation. In 1973, Kauffman [Citation1] defined fuzzy graph depending on the idea of fuzzy set introduced by Zadeh [Citation2]. In 1975, Rosenfeld [Citation3] first proposed another definition of the Fuzzy graph which is a generalization of Euler's Graph theory. He also elaborated definition of fuzzy vertex, fuzzy edges and several fuzzy concepts such as cycles, paths, connectedness, etc. The idea of isomorphism, weak isomorphism, co-weak isomorphism between fuzzy graphs was introduced by Bhutani [Citation4] in 1989. The extension of the concept of fuzzy set and the idea of bipolar fuzzy sets were given in 1994 by Zhang [Citation5, Citation6]. Several properties of fuzzy graphs and hypergraphs were discussed by Mordeson and Nair [Citation7–9] in 2000.

IVFG was defined by Hongmei and Lianhua [Citation10] in 2009 and some operations on this were studied by Akram and Dudek [Citation11] in 2011. Complete fuzzy graph was defined by Hawary [Citation12]. He also studied three new operations on it. Nagoorgani and Malarvizhu [Citation13, Citation14] studied isomorphic properties on fuzzy graphs and also defined the self-complementary fuzzy graphs. The extension of bipolar fuzzy set and the idea of m-polar fuzzy sets (m-PFS) were introduced by Chen et al. [Citation15] in 2014. Samanta and Pal [Citation16–19] investigated on fuzzy tolerance graph, fuzzy threshold graph, fuzzy k-competition graphs, p-competition fuzzy graphs and also fuzzy planar graphs. Some properties of isomorphism and complement on IVFG were studied by Talebi and Rashmanlou [Citation20]. Later, Ghorai and Pal [Citation21, Citation22] described various properties on m-PFGs. They examined isomorphic properties on m-PFG. Different types of research on generalized fuzzy graphs were discussed on [Citation23–31]. The main contribution of this study is as follows:

  • Concept of m-PIVFGs and complement of m-PIVFGs are introduced with examples.

  • The definitions of classic and non-classic m-PIVFG related to complement of that are also discussed.

  • Definition of isomorphic, weak isomorphic and co-weak isomorphic m-PIVFG are explained.

  • Results based on isomorphic properties of m-PFGs are discussed.

  • A case study based on m-PIVFG is explained.

The rest of the paper is arranged as follows: Section 1 describes the historical backgrounds of Fuzzy graphs. Section 2 provides some basic ideas of the m-PFGs, IVFGs with some examples. In Section 3, m-PIVFG is defined and supported with examples. Complete m-PIVFG and strong m-PIVFG are also investigated with suitable examples. Section 4 provides the definition of a complement of an m-PIVFG. This section is based on a description of the complement of an m-PIVFG and some improvements over this definition. In section 5 various types of isomorphic property of m-PIVFGs are described with examples. Some propositions and theorems related to this property are also discussed. Section 6 provides the application of an m-PIVFG in decision-making problems. Section 7 is based on a summary of this article.

2. Preliminaries

In this part, some definitions related to m-PFG are defined and demonstrated with the help of examples. The basic definition of IVFG is also discussed in this part, followed by an example for demonstration.

A fuzzy set is a set whose elements have degrees of membership. Fuzzy sets were introduced by Zadeh [Citation2] in 1965 as an extension of the classical notion of the set. A fuzzy set A is a pair (S,m) where S is a set and m:S[0,1] is a membership function. Throughout this article, G is a crisp graph, and G is a fuzzy graph.

Proof

DEFINITION 2.1

([Citation15]) An m-PFS (or a [0,1]m-set) on a set X is a mapping A:X[0,1]m. The set of all m-PFS on X is denoted by m(X).

Proof

DEFINITION 2.2

[Citation32] Let A be an m-PFS on X. An m-polar fuzzy relation on A is an m-PFS B of X×X such that B(x,y)min{A(x),A(y)} x,yX i.e. for each i=1,2,,m and x,yX piB(x,y)min{piA(x),piA(y)}.

Proof

DEFINITION 2.3

[Citation32] An m-PFG of a crisp graph G=(V,E) is a pair G=(A,B) where A:V[0,1]m is an m-PFS in V and B:V×V[0,1]m is an m-PFS in V×V such that for each i=1,2,,m; piB(xy)min{piA(x),piA(y)} xyV×V and B(xy)=0 xy(V×V)E, where 0=(0,0,,0) is the smallest element in [0,1]m. A is called the m-polar fuzzy vertex set of G and B is called the m-polar fuzzy edge set of G.

Proof

Example 1

The following is an example of an m-PFG. Let G=(V,E) be a crisp graph where V={a,b,c,d,e} and E={ab,bc,cd,ae,de}. Let piV be an m-PFS on V and let piE be an m-PFS on E defined by Tables and , respectively:

Figure 1. 3-PFG.

Figure 1. 3-PFG.

Table 1. m-PFS on V.

Table 2. m-PFS on E.

Proof

DEFINITION 2.4

[Citation33] An IVFS A on V is defined as A={(x,[μAl(x),μAu(x)]):xV}, where μAl(x) and μAu(x) are fuzzy subsets on V such that μAl(x)μAu(x), xV. Based on this set a graph called IVFG is defined.

Proof

DEFINITION 2.5

[Citation10] By an IVFG of a crisp graph G=(V,E) we mean G=(A,B), where A=[μAl(x),μAu(x)] is an IVFS on V and B=[μBl(xy),μBu(xy)] is an IVFS on E, such that μBl(xy)min{μAl(x),μAl(y)}, μBu(xy)min{μAu(x),μAu(y)} xyE.

Lots of works have been done on this graph [Citation34–38].

Proof

Example 2

The following is an example of IVFG. Let G=(V,E) be a crisp graph where V={a,b,d,e} and E={ab,ae,de}. Let A be an IVFS on V and let B be an IVFS on E defined by Tables and , respectively:

In the following section the m-PIVFG, a combination of IVFG and m-PFG is defined.

Figure 2. An IVFG.

Figure 2. An IVFG.

Table 3. IVFS on V.

Table 4. IVFS on E.

3. m-polar Interval-valued Fuzzy Graph (m-PIVFG)

Herein, m-PFG and IVFG are combined and the concept of m-PIVFG is introduced and demonstrated with examples. Also, in this part we described complete m-PIVFG with appropriate examples and strong m-PIVFG, illustrated with examples.

