ON INTUITIONISTIC PRODUCT FUZZY GRAPHS

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1 ITALIAN JOURNAL OF PURE AND APPLIED MATHEMATICS N ( ) 113 ON INTUITIONISTIC PRODUCT FUZZY GRAPHS Talal AL-Hawary Mathematics Department Yarmouk University Irbid, Jordan Bayan Hourani Department of Mathematics Yarmouk University Irbid-Jordan Abstract. In this paper, we provide three new operations on intuitionistic product fuzzy graphs; namely direct product, semi-strong product strong product.we discuss which of these operations preseverses the notions of strong complete. We also give some neaw properties of balanced intuitionistic fuzzzy graphs. Keywords: Fuzzy product graph, fuzzy intuitionistic product graph, balanced intuitionistic product fuzzy graph. 1. Background In 1736, Euler introduced the concept of graph theory while trying to find a solution to the well known Konigsberg bridge problem. This subject is now considered as a branch of combinatorics. The theory of graph is an extremely useful tool in solving combinatorial problems in areas such as geometry, algebra, number theory, topology, operations research, optimization computer science. The notion of fuzzy set was first introduced in [19] the notion of fuzzy graph was first introduced in [4]. Sense then, several authors explored this type of graphs. Since the notions of degree, complement, completeness, regularity, connectedness many others play very important rules in the crisp graph case, the idea is to see what corresponds to these notions in the case of fuzzy graphs. Several authors introduced studied what they called product fuzzy graphs, see for example [41]. AL-Hawary [32] introduced the concept of balanced fuzzy graphs. He defined three new operations on fuzzy graphs explored what classes of fuzzy graphs are balanced. Since then, many authors have studied the idea of balanced on distinct kinds of fuzzy graphs, see for example [8, 9, 18, 24, 25, 27]. In 1983, Atanassov [16] introduced the concept of intuitionistic fuzzy sets as a generalization of fuzzy sets [17]. Atanassov added a new component in the definition of fuzzy set. The fuzzy sets give the degree of. Corresponding author

2 TALAL AL-HAWARY, BAYAN HOURANI 114 membership of an element in a given set the nonmembership degree equals one minus the degree of membership, while intuitionistic fuzzy sets give both a degree of membership a degree of non-membership which are more-or-less independent from each other. The only requirement is that the sum of these two degrees is not greater than 1. Intuitionistic fuzzy sets have been applied in a wide variety of fields including computer science, engineering, mathematics, medicine, chemistry economics [15, 28]. Parvathy Karunambigai [29] introduced the concept of Intuitionistic fuzzy graph (IFG) elaborately analyzed its components. Articles [16, 20, 22, 28] motivated us to analyze balanced IFGs their properties. Several authors have studied balanced IFGs, see for example [24, 25] balanced product IFGs (PIFGs) were studied by [27, 42]. The idea of balanced came from matroids, see [31, 33, 34, 35, 36, 37, 38, 40, 39]. This paper deals with the significant properties of balanced IFGs. The basic definition theorems needed are discussed in section 2. In Section 3, we define three new operations on PIFGs we discuss which of these operations preserves the notions of strong complete. Section 4 is devoted to providing more new results on PIFGs. We remark that the results in this paper were done in Bayan Hourani masters thesis titled On complete balanced fuzzy graphs under the supervision of Talal Al-Hawary at Yarmouk University in Background A fuzzy subset of a non-empty set V is a mapping σ : V [0, 1] a fuzzy relation µ on a fuzzy subset σ, is a fuzzy subset of V V. All throughout this paper, we assume that σ is reflexive, µ is symmetric V is finite. Definition 1 ([4]). A fuzzy graph with V as the underlying set is a pair G : (σ, µ) where σ : V [0, 1] is a fuzzy subset µ : V V [0, 1] is a fuzzy relation on σ such that µ(x, y) σ(x) σ(y), x, y V, where sts for minimum. The underlying crisp graph of G is denoted by G : (σ, µ ) where σ = sup p(σ) = {x V : σ(x) > 0} µ = sup p(µ) = {(x, y) V V : µ(x, y) > 0}. H = (σ, µ ) is a fuzzy subgraph of G if there exists X V such that σ : X [0, 1] is a fuzzy subset µ : X X [0, 1] is a fuzzy relation on σ such that µ(x, y) σ(x) σ(y), x, y X. Definition 2 ([41]). An intuitionistic fuzzy graph (simply, IFG) is of the form G : (V, E) where (i) V = {ν 0, ν 1,..., ν n } such that µ 1 :V [0, 1] γ 1 : V [0, 1], denotes the degree of membership non-membership of the element v i V, respectively 0 µ 1 (ν i ) + γ 1 (ν i ) 1, ν i V, (i = 1, 2,..., n),

3 ON INTUITIONISTIC PRODUCT FUZZY GRAPHS 115 (ii) E V V where µ 2 : V V [0, 1] γ 2 : V V [0, 1] are such that µ 2 (ν i, ν j ) min[µ 1 (ν i ), µ 1 (ν j )], γ 2 (ν i, ν j ) max[γ 1 (ν i ), γ 1 (ν j )] 0 µ 2 (ν i, ν j )+γ 2 (ν i, ν j ) 1, for every (ν i, ν j ) E, (i, j = 1, 2,..., n). Definition 3 ([41]). An IFG H = ( V, É) is said to be an Intuitionistic fuzzy subgraph (IFSG) of the IFG G : (γ 1 ; µ 1, γ 2 ; µ 2 ) if (i) V V, where µ 1i = µ 1i, γ 1i = γ 1i, ν i V, i = 1, 2, 3,..., n. (ii) É E, where µ 2 ij = µ 2ij, γ 2ij γ 2ij, (υ i, ν j ) É, i, j = 1, 2,..., n. Corollary 1 ([30]). The complement of an IFG, G : (V, E) is an IFG, G c : (V c, E c ), where (i) V c = V, (ii) µ c 1i = µ 1i γ c 1i = γ 1i, i = 1, 2,..., n, (iii) µ c 2ij = min(µ 1i, µ 1j ) µ 2ij γ c 2ij = max(γ 1i, γ 1j ) γ 2ij, i, j = 1, 2,..., n. Definition 4 ([30]). An IFG, G : (V, E) is said to be complete IFG if µ 2ij = min(µ 1i, µ 1j ) γ 2ij = max(γ 1i, γ 1j ), ν i, ν j V. Definition 5 ([30]). An IFG, G : (V, E) is said to be strong IFG if µ 2ij = min(µ 1i, µ 1j ) γ 2ij = max(γ 1i, γ 1j ), ν i, ν j E. Definition 6 ([24]). Let G 1 : (V 1, E 1 ) G 2 : (V 2, E 2 ) be two IFG s. An isomorphism between G 1 G 2 (denoted by G 1 G 2 ) is a bijective map h : V 1 V 2 which satisfies µ 1 (ν i ) = µ 1 (h(ν i )), ν 1 (ν i ) = ν 1 (h(ν i )), µ 2 (ν i, ν j ) = µ 2 (h(ν i ), h(ν j )) γ 2 (ν i, ν j ) = γ 2 (h(ν i ), h(ν j )), ν i, υ j V. Definition 7 ([24]). The density of an IFG, G : (V, E) is D(G) = (D µ (G), D γ (G)) where D µ (G) = 2 (ν i,ν j ) V (µ 2(ν i, ν j )) (ν i,ν j ) E (µ 1(ν i ) µ 1 (ν j )) D γ (G) = 2 (ν i,ν j ) V (γ 2(ν i, ν j )) (ν i,ν j ) E (γ 1(ν i ) γ 1 (ν j )).