Proof

DEFINITION 3.1

An m-PIVFG of a graph G=(V,E) is a pair G=(V,A,B) consists of a non-empty set V together with pair of interval-valued function A:V[0,1]m is an m-PFS in V and B:V×V[0,1]m and μ:V×V[0,1]m for each i=1,2,,m; piμA(x)=[piμAl(x),piμAu(x)], 0μAl(x)μAu(x)1 and piμB(xy)=[piμBl(xy),piμBu(xy)], 0μBl(xy)μBu(xy)1 and for each i=1,2,,m, the interval number of vertex x and of the edge xy in G respectively satisfying piμBl(xy)pimin{μAl(x),μAl(y)}, piμBu(xy)pimin{μAu(x),μAu(y)}, x,yV.

Now, we give an example of m-PIVFG:(See ).

Figure 3. A 3-PIVFG.

Figure 3. A 3-PIVFG.

Proof

Example 3

Let us consider a 3-PIVFG G=(V,A,B), where A=u0.3,0.5,0.2,0.4,0.5,0.8,v0.3,0.6,0.5,0.6,0.2,0.5,w0.7,0.8,0.4,0.6,0.1,0.5and B=uv0.3,0.5,0.2,0.4,0.2,0.5,vw0.3,0.6,0.4,0.6,0.1,0.5,wu0.3,0.5,0.2,0.4,0.1,0.5

Proof

DEFINITION 3.2

An m-PIVFG G=(V,A,B) of G=(V,E) is said to be complete if piμBl(xy)=min{piμAl(x),piμAl(y)} and piμBu(xy)=min{piμAu(x),piμAu(y)} for every pair of vertices x,yV and for each i=1,2,,m.

Proof

Example 4

Let us consider Example 3, here, p1μBl(uv)=0.3=min{p1μAl(u),p1μAl(v)}={0.3,0.3} p1μBu(uv)=0.5=min{p1μAu(u),p1μAu(v)}={0.5,0.6} p2μBl(uv)=0.2=min{p2μAl(u),p2μAl(v)}={0.2,0.5} p2μBu(uv)=0.4=min{p2μAu(u),p2μAu(v)}={0.4,0.6} p3μBl(uv)=0.2=min{p3μAl(u),p3μAl(v)}={0.5,0.2} p3μBu(uv)=0.5=min{p3μAu(u),p3μAu(v)}={0.8,0.5} Similarly, we get the edges vw and wu. Hence, the graph G is complete, since for all the pair of vertices x,yV the conditions piμBl(xy)=min{piμAl(x),piμAl(y)} and piμBu(xy)=min{piμAu(x),piμAu(y)} hold.

But, for the graph of is not complete. Here, A=u0.3,0.6,0.1,0.4,0.5,0.8,v0.1,1.0,0.2,0.3,0.2,0.5,w0.7,0.8,0.2,0.3,0.1,0.5and B=uv0.3,0.5,0.2,0.4,0.2,0.5,wu0.3,0.50.2,0.4,0.1,0.5 This is not complete m-PIVFG. From the definition of m-PIVFG, there must be an edge between vertices v and w with μ(vw)=0.1,0.8,0.2,0.3,0.1,0.5 . But there is no edge ‘vw’ that ‘s' why the graph is not complete.

Figure 4. A 3-PIVFG G which is not complete.

Figure 4. A 3-PIVFG G which is not complete.

Proof

DEFINITION 3.3

An m-PIVFG G=(V,A,B) of G=(V,E) is said to be strong m-PIVFG if piμBl(xy)=min{piμAl(x),piμAl(y)} and piμBu(xy)=min{piμAu(x),piμAu(y)} for all the edges xyE and for each i=1,2,,m.

Above described example is an example of a strong m-PIVFG. Already, we have discussed that is not complete.

4 Complement of an m-PIVFG

In this present section, first, the complement of m-PIVFG with suitable examples are defined. Then the limitations of the definitions are observed with the help of some examples. After that new modified definition for the complement is developed and is verified with examples.

Proof

DEFINITION 4.1

Let G=(V,A,B) of G=(V,E) be an m-PIVFG. The complement of G is an m-PIVFG G¯=(A¯,B¯), where piμB¯(xy)=[piμB¯l(xy),piμB¯u(xy)], piμB¯l(xy)=min{piμAl(x),piμAl(y)}piμBl(xy), and piμB¯u(xy)=min{piμAu(x),piμAu(y)}piμBu(xy) for each i=1,2,,m and for every x,yV.

Example 5 The following is an example of an m-PIVFG while represents its complement. Let us consider a 3-PIVFG G=(V,A,B), where A=x0.1,0.2,0.2,0.4,0.3,0.5,y0.2,0.4,0.3,0.6,0.3,0.7,z0.2,0.4,0.4,0.6,0.3,0.7and B=xy0.1,0.2,0.1,0.2,0.2,0.3,xz0.1,0.2,0.1,0.3,0.3,0.4. The complement G¯ of G is A¯=x0.1,0.2,0.2,0.4,0.3,0.5,y0.2,0.4,0.3,0.6,0.3,0.7,z0.2,0.4,0.4,0.6,0.3,0.7p1μB¯l(xy)=min{p1μAl(x),p1μAl(y)}p1μBl(xy)=min{0.1,0.2}0.1=0.0p1μB¯u(xy)=min{p1μAu(x),p1μAu(y)}p1μBu(xy)=min{0.2,0.4}0.2=0.0p2μB¯l(xy)=min{p2μAl(x),p2μAl(y)}p2μBl(xy)=min{0.2,0.3}0.1=0.1p2μB¯u(xy)=min{p2μAu(x),p2μAu(y}p2μBu(xy)=min{0.4,0.6}0.2=0.2p3μB¯l(xy)=min{p3μAl(x),p3μAl(y)}p3μBl(xy)=min{0.3,0.3}0.2=0.1p3μB¯u(xy)=min{p3μAu(x),p3μAu(y)}p3μBu(xy)=min{0.5,0.7}0.3=0.2 Similarly for others, Thus, we get B¯=xy0.1,0.2,0.1,0.2,0.2,0.3,yz0.2,0.3,0.3,0.6,0.3,0.7,zx0.0,0.0,0.1,0.1,0.0,0.1. Construction of complements we just stated by the above definition fails for some m-PIVFG. For further illustration, we consider the examples as follows.

Figure 5. A 3-PIVFG.

Figure 5. A 3-PIVFG.

Figure 6. The complement of the 3-PIVFG of .

Figure 6. The complement of the 3-PIVFG of Figure 5.

Example 6 Let us consider a 3-PIVFG G(V,A,B) of G(V,E) (See ), A=x0.1,0.2,0.2,0.4,0.3,0.5,y0.2,0.4,0.3,0.6,0.3,0.7,z0.2,0.3,0.4,0.6,0.3,0.7and B=xy0.1,0.2,0.01,0.2,0.2,0.4,xz0.2,0.3,0.4,0.6,0.3,0.7 The complement G¯ () of G is A¯=<x0.1,0.2,0.2,0.4,0.3,0.5,y0.2,0.4,0.3,0.6,0.3,0.7,z0.2,0.3,0.4,0.6,0.3,0.7B¯=<xy0.0,0.0,0.19,0.0,0.1,0.1,yz0.2,0.3,0.3,0.6,0.3,0.7,zx0.0,0.0,0.1,0.1,0.0,0.1

Here for i=2, p2μBl(xy)=0.19 and p2μBu(xy)=0.0, p2μB(xy)=[0.19,0.0], which is not an interval. So, we can't construct this type of m-PIVFG.