4 TALAL AL-HAWARY, BAYAN HOURANI 116 Definition 8 ([24]). An IFG, G : (V, E) is balanced if D(H) D(G), that is D µ (H) D µ (G), D γ (H) D γ (G), non-empty subgraphs H of G. Definition 9 ([25]). Let G 1 : (V 1, E 1 ) G 2 : (V 2, E 2 ) be an IFG S, where V = V 1 V 2 E = {(x 1, y 1 )(x 2, y 2 ) : (x 1, x 2 ) E 1, (y 1, y 2 ) E 2 }. Then the direct product of G 1 G 2 is an IFG denoted by G 1 G 2 = (V, E), where (µ 1 µ 1 )(x 1, y 1 ) = µ 1 (x 1 ) µ 1 (y 1 ), (x 1, y 1 ) V 1 V 2, (γ 1 γ 1 )(x 1, y 1 ) = γ 1 (x 1 ) γ 1 (y 1 ), (x 1, y 1 ) V 1 V 2, (µ 2 µ 2 )(x 1, y 1 )(x 2, y 2 ) = µ 2 (x 1, x 2 ) µ 2 (y 1, y 2 ), (x 1, x 2 ) E 1, (y 1, y 2 ) E 2, (γ 2 γ 2 )(x 1, y 1 )(x 2, y 2 ) = γ 2 (x 1, x 2 ) γ 2 (y 1, y 2 ), (x 1, x 2 ) E 1, (y 1, y 2 ) E 2. Definition 10 ([25]). Let G 1 : (V 1, E 1 ) G 2 : (V 2, E 2 ) be an IFG S, where V = V 1 V 2 E = {(x, x 2 )(x, y 2 ) : x V 1, (x 2, y 2 ) E 2 } {(x 1, y 1 )(x 2, y 2 ) : (x 1, x 2 ) E 1, (y 1, y 2 ) E 2 }. Then the semi-strong product of G 1 G 2 is an IFG denoted by G 1 G 2 = (V, E), where (µ 1 µ 1 )(x 1, x 2 ) = µ 1 (x 1 ) µ 1 (x 2 ), (x 1, x 2 ) V 1 V 2, (γ 1 γ 1 )(x 1, x 2 ) = γ 1 (x 1 ) γ 1 (x 2 ), (x 1, x 2 ) V 1 V 2, (µ 2 µ 2 )(x, x 2 )(x, y 2 ) = µ 1 (x) µ 2 (x 2, y 2 ), x V 1, (x 2, y 2 ) E 2, (γ 2 γ 2 )(x, x 2 )(x, y 2 ) = γ 1 (x) γ 2 (x 2, y 2 ), x V 1, (x 2, y 2 ) E 2, (µ 2 µ 2 )(x 1, x 2 )(y 1, y 2 ) = µ 2 (x 1, x 2 ) µ 2 (y 1, y 2 ), (x 1, x 2 ) E 1, (y 1, y 2 ) E 2, (γ 2 γ 2 )(x 1, x 2 )(y 1, y 2 ) = γ 2 (x 1, x 2 ) γ 2 (y 1, y 2 ), (x 1, x 2 ) E 1, (y 1, y 2 ) E 2. Definition 11 ([25]). Let G 1 : (V 1, E 1 ) G 2 : (V 2, E 2 ) be an IFG S, where V = V 1 V 2 E = {(x, y 1 )(x, y 2 ) : x V 1, (y 1, y 2 ) E 2 } {(x 1, y)(x 2, y) : y V 2, (x 1, x 2 ) E 1 } {(x 1, y 1 )(x 2, y 2 ) : (x 1, x 2 ) E 1, (y 1, y 2 ) E 2 } Then the strong product of G 1 G 2 is an IFG denoted by G 1 G 2 : (V, E), where µ 1 µ 1 )(x 1, x 2 ) = µ 1 (x 1 ) µ 1 (x 2 )forevery(x 1, x 2 ) V 1 V 2, (γ 1 γ 1 )(x 1, x 2 ) = γ 1 (x 1 ) γ 1 (x 2 )forevery(x 1, x 2 ) V 1 V 2, (µ 2 µ 2 )(x, x 2 )(x, y 2 ) = µ 1 (x) µ 2 (x 2, y 2 ), x V 1, (x 2, y 2 ) E 2, (γ 2 γ 2 )(x, x 2 )(x, y 2 ) = γ 1 (x) γ 2 (x 2, y 2 ), x V 1, (x 2, y 2 ) E 2, (µ 2 µ 2 )(x 1, x 2 )(y 1, y 2 ) = µ 2 (x 1, x 2 ) µ 2 (y 1, y 2 ), (x 1, x 2 ) E 1, (y 1, y 2 ) E 2, (γ 2 γ 2 )(x 1, x 2 )(y 1, y 2 ) = γ 2 (x 1, x 2 ) γ 2 (y 1, y 2 ), (x 1, x 2 ) E 1, (y 1, y 2 ) E 2, (µ 2 µ 2 )(x 1, y)(x 2, y) = µ 2 (x 1, x 2 ) µ 2 (y), (x 1, x 2 ) E 1, y V 2, (γ 2 γ 2 )(x 1, y)(x 2, y) = γ 2 (x 1, x 2 ) γ 2 (y), (x 1, x 2 ) E 1, y V 2.

5 ON INTUITIONISTIC PRODUCT FUZZY GRAPHS Product intuitionistic fuzzy graph (PIFG) The first definition of product intuitionistic fuzzy graph was introduced by Vinoth Geetha in [27]. In this section, we recall some necessary definitions related to our work. Definition 12 ([27]). Let G : (V, E) be an IFG. If µ 2 (ν i, ν j ) µ 1 (ν i )µ 1 (ν j ) γ 2 (ν i, ν j ) γ 1 (ν i )γ 1 (ν j ), (ν i, ν j ) V, the intuitionistic fuzzy graph is called product intuitionistic fuzzy graph of G (simply, PIFG). Definition 13 ([24]). A PIFG G : (V, E) is said to be complete product if µ 2 (ν i, ν j ) = µ 1 (ν i )µ 1 (ν j ) γ 2 (ν i, ν j ) = γ 1 (ν i )γ 1 (ν j ), ν i, ν j V. Definition 14 ([24]). The complement of a PIFG G : (V, E) is G c : (V c, E c ) wherev c =V, µ c 1i = µ 1i γ c 1i = γ 1i, i = 1, 2,...n, µ c 2ij = µ 1(ν i )µ 1 (ν j ) µ 2 (ν i, ν j ) γ c 2ij = γ c 1(ν i )γ c 1(ν j ) γ c 2(ν i, ν j ), i, j = 1, 2,...n. Definition 15 ([25]). The density of a PIFG G : (V, E) is defined by D(G) = (D µ (G), D γ (G)) where D µ (G) = 2 (µ 2(ν i, ν j )) ν i,ν j E (µ 1(ν i )µ 1 (ν j )), D γ (G) = 2 (γ 2(ν i, ν j )) ν i,ν j E (γ 1(ν i )γ 1 (ν j )). Definition 16 ([25]). A PIFG G : (V, E) is balanced if D(H) D(G), that is, D µ (H) D µ (G), D γ (H) D γ (G),, subgraph H of G. 4. Operations on PIFGs In this section, we define the operations of direct product, semi-strong product strong product on PIFG S we study some results related to balanced PIFG S. Definition 17. Let G 1 : (V 1, E 1 ) G 2 : (V 2, E 2 ) be PIFG S, where V = V 1 V 2 E = {(u 1, v 1 )(u 2, v 2 ) : (u 1, u 2 ) E 1, (v 1, v 2 ) E 2 }. Then the direct product of G 1 G 2 is a PIFG denoted by G 1 G 2 : (V, E) where (µ 1 µ 1 )(u 1, v 1 ) = µ 1 (u 1 ) µ 1 (v 1 ), (u 1, v 1 ) V 1 V 2, (γ 1 γ 1 )(u 1, v 1 ) = γ 1 (u 1 ) γ 1 (v 1 ), (u 1, v 1 ) V 1 V 2, (µ 2 µ 2 )(u 1, v 1 )(u 2, v 2 ) = µ 2 (u 1, u 2 ) µ 2 (v 1, v 2 ), (u 1, u 2 ) E 1, (v 1, v 2 ) E 2

6 TALAL AL-HAWARY, BAYAN HOURANI 118 (γ 2 γ 2 )(u 1, v 1 )(u 2, v 2 ) = γ 2 (u 1, u 2 ) ν 2 (v 1, v 2 ), (u 1, u 2 ) E 1, (v 1, v 2 ) E 2. Definition 18. Let G 1 : (V 1, E 1 ) G 2 : (V 2, E 2 ) be PIFG S, where V = V 1 V 2 E = {(u, u 2 )(u, v 2 ) : u V 1, (u 2, v 2 ) E 2 } {(u 1, v 1 )(u 2, v 2 ) : (u 1, u 2 ) E 1, (v 1, v 2 ) E 2 }. Then the semi-strong product of G 1 G 2 is a PIFG denoted by G 1 G 2 = (V, E) where (µ 1 µ 1 )(u 1, u 2 ) = µ 1 (u 1 ) µ 1 (u 2 ), (u 1, u 2 ) V 1 V 2, (γ 1 γ 1 )(u 1, u 2 ) = γ 1 (u 1 ) γ 1 (u 2 ), (u 1, u 2 ) V 1 V 2, (µ 2 µ 2 )(u, u 2 )(u, v 2 ) = µ 2 1(u) µ 2 (u 2, v 2 ), u V 1, (u 2, v 2 ) E 2, (γ 2 γ 2 )(u, u 2 )(u, v 2 ) = γ 2 1(u) γ 2 (u 2, v 2 ), u V 1, (u 2, v 2 ) E 2, (µ 2 µ 2 )(u 1, u 2 )(v 1, v 2 ) = µ 2 (u 1, u 2 ) µ 2 (v 1, v 2 ), (u 1, u 2 ) E 1, (v 1, v 2 ) E 2 (γ 2 γ 2 )(u 1, u 2 )(v 1, v 2 ) = γ 2 (u 1, u 2 ) γ 2 (v 1, v 2 ), (u 1, u 2 ) E 1, (v 1, v 2 ) E 2. Definition 19. Let G 1 : (V 1, E 1 ) G 2 : (V 2, E 2 ) be PIFG S, where V = V 1 V 2 E = {(u, v 1 )(u, v 2 ) : u V 1, (v 1, v 2 ) E 2 } {(u 1, v)(u 2, v) : v V 2, (u 1, u 2 ) E 1 } {(u 1, v 1 )(u 2, v 2 ) : (u 1, u 2 ) E 1, (v 1, v 2 ) E 2 }. Then the strong product of G 1 G 2 is a PIFG denoted by G 1 G 2 = (V, E) where (µ 1 µ 1 )(u 1, u 2 ) = µ 1 (u 1 ) µ 1 (u 2 ) (u 1, u 2 ) V 1 V 2, (γ 1 γ 1 )(u 1, u 2 ) = γ 1 (u 1 ) γ 1 (u 2 ) (u 1, u 2 ) V 1 V 2, (µ 2 µ 2 )(u, u 2 )(u, v 2 ) = µ 2 1(u) µ 2 (u 2, v 2 ) u V 1, (u 2, v 2 ) E, (γ 2 γ 2 )(u, u 2 )(u, v 2 ) = γ 2 1(u) γ 2 (u 2, v 2 )) u V 1, (u 2, v 2 ) E 2, (µ 2 µ 2 )(u 1, u 2 )(v 1, v 2 ) = µ 2 (u 1, u 2 ) µ 2 (v 1, v 2 ) (u 1, u 2 ) E 1, (v 1, v 2 ) E 2, (γ 2 γ 2 )(u 1, u 2 )(v 1, v 2 ) = γ 2 (u 1, u 2 ) γ 2 (v 1, v 2 ) (u 1, u 2 ) E 1, (v 1, v 2 ) E 2, (µ 2 µ 2 )(u 1, v)(u 2, v) = µ 2 (u 1, u 2 ) µ 2 2(v) (u 1, u 2 ) E 1, v V 2, (γ 2 γ 2 )(u 1, v)(u 2, v) = γ 2 (u 1, u 2 ) γ 2 2(v) (u 1, u 2 ) E 1, v V 2. Theorem 1. Let G 1 : (V 1, E 1 ) G 2 : (V 1, E 1 ) be strong PIFG S. Then G 1 G 2 is strong.