Figure 7. A 3-PIVFG.

Figure 7. A 3-PIVFG.

Figure 8. Complement of the 3-PIVFG of .

Figure 8. Complement of the 3-PIVFG of Figure 7.

Keeping in mind the limitations of definition 9 as demonstrated by example 5, we propose a new definition of the complement of m-PIVFG which is well defined given below.

Proof

DEFINITION 4.2

Let G=(V,A,B) be an m-PIVFG. Also let A and B represent min{piμAl(x),piμAl(y)}piμBl(xy) and min{piμAu(x),piμAu(y)}piμBu(xy), respectively. The complement G¯=(V,A¯,B¯) of G is also an m-PIVFG, where piμB¯(xy)=[piμB¯l(xy),piμB¯u(xy)]=min{piμAl(x),piμAl(y)}piμBl(xy),min{piμAu(x),piμAu(y)}piμBu(xy);if ABmin{piμAu(x),piμAu(y)}piμBu(xy),min{piμAu(x),piμAu(y)}piμBu(xy);if A>B for each i=1,2,,m and for every x,yV.

Example 7 For the above considered 3-PIVFG G=(V,A,B), modified G¯ will be () A¯=x[0.1,0.2],[0.2,0.4],[0.3,0.5], y[0.2,0.4],[0.3,0.6],[0.3,0.7], x[0.2,0.3],[0.4,0.6],[0.3,0.7]B¯=xy[0.0,0.0],[0.0,0.0],[0.1,0.1], yx[0.2,0.3],[0.3,0.6],[0.3,0.7], zx[0.0,0.0],[0.1,0.1],[0.0,0.1]

Proof

DEFINITION 4.3

An m-PIVFG G=(V,A,B) of a crisp graph G(V,E) is called classic m-PIVFG if all its m-pole of all its edge satisfy the condition min{piμAl(x),piμAl(y)}piμBl(xy)min{piμAu(x),piμAu(y)}piμBu(xy) for each i=1,2,,m and for every x,yV.

Figure 9. Modified G¯.

Figure 9. Modified G¯.

Proof

DEFINITION 4.4

Let G=(V,A,B) be an m-PIVFG of a crisp graph G=(V,E). Then the edge xy in G satisfying min{piμAl(x),piμAl(y)}piμBl(xy)min{piμAu(x),piμAu(y)}piμBu(xy), for each i=1,2,,m and for every x,yV are called perfect edges and all other edges xy for which min{piμAl(x),piμAl(y)}piμBl(xy)min{piμAu(x),piμAu(y)}piμBu(xy), are called imperfect edges i=1,2,,m.

Proposition 1:

All the edges of an m-PIVFG are perfect iff m-PIVFG is classic.

Proof Let us consider an m-PIVFG is classic. Then, min{piμAl(x),piμAl(y)}piμBl(xy)min{piμAu(x),piμAu(y)}piμBu(xy), for each i=1,2,,m and for every x,yV, i.e. for each edge this condition satisfies. Hence all of the edges are perfect. The proof of the converse part is straight forward.

In the next section, we study various types of isomorphic property of m-PIVFG with proper examples. Thereafter, we describe some propositions and theorems of m-PIVFG with the proofs.

5. Isomorphic m-PIVFG

Proof

Definition 5.1

Let G1=(V1,A1,B1) of G1=(V1,E1) and G2=(V2,A2,B2) of G2=(V2,E2) be two mPIVFGs. A homomorphism φ:G1G2 is a mapping φ:V1V2 satisfying the following conditions,

  1. 1. piμA1l(x)piμA2l(φ(x)), piμA1u(x)piμA2u(φ(x)), xV1 and for each i=1,2,,m.

  2. 2. piμB1l(xy)piμB2l(φ(x)φ(y)), piμB1u(xy)piμB2u(φ(x)φ(y)), xyE1 and for each i=1,2,,m.

Example 8 Here for any two 3-PIVFG, G1=(V1,A1,B1):A1=v10.2,0.3,0.4,0.8,0.5,0.7,v2<0.2,0.4,0.3,0.9,0.4,0.8,B1=v1v20.2,0.3,0.3,0.7,0.3,0.7 and G2=(V2,A2,B2):A2=vˆ10.2,0.4,0.4,0.9,0.6,0.8,vˆ20.2,0.4,0.4,0.7,0.5,0.9,B2=vˆ1vˆ20.2,0.4,0.3,0.7,0.4,0.8

Consider a mapping φ:V1V2, here, piμA2l(φ(v1))=piμA2l(v1ˆ), piμA2u(φ(v1))=piμA2u(v1ˆ) v1V, piμA1l(v1)piμA2l(φ(v1)), piμA1u(v1)piμA2u(φ(v1)), and also piμB1l(v1v2)piμB2l(φ(v1)φ(v2)), piμB1u(v1v2)piμB2u(φ(v1)φ(v2)) for v1v2E1 and i=1,2,,m. Since all the conditions of homomorphism are hold therefore, there exists a homomorphism φ:G1G2 (See Figures and ).

Proof

DEFINITION 5.2

Let G1=(V1,A1,B1) of G1=(V1,E1) and G2=(V2,A2,B2) of G2=(V2,E2) be two m-PIVFG. An isomorphism φ:G1G2 is a bijective mapping φ:V1V2 satisfying the following conditions,

  1. piμA1l(x)=piμA2l(φ(x)), piμA1u(x)=piμA2u(φ(x)), xV1 and

  2. piμB1l(xy)=piμB2l(φ(x)φ(y)), piμB1u(xy)=piμB2u(φ(x)φ(y)), xyE1 and for each i=1,,2,,m.

The following m-PIVFG depicted in Figures and show that there exists an isomorphism between them by the help of Definition 14.

Figure 10. A 3-PIVFG G1(V1,A1,B1).

Figure 10. A 3-PIVFG G1(V1,A1,B1).

Figure 11. A 3-PIVFG G2(V2,A2,B2).

Figure 11. A 3-PIVFG G2(V2,A2,B2).

Figure 12. A 3-PIVFG G1

Figure 12. A 3-PIVFG G1

Figure 13. A 3-PIVFG G2.

Figure 13. A 3-PIVFG G2.