7 ON INTUITIONISTIC PRODUCT FUZZY GRAPHS 119 Proof. If (u 1, v 1 )(u 2, v 2 ) E, then since G 1 G 2 are strong PIFG S, then (µ 2 µ 2 )(u 1, v 1 )(u 2, v 2 ) = µ 2 (u 1, u 2 ) µ 2 (v 1, v 2 ) = µ 1 (u 1 )µ 1 (u 2 ) µ 1 (v 1 ) µ 1 (v 2 ) = (µ 1 µ 2 )((u 1, v 1 )(u 2, v 2 )), (γ 2 γ 2 )(u 1, v 1 )(u 2, v 2 ) = γ 2 (u 1, u 2 ) γ 2 (v 1, v 2 ) Therefore, G 1 G 2 is strong. = γ 1 (u 1 )γ 1 (u 2 ) γ 1 (v 1 ) γ 1 (v 2 ) = (γ 1 γ 1 )((u 1, v 1 )(u 2, v 2 )). Theorem 2. Let G 1 : (V 1, E 1 ) G 2 : (V 1, E 1 ) be strong PIFG s. Then G 1 G 2 is strong. Proof. If (u, v 1 )(u, v 2 ) E, then since G 1 G 2 are strong, then (µ 2 µ 2 )(u, v 1 )(u, v 2 ) = µ 1 (u) 2 µ 2 (v 1, v 2 ) = µ 1 (u)µ 1 (u) µ 1 (v 1 ) µ 1 (v 2 ) = (µ 1 µ 2 )((u, v 1 )(u, v 2 )), (γ 2 γ 2 )(u, v 1 )(u, v 2 ) = γ 1 (u) 2 γ 2 (v 1, v 2 ) = γ 1 (u)γ 1 (u) γ 1 (v 1 ) γ 1 (v 2 ) = (γ 1 γ 1 )((u, v 1 )(u, v 2 )). If (u 1, v 1 )(u 2, v 2 ) E, then since G 1 G 2 are strong, then (µ 2 µ 2 )(u 1, v 1 )(u 2, v 2 ) = µ 2 (u 1, u 2 ) µ 2 (v 1, v 2 ) = µ 1 (u 1 )µ 1 (u 2 ) µ 1 (v 1 ) µ 1 (v 2 ) = (µ 1 µ 2 )((u 1, v 1 )(u 2, v 2 )), (γ 2 γ 2 )(u 1, v 1 )(u 2, v 2 ) = γ 2 (u 1, u 2 )γ 2 (v 1, v 2 ) Hence G 1 G 2 is strong. = γ 1 (u 1 )γ 1 (u 2 ) γ 1 (v 1 ) γ 1 (v 2 ) = (γ 1 γ 1 )((u 1, v 1 )(u 2, v 2 )). Theorem 3. Let G 1 : (V 1, E 1 ) G 2 : (V 1, E 1 ) be strong PIFG S. Then G 1 G 2 is strong.

8 TALAL AL-HAWARY, BAYAN HOURANI 120 Proof. If (u, v 1 )(u, v 2 ) E, then since G 1 G 2 are strong, then (µ 2 µ 2 )(u, v 1 )(u, v 2 ) = µ 1 (u) 2 µ 2 (v 1, v 2 ) = µ 1 (u)µ 1 (u) µ 1 (v 1 ) µ 1 (v 2 ) = (µ 1 µ 2 )((u, v 1 )(u, v 2 )), (γ 2 γ 2 )(u, v 1 )(u, v 2 ) = γ 1 (u) 2 γ 2 (v 1, v 2 ) = γ 1 (u)γ 1 (u) γ 1 (v 1 ) γ 1 (v 2 ) = (γ 1 γ 1 )((u, v 1 )(u, v 2 )). If (u 1, v)(u 2, v) E, then since G 1 G 2 are strong, then (µ 2 µ 2 )(u 1, v)(u 2, v) = µ 2 (u 1, u 2 ) µ(v) 2 = µ 1 (u 1 )µ 1 (u 2 ) µ 1 (v) µ 1 (v) = (µ 1 µ 2 )((u 1, v)(u 2, v)), (γ 2 γ 2 )(u 1, v)(u 2, v) = γ 1 (u 1, u 2 )γ 2 (v, v) = γ 1 (u 1 )γ 1 (u 2 ) γ 1 (v) γ 1 (v) = (γ 1 γ 1 )((u 1, v)(u 2, v)). If (u 1, v 1 )(u 2, v 2 ) E, then since G 1 G 2 are strong, then (µ 2 µ 2 )(u 1, v 1 )(u 2, v 2 ) = µ 2 (u 1, u 2 ) µ 2 (v 1, v 2 ) = µ 1 (u 1 )µ 1 (u 2 ) µ 1 (v 1 ) µ 1 (v 2 ) = (µ 1 µ 2 )((u 1, v 1 )(u 2, v 2 )), (γ 2 γ 2 )(u 1, v 1 )(u 2, v 2 ) = γ 2 (u 1, u 2 )γ 2 (v 1, v 2 ) Hence G 1 G 2 is strong. From Theorem 1 Theorem 3, we get, = γ 1 (u 1 )γ 1 (u 2 ) γ 1 (v 1 ) γ 1 (v 2 ) = (γ 1 γ 1 )((u 1, v 1 )(u 2, v 2 )). Corollary 2. Let G 1 : (V 1, E 1 ) G 2 : (V 1, E 1 ) be complete PIFG S. Then G 1 G 2 G 1 G 2 are strong. We remark that the above result need not be true for G 1 G 2 since G 1 G 2 is never complete by its definition.

9 ON INTUITIONISTIC PRODUCT FUZZY GRAPHS Balanced PIFG S Balanced PIFGs were defined by Karunambigai, Sivasankar Palanivel in [27] some properties on PIFG were established. In this section, we examine many of the results that have not been studied. Lemma 1. Let G : (V, E) be a self-complementary PIFG. Then µ 2 (ν i, ν j ) = 1 2 γ 2 (ν i, ν j ) = 1 2 µ 1 (ν i )µ 2 (ν j ), γ 1 (ν i )γ 1 (ν j ). Proof. Let G : (V, E) be a self-complementary PIFG. Then by Definition of G c, V c = V, µ c 1i = µ 1i γ c 1i = γ 1i, i = 1, 2,..., n, µ c 2 (h(ν i), h(ν j )) = (µ 1 (h(ν i ), µ 1 (h(ν j )) µ 2 (h(ν i ), h(ν j ) γ c 2 (h(ν i), h(ν j )) = (γ 1 (h(ν i ), γ 1 (h(ν j )) γ 2 (h(ν i ), h(ν j )), i, j = 1, 2,..., n, µ c 2 (h(ν i), h(ν j )) = µ 2 (ν i, ν j ). Now µ 2 (ν i, ν j ) + µ 2 (h(ν i ), h(ν j ) = µ 1 (ν i )µ 1 (ν j ). Thus So Also, Thus So 2 µ 2 (ν i, ν j ) = µ 1 (ν i )µ 1 (ν j ). µ 2 (ν i, ν j ) = 1 2 µ 1 (ν i )µ 1 (ν j ). γ 2 (ν i, ν j ) + γ 2 (h(ν i ), h(ν j ) = γ 1 (ν i )γ 1 (ν j ). 2 γ 2 (ν i, ν j ) = γ 1 (ν i )γ 1 (ν j ). γ 2 (ν i, ν j ) = 1 2 γ 1 (ν i )γ 1 (ν j ). Theorem 4. Let G : (V, E) be a PIFG G c : (V c, E c ) be its complement. Then D(G) + D(G c ) (2, 2).