Example 9 For any two 3-PIVFG G1=(V1,A1,B1) A1=b10.2,0.5,0.3,0.6,0.3,0.7,b20.3,0.4,0.4,0.6,0.4,0.8,b30.4,0.6,0.5,0.6,0.6,0.8,b40.2,0.6,0.4,0.5,0.2,0.7B1=b1b20.2,0.3,0.2,0.5,0.2,0.7,b2b30.2,0.4,0.2,0.5,0.3,0.6,b2b40.2,0.4,0.3,0.4,0.2,0.5 and G2=(V2,A2,B2) A2=bˆ10.3,0.4,0.4,0.6,0.4,0.8,bˆ20.4,0.6,0.5,0.6,0.6,0.8,bˆ30.2,0.6,0.4,0.5,0.2,0.7,bˆ40.2,0.5,0.3,0.6,0.3,0.7B2=bˆ1bˆ20.4,0.6,0.3,0.4,0.2,0.5,bˆ1bˆ40.2,0.4,0.2,0.5,0.3,0.6,bˆ3bˆ40.2,0.6,0.4,0.5,0.2,0.7 We consider a homomorphism (See Figures and ) φ:G1G2 where the mapping φ:V1V2 satisfies the following criteria, piμA1l(b1)=piμA2l(b4)ˆ piμA1l(b2)=piμA2l(b1)ˆ piμA1u(b1)=piμA2u(b4)ˆ piμA1u(b2)=piμA2u(b1)ˆ piμA1l(b3)=piμA2l(b2)ˆ piμA1l(b4)=piμA2l(b3)ˆ piμA1u(b3)=piμA2u(b2)ˆ piμA1u(b4)=piμA2u(b3)ˆ and piμB1l(b1b2)=piμB2l(b4ˆb3ˆ) piμB1l(b2b3)=piμB2l(b1ˆb4ˆ) piμB1u(b1b2)=piμB2u(b4ˆb3ˆ) piμB1u(b2b3)=piμB2u(b1ˆb4ˆ) piμB1l(b2b4)=piμB2l(b1ˆb2ˆ) piμB1u(b2b4)=piμB2u(b1ˆb2ˆ) Therefore, there exists an isomorphism φ:G1G2.

Proof

THEOREM 1

Let G1=(V1,A1,B1) of G1=(V1,E1) and G2=(V2,A2,B2) of G2=(V2,E2) be two complete m-PIVFGs. Then G1 is isomorphic to G2 iff G1¯ is isomorphic to G2¯.

Proof.

Let G1=(V1,A1,B1) is isomorphic to G2=(V2,A2,B2), then there exists a bijective mapping φ:V1V2 satisfying

  1. piμA1l(x)=piμA2l(φ(x)), piμA1u(x)=piμA2u(φ(x)), xV1 and for each i=1,2,,m.

  2. piμB1l(xy)=piμB2l(φ(x)φ(y)), piμB1u(x)=piμB2u(φ(x)φ(y)), xyE1 and for each i=1,,2,,m.

Again from the definition of complement for the complete graph, piμB1¯l(xy)=min{piμA1l(x),piμA1l(y)}=min{piμA2l(φ(x)),piμA2l(φ(y))}=piμB2¯l(φ(x)φ(y)),and piμB1¯u(xy)=min{piμA1u(x),piμA1u(y)}=min{piμA2u(φ(x)),piμA2u(φ(y))}=piμB2¯u(φ(x)φ(y)) xyE1andforeachi=1,2,,m. This implies that G1¯ is isomorphic to G2¯. The proof of the converse part is the same as above.

Proof

DEFINITION 5.3

An m-PIVFG G=(V,A,B) is said to be self complementary if GG¯.

Example 10 Let us consider a 3-PIVFG G=(V,A,B) described by , where A=x0.2,0.4,0.4,0.6,0.2,0.8,y0.2,0.4,0.4,0.6,0.2,0.8,z0.1,0.8,0.2,0.6,0.4,0.6,B=xy0.1,0.2,0.2,0.3,0.1,0.4,xz0.1,0.4,0.2,0.6,0.4,0.6 Complement of G, i.e. G¯=(V,A¯,B¯) (See ) where A¯=x0.2,0.4,0.4,0.6,0.2,0.8>,y0.2,0.4,0.4,0.6,0.2,0.8,z0.1,0.8,0.2,0.6,0.4,0.6and B¯=xy0.1,0.2,0.2,0.3,0.1,0.4,yz0.1,0.8,0.2,0.6,0.4,0.6 Here, we see G is isomorphic to G¯. Hence, G is self-complementary.

Figure 14. A 3-PIVFG G

Figure 14. A 3-PIVFG G

Figure 15. Complement G¯.

Figure 15. Complement G¯.

Proof

PROPOSITION 2

If G=(V,A,B) is a complete m-PIVFG that is then G is self complementary (Figures and ).

Figure 16. A 3-PIVFG G1=(V1,A1,B1).

Figure 16. A 3-PIVFG G1=(V1,A1,B1).

Figure 17. A 3-PIVFG G2=(V2,A2,B2).

Figure 17. A 3-PIVFG G2=(V2,A2,B2).

Proof.

Let G=(V,A,B) be a complete m-PIVFG such that piμBl(xy)=min{piμAl(x),piμAl(y)} and piμBu(xy)=min{piμAu(x),piμAu(y)}, x,yV.

Now piμBl(xy)=min{piμAl(x),piμAl(y)}=min{piμAl(φ(x)),piμAl(φ(y))}=piμB¯l(xy) Similarly, we can prove that piμBu(xy)=piμB¯u(xy) for any xyE. Therefore, G is self-complementary.

Note 1 Let G=(V,A,B) of G=(V,E) be a strong m-PIVFG. Then G¯ is a strong m-PIVFG if piμB¯l(xy)=0;if 0<piμBl(xy)1min{piμAl(x),piμAl(y)};if piμBl(xy)=0piμB¯u(xy)=0;if 0<piμBu(xy)1min{piμAu(x),piμAu(y)};if piμBu(xy)=0

Proof

THEOREM 2

Let G=(V,A,B) be a strong m-PIVFG of the crisp graph G=(V,E) and G¯=(V,A¯,B¯) be the complement of G then,

  1. piμB¯l(xy)=min{piμAl(x),piμAl(y)}piμBl(xy)

  2. piμB¯u(xy)=min{piμAu(x),piμAu(y)}piμBu(xy) for xyE, i=1,2,,m.

Proof.

Let xyE

  1. If 0<piμBl(xy)1 for each i=1,2,,m; then xyE. For i=1,2,,m, as G is strong min{piμAl(x),piμAl(y)}piμBl(xy)=0=piμB¯l(xy). Similarly, if 0<piμBu(xy)1 for each i=1,2,,m; then xyE. For i=1,2,,m, as G is strong, min{piμAu(x),piμAu(y)}piμBu(xy)=0=piμB¯u(xy).

  2. If for i=1,2,,m; piμBl(xy)=0, then min{piμAl(x),piμAl(y)}piμBl(xy)=min{piμAl(x),piμAl(y)}=piμB¯l(xy). Similarly, if for i=1,2,,m; piμBu(xy)=0, then min{piμAu(x),piμAu(y)}piμBu(xy)=min{piμAu(x),piμAu(y)}=piμB¯u(xy). Hence the proof.

Proof

THEOREM 3

Let G be a self complementary strong m-PIVFG, then for xyE, and for each i=1,2,,m xypiμBl(xy)=12xymin{piμAl(x),piμAl(y)} and xypiμBu(xy)=12xymin{piμAu(x),piμAu(y)}.

Proof.

Let G=(V,A,B) be a self-complementary strong m-PIVFG. Then xyE, for each i=1,2,,m, piμBl(xy)=min{piμAl(x),piμAl(y)} and piμBu(xy)=min{piμAu(x),piμAu(y)} and there exists an isomorphism φ:GG¯ such that

  1. piμAl(x)=piμA¯lφ(x), piμAu(x)=piμA¯uφ(x) xV.

  2. piμBl(xy)=piμB¯l(φ(x)φ(y)), piμBu(x)=piμB¯u(φ(x)φ(y)) x,yV and for i=1,2,,m. Let xyE and for i=1,2,,m, then by the Definition 2, piμB¯l(φ(x)φ(y))=min{piμAl(φ(x)),piμAl(φ(y))}piμBl(φ(x)φ(y)). That is, piμBl(xy)=min {piμAl(φ(x)),piμAl(φ(y)}piμBl(φ(x)φ(y))piμBl(xy)+piμBl(φ(x)φ(y))=min {piμAl(φ(x)),piμAl(φ(y)} . Therefore, xypiμBl(xy)+xypiμBl(φ(x)φ(y))=xymin{piμAl(φ(x)),piμAl(φ(y))}=xymin{piμAl(x),piμAl(y)}2xypiμBl(xy)=xymin{piμAl(x),piμAl(y)}xypiμBl(xy)=12xymin{piμAl(x),piμAl(y)}. Similarly we can prove, xypiμBu(xy)=12xymin{piμAu(x),piμAu(y)}. Hence, the result.

Proof

THEOREM 4

Let G=(V,A,B) be a strong m-PIVFG of G=(V,E). If piμBl(xy)=12min{piμAl(x),piμAl(y)} and piμBu(xy)=12min{piμAu(x),piμAu(y)} xyE, i=1,2,,m, then G is self-complementary.

Proof.

Let G=(V,A,B) be a strong m-PIVFG, satisfying piμBl(xy)=12min {piμAl(x),piμAl(y)} and piμBu(xy)=12min{piμAu(x),piμAu(y)}, xyE, i=1,2,,m, then the identity mapping I:VV is an isomorphism from G to G¯ . Clearly I satisfies the condition of vertices for isomorphism, that is, piμAl(x)=piμA¯l(I(x)) and piμAu(x)=piμA¯u(I(x))  xV. And by the Theorem 2, xyE and i=1,2,,m, piμBl(I(xy))=piμB¯l(xy)=min {piμAl(x),piμAl(y)}piμBl(xy)=min{piμAl(x),piμAl(y)}12min{piμAl(x),piμAl(y)}=12min{piμAl(x),piμAl(y)}=piμBl(xy). That is, piμB¯l(xy)=piμBl(xy). Similarly, piμB¯u(xy)=piμBu(xy), xyE, i=1,2,,m. That imply I satisfies also the condition of edges for isomorphism. Therefore, GG¯. That is G is self-complementary.

Proof

THEOREM 5

Let G1=(V1,A1,B1) and G2=(V2,A2,B2) be two strong m-PIVFG. Then G1G2 iff G1¯G2¯.

Proof.

Assume that G1=(V1,A1,B1) and G2=(V2,A2,B2) be two strong m-PIVFG and let us assume G1G2. Then by definition, there exists a bijective mapping φ:V1V2 satisfying

  1. piμA1l(x)=piμA2l(φ(x)), piμA1u(x)=piμA2u(φ(x))  xV1 and

  2. piμB1l(xy)=piμB2l(φ(x)φ(y)), piμB1u(xy)=piμB2u(φ(x)φ(y)), xyE1 and for each i=1,2,,m.

Case I: For i=1,2,,m and for every xyE1. If piμB1u(xy)=0thenpiμB1¯l(xy)=min {piμA1l(x),piμA1l(y)}=min {piμA2l(φ(x)),piμA2l(φ(y))}=piμB2¯l(φ(x)φ(y))andpiμB1¯u(xy)=min{piμA1u(x),piμA1u(y)}=min{piμA2u(φ(x)),piμA2u(φ(y))}=piμB2¯u(φ(x)φ(y))xyE1and for each. …  …  …  …  …  …  …  …  …  …  … ..

Case II: If for 0<piμB1l(xy)1 and 0<piμB1u(xy)1 then, 0<piμB2l(φ(x)φ(y))1 and 0<piμB2u(φ(x)φ(y))1. So, piμB1¯l(xy)=0=piμB2¯l(φ(x)φ(y)) and piμB1¯u(xy)=0=piμB2¯u(φ(x)φ(y)) xyE1 and for each i=1,2,,m. Hence, G1¯G2¯.

Conversely, let G1¯G2¯, then there exists a bijective mapping φ:V1V2 satisfying

  1. piμA1¯l(x)=piμA2¯l(φ(x)),piμA1¯u(x)=piμA2¯u(φ(x)),

  2. piμB1¯l(xy)=piμB2¯l(φ(x)φ(y)),piμB1¯u(xy)=piμB2¯u(φ(x)φ(y)).

Case I: If xyE1 and for each i=1,2,,m, piμB1l(xy)=0, then piμB2¯l(φ(x)φ(y))=piμB1¯l(xy)=min {piμA1l(x),piμA1l(y)}=min {piμA1¯l(x),piμA1¯l(y)}=min {piμA2¯l(φ(x),piμA2¯l(φ(y)}=min {piμA2l(φ(x),piμA2l(φ(y))}. Again, piμB2¯l(φ(x)φ(y))=min{piμA2l(φ(x)),piμA2l(φ(y))}piμB2l(φ(x)φ(y)). So, piμB2l(φ(x)φ(y))=0=piμB1l(xy) for i=1,2,,m.