10 TALAL AL-HAWARY, BAYAN HOURANI 122 Proof. Let G : (V, E) be a PIFG G c : (V c, E c ) be its complement. Let H be a non-empty fuzzy subgraph of G. Since G is PIFG µ c 2(ν i, ν j ) = µ 1 (ν i )µ 1 (ν j ) µ 2 (ν i, ν j ), Thus So C µ c 2(ν i, ν j ) + µ 2 (ν i, ν j ) = µ 1 (ν i )µ 1 (ν j ). C µc 2 (ν i, ν j ) C µ 1(ν i )µ 1 (ν j ) + µ 2(ν i, ν j ) µ 1(ν i )µ 1 (ν j ) = 1. Hence Therefore, Also So Hence Therefore, 2 C µc 2 (ν i, ν j ) C µ 1(ν i )µ 1 (ν j ) + 2 µ 2(ν i, ν j ) µ 1(ν i )µ 1 (ν j ) = 2. 2 C µc 2 (ν i, ν j ) C µ 1(ν i )µ 1 (ν j ) + 2 µ 2(ν i, ν j ) µ 1(ν i )µ 1 (ν j ) 2 C µc 2 (ν i, ν j ) ν i,ν j E C µ 1(ν i )µ 1 (ν j ) + 2 µ 2(ν i, ν j ) ν i,ν j E µ 1(ν i )µ 1 (ν j ). C γ c 2(ν i, ν j ) + γ c 2(ν i, ν j ) = γ 1 (ν i )γ 1 (ν j ) γ 2 (ν i, ν j ), µ c 2(ν i, ν j ) + µ 2 (ν i, ν j ) = µ 1 (ν i )µ 1 (ν j ). γ 2 (ν i, ν j ) = γ 1 (ν i )γ 1 (ν j ). C γc 2 (ν i, ν j ) C γ 1(ν i )γ 1 (ν j )) + γ 2(ν i, ν j ) γ 1(ν i )γ 1 (ν j ) = 1 2 C γc 2 (ν i, ν j ) C γ 1(ν i )γ 1 (ν j ) + 2 γ 2(ν i, ν j ) γ 1(ν i )γ 1 (ν j ) = 2 2 C γc 2 (ν i, ν j ) C γ 1(ν i )γ 1 (ν j ) + 2 γ 2(ν i, ν j ) γ 1(ν i )γ 1 (ν j ) 2 C γc 2 (ν i, ν j ) ν i,ν j E C γ 1(ν i )γ 1 (ν j ) + 2 γ 2(ν i, ν j ) ν i,ν j E γ 1(ν i )γ 1 (ν j ). Theorem 5. Let G : (V, E) be a self-complementary PIFG. Then D(G) (1, 1).

11 ON INTUITIONISTIC PRODUCT FUZZY GRAPHS 123 Proof. D(G) = (D µ (G), D γ (G)) 2 ν = (( i,ν j v µ 2(ν i, ν j ) ν i,ν j E (µ 1(ν i )µ 2 (ν j )), 2 ν i,ν j v γ 2(ν i, ν j ) ν i,ν j E (γ 1(ν i )γ 1 (ν j )) )) ( 2 ν i,ν j v µ 2(ν i, ν j ) ν i,ν j v (µ 1(ν i )µ 2 (ν j )), 2 ν i,ν j v γ 2(ν i, ν j ) ν i,ν j v (γ 1(ν i )γ 1 (ν j )) ). But by Lemma 1, we get D(G) ( ν i,ν j v (µ 1(ν i )µ 2 (ν j )) ν i,ν j v (µ 1(ν i )µ 2 (ν j )), ν i,ν j v (γ 1(ν i )γ 1 (ν j )) ν i,ν j v (γ 1(ν i )γ 1 (ν j )) ) = (1, 1). Theorem 6. Let G 1 : (V 1, E 1 ) G 2 : (V 1, E 1 ) be two complete PIFG S Then D(G i ) D(G 1 G 2 ) for i = 1, 2 if only if D(G 1 ) = D(G 2 ) = D(G 1 G 2 ). Proof. If D(G i ) D(G 1 G 2 ) for i = 1, 2, since G 1 G 2 are complete PIFG S, D(G 1 ) = D(G 2 ) = 2. by Corollary 2, G 1 G 2 is strong hence D(G 1 G 2 ) = 2.Thus D(G i ) D(G 1 G 2 ) for i = 1, 2 so D(G 1 ) = D(G 2 ) = D(G 1 G 2 ). The converse is trivial. 6. Acknowledgment The authors would like to thank the referees for useful comments suggestions. References [1] A. Nagoorgani J Malarvizhi., Isomorphism properties on strong fuzzy graphs, Int. J. Algorithms, Comp. Math., 2 (1)(2009), [2] A. Nagoorgani J. Malarvizhi, Isomorphism on fuzzy graphs, Int. J. Comp. Math. Sci., 2(4) (2008), [3] A. Nagoorgani K. Radha, On regular fuzzy graphs, J. Physical Sciences, 12 (2008), [4] A. Rosenfeld, Fuzzy Graphs, in Zadeh. L. A, K. S. Fu, K, Tanaka Shirmura. M (Eds). Fuzzy their applications to cognitive processes, Academic Press. New York, 1975,

12 TALAL AL-HAWARY, BAYAN HOURANI 124 [5] A. Sharma, Padamwar, B., Trends In Fuzzy Graphs, International Journal of Innovative Research in Science, [6] A. Somasundaram, Somasundaram, Domination in fuzzy graphs, Pattern Recognition Letter 19: (1989) [7] F. Harary, Graph Theory, Narosa Addison Wesley, IndianStudent Edition, (1988). [8] H. Rashmanlou M. Pal, Balanced interval-valued Fuzzy Graphs, [9] H. Rashmanlou Y. Benjun, Complete Interval-Valued Fuzzy Graph, Annals of Fuzzy Mathematics Informatics, [10] J.N. Mordeson P.S. Nair, Cycles, cocyles of fuzzy graphs, Information Sciences, 90 (1996), [11] J.N. Mordeson, Fuzzy line graphs, Pattern Recognition Letter, 14 (1993), [12] J.N. Mordeson P.S. Nair, Fuzzy graphs, fuzzy hypergraphs, Physica Verlag, Heidelberg 1998; Second Edition [13] K.R. Bhutani, On automorphism of fuzzy graphs, Pattern Recognition Letter, 9 (1989), [14] K.R. Bhutani A Rosenfeld, Strong arcs in fuzzy graphs, Information Sciences, 152 (2003), [15] K.T. Atanassov, Intuitionistic fuzzy sets: Theory, applications, Studies in fuzziness soft computing, Heidelberg, New York, Physica-Verl., [16] K.T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets Systems, 20 (1986), [17] K.T. Atanassov, G. Pasi, R. Yager V. Atanassova, Intuitionistic fuzzy graph interpretations of multi-person multi-criteria decision making, EUSFLAT Conf., 2003, [18] K.Tatanassov, Intuitionistic fuzzy sets: Theory applications, Studies in fuzziness soft computing, Heidelberg, New York, Physicaverl, [19] L. Zadeh, Fuzzy sets, Inform. Control., 8 (1965), [20] M. Akram, Intuitionistic (S; T )-fuzzy Lie ideals of Lie algebras, Quasigroups, Related Systems, 15 (2007), [21] M. Akram W.A. Dudek, Interval-valued fuzzy graphs, Computers Math. Appl., 61 (2011),

13 ON INTUITIONISTIC PRODUCT FUZZY GRAPHS 125 [22] M. Akram W.A. Dudek, Intuitionistic fuzzy hypergraphs with applications, Information Sci., 218 (2013), [23] M. Akram B. Davvaz, Strong intuitionistic fuzzy graphs, Filomat, 26 (2012), [24] M. G Karunambigai, M. Akram, S. Sivasankar K. Palanive, Balanced intuitionistic fuzzy graphs, Applied Mathematical Sciences, 7 (2012), [25] M. Karunambigai, S. Sivasankar K. Palanivel, Properties of Balanced Intuitionistic Fuzzy Graphs, International Journal of Research in Since, Vol(1), 01-05, January-June (2014). [26] M. Sunitha A. Kumar, Complement of fuzzy graphs, Indian J. Pure Appl. Math., 33 (9)(2002), [27] N. Vinoth Kumar G. Ramani, Product Intuitionistic Fuzzy Graph, International Journal of Computer Applications, Vol 28, No 1. [28] P. Bhattacharya, Some remarks on fuzzy graphs, Pattern Recognition Letter, 6 (1987), [29] R. Parvathi, M. Karunambigai, Intuitionistic fuzzy graphs, Computational Intelligence, Theory applications, , [30] R. Parvathi, M. Karunambigai K. Atanassov, Operations on intuionistic fuzzy graphs, Proceeding of IEEE International Conference Fuzzy Systems (FUZZ-IEEE), (2009), [31] T. Al-Hawary, Certain classes of fuzzy graphs, Eur. J. Pure Appl. Math., 10(3) (2017), [32] T. AL-Hawary, Complete fuzzy graphs, International J. Math Comb., 4(2011), [33] T.A. Al-Hawary, Fuzzy C-flats, FASCICULI MATHEMATICI 50(2013), [34] T. AL-Hawary, Fuzzy Closure Matroids, MATEMATIKA, 32(1)(2016), [35] T.Al-Hawary, Fuzzy flats, Indian J. Mathematics, 55(2) (2013), [36] T.A.Al-Hawary, Fuzzy greedoids, Int. J. Pure Appl. Math., 70, 3 (2011), [37] T.Al-Hawary, On Balanced Graphs Balanced Matroids, Math. Sci. Res. Hot-Line, 4(7) (2000),

14 TALAL AL-HAWARY, BAYAN HOURANI 126 [38] T.Al-Hawary, On K-Balanced Matroids, Mu tah Lil-Buhuth Wad-Dirasat, 16(1), 2001, [39] T. A. Al-Hawary, On Fuzzy Matroids, Inter. J. Math. Cobin., 1 (2012), [40] T. Al-Hawary Bayan Horani, On product fuzzy graphs, Annals of fuzzy mathematics Informatics, 12(2) (2016), [41] V. Ramaswamy B. Poornima, Product fuzzy graphs, International journal of computer science network security, 9 (1) (2009), [42] Z. Ningurm D. Ratnasari, Produk graf fuzzy intuitionistic, Jurnal Watematik, 1(1) (2012). Accepted:

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