Case II: If for i=1,2,,m, 0<piμB1l(xy)1 then, piμB2¯l(φ(x)φ(y))=piμB1¯l(xy))=0. Thus, piμB2l(φ(x)φ(y))=min{piμA2l(φ(x),piμA2l(φ(y)}0=min{piμA2l(φ(x),piμA2l(φ(y)}=piμB1l(xy). Similarly we can prove, piμB2u(φ(x)φ(y))=piμB1u(xy). Hence, G1G2.

Proof

DEFINITION 5.4

Let G1=(V1,A1,B1) of G=(V1,E1) and G2=(V2,A2,B2) of G=(V2,E2) be two m-PIVFG. A weak isomorphism φ:G1G2 is a bijective mapping φ:V1V2 satisfying the following conditions,

  1. φ is homomorphism

  2. piμA1l(x)=piμA2l(φ(x)), piμA1u(x)=piμA2u(φ(x)) for each xV1 and for each i=1,2,,m, i.e. the weight of the nodes of the intervals are preserved but the weight of the edges are not necessarily preserved.

Example 11 Let us consider any two 3-PIVFGs G1=(V1,A1,B1):A1=b10.2,0.5,0.3,0.6,0.3,0.7,b20.3,0.4,0.4,0.6,0.4,0.8,b30.4,0.6,0.5,0.6,0.6,0.8B1=b1b20.2,0.5,0.3,0.5,0.3,0.7,b2b30.3,0.4,0.4,0.5,0.4,0.7G2=(V2,A2,B2):A2=bˆ10.2,0.5,0.3,0.6,0.3,0.7,bˆ20.3,0.4,0.4,0.6,0.4,0.8,bˆ30.4,0.6,0.5,0.6,0.6,0.8B2=bˆ1bˆ20.2,0.4,0.3,0.6,0.3,0.7,bˆ2bˆ30.3,0.4,0.4,0.5,0.4,0.7 We define a mapping φ:V1V2 such that φ(b1)=b1ˆ, φ(b2)=b2ˆ, φ(b3)=b3ˆ, piμA1l(b1)=piμA2l(b1)ˆ, piμA1l(b2)=piμA2l(b2)ˆ, piμA1u(b1)=piμA2u(b1)ˆ, piμA1u(b2)=piμA2u(b2)ˆ, piμA1l(b3)=piμA2l(b3)ˆ, piμA1u(b3)=piμA2u(b3)ˆ for biV1, but, piμB1l(b1b2)piμB2l(φ(b1)φ(b2)), piμB1l(b2b3)piμB2l(φ(b2)φ(b3)), piμB1u(b1b2)piμB2u(φ(b1)φ(b2)) piμB1u(b2b3)piμB2u(φ(b2)φ(b3)). Since all the conditions satisfied, thus, G1 is weak-isomorphic to G2.

Proof

THEOREM 6

Let us consider a weak isomorphism φ:GG¯, then for xyE, and for each i=1,2,,m, xypiμBl(xy)12xymin{piμAl(x),piμAl(y)}andxypiμBu(xy)12xymin{piμAu(x),piμAu(y)}

Proof.

Let us consider a weak isomorphism φ from G=(V,A,B) to it's complement G¯ i.e. φ:GG¯. Then φ:GG¯ such that

  1. piμAl(x)=piμA¯lφ(x), piμAu(x)=piμA¯uφ(x)xV

  2. piμBl(xy)piμB¯l(φ(x)φ(y)), piμBu(x)piμB¯u(φ(x)φ(y))xyE and for i=1,2,,m. Now, piμBl(xy)piμB¯l(φ(x)φ(y))=min{piμAl(φ(x)),piμAl(φ(y))}piμBl(φ(x)φ(y)) or, piμBl(xy)+piμBl(φ(x)φ(y))min{piμAl(φ(x)),piμAl(φ(y))}.

Taking summation both sides, xypiμBl(xy)+xypiμBl(φ(x)φ(y))xymin{piμAl(φ(x)),piμAl(φ(y))}=xymin{piμAl(x),piμAl(y)}or, 2xypiμBl(xy)xymin{piμAl(x),piμAl(y)}or,xypiμBl(xy)12xymin{piμAl(x),piμAl(y)}.  Similarly we can prove, xypiμBu(xy)12xymin{piμAu(x),piμAu(y)}. Hence, the result.

Proof

THEOREM 7

Let G=(V,A,B) be an m-PIVFG of G=(V,E). If piμBl(xy)12min{piμAl(x),piμAl(y)} and piμBu(xy)12min{piμAu(x),piμAu(y)} xyE, i=1,2,,m, then G has a weak isomorphism φ from G to it's complement G¯.

Proof.

Let G=(V,A,B) be an m-PIVFG, satisfying piμBl(xy)12min{piμAl(x),piμAl(y)} and piμBu(xy)12min{piμAu(x),piμAu(y)}, xyE, i=1,2,,m, then the identity mapping I:VV satisfies the condition piμAl(x)=piμA¯l(I(x)) and piμAu(x)=piμA¯u(I(x))  xV and, xyE and i=1,2,,m, piμB¯l(I(x)I(y))=piμB¯l(xy)=min{piμAl(x),piμAl(y)}piμBl(xy)min{piμAl(x),piμAl(y)}12min{piμAl(x),piμAl(y)}=12min{piμAl(x),piμAl(y)}piμBl(xy). That is, piμB¯l(I(x)I(y))piμBl(xy). Similarly, piμB¯u(I(x)I(y))piμBu(xy), xyE, i=1,2,,m. That imply I satisfies also the condition for weak isomorphism from G to it's complement G¯. Hence, G has a weak isomorphism φ from G to it's complement G¯.

Proof

DEFINITION 5.5

Let G1=(V1,A1,B1) of G=(V1,E1) and G2=(V2,A2,B2) of G=(V2,E2) be two m-PIVFGs. A co-weak isomorphism φ:G1G2 is a bijective mapping φ:V1V2 satisfying the following conditions,

  1. φ is homomorphism.

  2. piμB1l(xy)=piμB2l(φ(x)φ(y)), piμB1u(x)=piμB2u(φ(x)φ(y)), xyE1 and for each i=1,2,,m.

Example 12 Let us consider any two 3-PIVFGs G1=(V1,A1,B1):A1=b10.2,0.5,0.3,0.6,0.3,0.7,b20.3,0.6,0.4,0.6,0.4,0.8,b30.4,0.6,0.5,0.6,0.6,0.8B1=b1b20.2,0.3,0.3,0.5,0.5,0.7,b2b30.3,0.4,0.4,0.5,0.4,0.7G2=(V2,A2,B2):A2=bˆ10.3,0.5,0.4,0.6,0.4,0.8,bˆ20.2,0.3,0.3,0.7,0.4,0.8,bˆ30.2,0.4,0.4,0.6,0.3,0.8B2=bˆ1bˆ20.3,0.4,0.4,0.5,0.4,0.7,bˆ2bˆ30.2,0.3,0.4,0.6,0.3,0.8 Here, we define a mapping φ:V1V2 like φ(b1)=b3ˆ, φ(b2)=b2ˆ, φ(b3)=b1ˆ, piμA1l(b1)piμA2l(b3)ˆ, piμA1l(b2)piμA2l(b2)ˆ, piμA1u(b1)piμA2u(b3)ˆ, piμA1u(b2)piμA2u(b2)ˆ, piμA1l(b3)piμA2l(b1)ˆ, piμA1u(b3)piμA2u(b1)ˆ, for biV1,i=1,2,3. Thus, φ:G1G2 is a co-weak isomorphism (See Figures and ).

Figure 18. A 3-PIVFG G1=(V1,A1,B1).

Figure 18. A 3-PIVFG G1=(V1,A1,B1).

Figure 19. A 3-PIVFG G2=(V2,A2,B2).

Figure 19. A 3-PIVFG G2=(V2,A2,B2).

Proof

THEOREM 8

Let us consider a co-weak isomorphism φ:GG¯, then for xyE, and for each i=1,2,,m,xypiμBl(xy)12xymin{piμAl(x),piμAl(y)}andxypiμBu(xy)12xymin{piμAu(x),piμAu(y)}

Proof.

Let us consider a co-weak isomorphism φ from G=(V,A,B) to it's complement G¯ i.e. φ:GG¯ . Then φ:GG¯ such that

  1. piμAl(x)piμA¯lφ(x), piμAu(x)piμA¯uφ(x) xV

  2. piμBl(xy)=piμB¯l(φ(x)φ(y)), piμBu(x)=piμB¯u(φ(x)φ(y)) xyE and for each i=1,2,,m. Now, piμBl(xy)=piμB¯l(φ(x)φ(y))=min{piμAl(φ(x)),piμAl(φ(y))}piμBl(φ(x)φ(y)) or, piμBl(xy)+piμBl(φ(x)φ(y))=min{piμAl(φ(x)),piμAl(φ(y))}. Taking summation both sides, Similarly we can prove, xypiμBu(xy)12xymin{piμAu(x),piμAu(y)}. Hence, the result.

6. Application

Fuzzy graphs have many applications for problems concerning group structures, solving fuzzy intersection equations, etc. An m-PFG has applications in decision-making problems including co-operative games, medical diagnosis, signal processing, pattern recognition, robotics, database theory, expert systems and so on. Also, m-PIVFG is used in many decision-making problems. This happens when a democratic country elects its leader, a group of people decide which movie to watch when a company decides which product design to manufacturing, when a group of judges choose a participate in a reality show, etc. Here we consider an example of a singing competition. Let, V={Aman,Survi,Karan,Piu,Bibhu} be the set of five candidates and J={a,b,c,d} be the set of four judges. They have to select a candidate for the winning trophy depending on their qualities that are voice tone, smoothness, confidence, facial expression, presentation. Suppose Judge ‘a’ is an expert of ‘Sufi music’, judge ‘b’ an expert of ‘Ghazal music’, judge ‘c’ an expert of ‘folk music’ and judge ‘d’ an expert of ‘Indian filmy music’. By default, all the Judges have sufficient knowledge in ‘Classical music’. For each candidate a judge from J can give marks in the form of interval value in [0,1] to xV; such as,

Assuming is constructed by the four Judges. The first column represents the performance marks of Aman given by four Judges. Similar to other columns. On the other hand first row represents the marks to all participants given by First Judge. From this table, one can construct a 5-PIVFG shown in . The first row can be denoted by A(a), i.e. A(a)=0.3,0.6,0.4,0.6,0.2,0.5,0.1,0.7,0.1,0.5. Also, p1A(a)=(0.3,0.6) means a score of the candidate Aman by the judge ‘a’ for the trophy is in between 30 and 60% depending on the qualities Tone, Smoothness, Confidence, Facial expression and Presentation. Similarly for others. Also, an edge represents score by Judges whose fields of music are common. For example Judge ‘a’ who is an expert of ‘Sufi music’ also has ideas on ‘Ghazal music’. Here, the edges ab=0.2,0.3,0.3,0.5,0.2,0.4,0.1,0.6,0.1,0.5 bc=0.1,0.3,0.2,0.4,0.4,0.5,0.2,0.6,0.3,0.7 ad=0.1,0.2,0.2,0.6,0.2,0.5,0.1,0.6,0.1,0.5 cd=0.1,0.2,0.2,0.5,0.3,0.4,0.2,0.6,0.3,0.6 bd=0.1,0.2,0.2,0.5,0.3,0.6,0.2,0.6,0.4,0.6

Figure 20. For the graph G1.

Figure 20. For the graph G1.

Table 5. Marks given to each candidate.

The judges give marks to the singers by the following rule:

Marks ={(upper limit of the interval + lower limit of the interval)÷2}×100. Marks of each candidate (vi) given by the judges are listed in following table. Then each pair of judges give rank (Ri) to all the candidates (vi) according to their marks (Tables ).

Table 6. Marks given to each candidate.

Table 7. Rank given to each candidate.

Table 8. Score of each candidate.

Depending on the performance of the competitions, each pair of judges prepared a panel for the candidates. Again, to find the combined rank of each candidate based on the rank of all judges we consider weights for a different rank. Suppose wi be the weights for the rank i. Obviously wi>wj for i<j. Thus the combined rank or say a score of a candidate is given by the formula sj=i×wi. Using this formula the score (sj) of all five candidates are calculated below:

Hence according to the final score, Bibhu get the first position, Karan gets the second position, Piu gets the third position, Survi gets the fourth position and Aman gets the fifth position. The determination of which singer to win the trophy is called the decision-making problem. Moreover, m-PIVFG has applications in different areas of computer science, neural intelligence, astronomy, autonomous system and industrial field and so on.

7. Conclusion and Future Research Direction

We have been seen that IVFG being viewed as a generalization of fuzzy graph and m-PFG also viewed as an extension of bi-polar fuzzy graph. In this study, we have been introduced the m-PIVFG, a generalization of IVFG and m-PFG, and its complements with examples. The definition of complement has been failed in some cases. Therefore, we have been modified the definition with examples. The definitions of homomorphism, isomorphism, weak isomorphism, co-weak isomorphism of m-PIVFG have been defined with proper given examples. Furthermore, we have been stated the complete m-PIVFG and strong m-PIVFG. In fact, some properties related to complements of complete m-PIVFG and strong m-PIVFG have been described. Thereafter, we also have been discussed few properties regarding self-complementary of m-PIVFG.

We should feature that regarding this investigation, there are distinctive developing regions that we need not demonstrate here as they are outside of our feasible region. In any case, there can be interesting points for future research; for example, one may examine the m-PIVFG with various kinds of environments [Citation39], e.g. domination, Pythagorean, fuzzy soft graph [Citation40–44], etc. In the future, we shall investigate other results of m-PIVFG and extend them to solve various problems of decision-making problems under different fuzzy environments.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Sanchari Bera

Sanchari Bera is a Research Scholar in the Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore-721102, West Bengal, India. She received her B.Sc (Hons.) and M. Sc. degrees in Mathematics from Raja Narendra Lal Khan Women's College (Autonomous) and Vidyasagar University, West Bengal, India in 2012 and 2014, respectively. Her main research interests include Graph Theory and Fuzzy Graph Theory. She has published two research papers in reputed journals.

Madhumangal Pal

Madhumangal Pal is currently a Professor of Applied Mathematics, Vidyasagar University. He has received Gold and Silver medals from Vidyasagar University for rank first and second in M.Sc. and B.Sc. examinations respectively. Also, he received ‘Computer Division Medal’ from Institute of Engineers (India) in 1996 for best research work. In 2013, he has received Bharat Jyoti Award for the significant contribution in academic. Prof. Pal has successfully guided 34 research scholars for Ph.D. degrees and has published more than 320 articles in international and national journals. His specializations include Algorithmic and Fuzzy Graph Theory, Fuzzy Matrices, Genetic Algorithms and Parallel Algorithms. Prof. Pal is the author of eight text books published from India and United Kingdom and two edited book published by IGI Global, USA. He has published 21 book chapters in several edited books. Prof. Pal completed three research project funded by UGC and DST and one project is going on. Prof. Pal is the Editor-in-Chief of Journal of Physical Sciences', ‘Annals of Pure and Applied Mathematics’, area editor of ‘International Journal of Computational Intelligence Systems (SCI Indexed Journal)’ and member of the editorial Boards of many journals. Also, he has visited China, Greece, London, Taiwan, Malaysia, Thailand, Hong Kong, Dubai and Bangladesh to participated, delivered invited talks and to chair conference event. He is also a member of the American Mathematical Society, USA, Calcutta Mathematical Society, Advanced Discrete Mathematics and Application, Neutrosophic Science International Association, USA, etc. As per Google Scholar, the citation of Prof. Pal is 6233, h-index is 40 and i10-index is 184, as on 25.06.2020. He is the member of several administrative and academic bodies in Vidyasagar University and other institutes/organizations.

References

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  • Samanta S, Pal M. Fuzzy tolerance graph. Int J Latest Trends Mat. 2011;1(2):57–67.
  • Samanta S, Pal M. Fuzzy threshold graph. CIIT Int J Fuzzy Syst. 2011;3(12):360–364.
  • Samanta S, Pal M. Fuzzy -competition graph. Fuzzy Inf Eng. 2013;5(2):191–204.
  • Samanta S, Pal M, Pal A. New concepts of fuzzy planar graph. Int J Adv Res Artif Intell. 2014;3(1):52–59.
  • Talebi AA, Rashmanlou H. Isomorphism on interval valued fuzzy graphs. Ann Fuzzy Math Inform. 2013;6(1):47–58.
  • Ghorai G, Pal M. Some properties of m-polar fuzzy graphs. Pac Sci Rev A: Nat Sci Eng. 2016;18(1):38–46.
  • Ghorai G, Pal M. Some isomorphic properties of m-polar fuzzy graphs with applications. SpringerPlus. 2016;5(1):2104.
  • Saha A, Pal M, Pal TK. Selection of programme slots of television channels for giving advertisement: A graph theoretic approach. Inf Sci (Ny). 2007;177(12):2480–2492.
  • Akram M. Bipolar fuzzy graphs. Inf Sci (Ny). 2011;181(24):5548–5564.
  • Akram M. Bipolar fuzzy graphs with applications. Knowl Based Syst. 2013;39:1–8.
  • Ghorai G, Pal M. Regular product vague graphs and product vague line graphs. Cogent Math. 2016;3(1):1–13.
  • Ghorai G, Pal M. A note on “regular bipolar fuzzy graphs,”. Neural Comput Appl. 2016;21(1):197–205.
  • Ghorai G, Pal M. On degrees of m-polar fuzzy graphs. J Uncertain Syst. 2017;11(4):294–305.
  • Ghorai G, Pal M. Applications of bipolar fuzzy sets in interval graphs. TWMS J Appl Eng Math. 2018;8(2):411–424.
  • Jabbar NA, Naoom JH, Ouda EH. Fuzzy dual graphs. J Al-Nahrain Univ. 2009;12(4):168–171.
  • Sahoo S, Pal M. Intuitionistic fuzzy competition graphs. J Appl Math Comput. 2016;52(1-2):37–57.
  • Ghorai G, Pal M. A study on m-polar fuzzy planar graphs. Int J Comput Sci Math. 2016;7(3):283–292.
  • Gorzalczany MB. A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets System. 1987;21:1–17.
  • Mishra S, Pal A. Product of interval-valued intuitionistic fuzzy graph. Annu Pure Math. 2013;5:37–46.
  • Mishra S, Pal A. Regular interval-valued intuitionistic fuzzy graph. J Inf Math Sci. 2017;9:609–621.
  • Pramanik T, Samanta S, Pal M. Interval valued fuzzy planar graphs. Int J Mach Learn Cybern. 2016;7:653–664.
  • Rashmanlou H, Pal M. Balanced interval-valued fuzzy graphs. J Phys Sci. 2013;17:43–57.
  • Rashmanlou H, Pal M. Isometry on interval-valued fuzzy graphs. arXiv Prepr ArXiv. 2014;1405:6003.
  • Bera S, Pal M. Certain types of m-polar interval-valued fuzzy graph. J Intell Fuzzy Syst. 2020. doi: 10.3233/JIFS-191587
  • Hassan N, Sayed OR, Khalil AM, et al. Fuzzy soft expert system in prediction of coronary artery disease. Int J Fuzzy Syst. 2017;19(5):1546–1559.
  • Khalil AM, Li SG, Li HX, et al. Possibility m-polar fuzzy soft sets and its application in decision-making problems. J Intell Fuzzy Syst. 2019;37(1):929–940.
  • Khalil AM, Li SG, Garg H, et al. New operations on interval-valued picture fuzzy set, interval-valued picture fuzzy soft set and their applications. IEEE Access. 2019;7:51236–51253.
  • Khalil AM, Hassan N. Inverse fuzzy soft set and its application in decision making. Int J Inf Deci Sci. 2019;11(1):73–92.
  • Khalil AM, Li SG, Lin Y, et al. A new expert system in prediction of lung cancer disease based on fuzzy soft sets. Soft comput. 2020. doi: 10.1007/s00500-020-04787-x