1 Introduction

In Fuzzy metric spaces we refer to as KM-spaces were initiated by Kramosil and Michálek [1]. The conditions which they formulated were modified later by George and Veeramani [2] via proposing new fuzzy metric spaces called GV-spaces in this paper, with the help of continuous t-norms (see [3]) in order to obtain a Hausdorff topology in fuzzy metrics paces. The paper of Grabiec [4] started the investigations concerning a fixed point theory in fuzzy metric spaces by extending the well-known Banach contraction principle to KM-spaces. Many authors followed this concept by introducing and investigating the different types of fuzzy contractive mappings. Some instances of these works are in [519]. For instance, in 2002, Gregori and Sapena [5] have introduced a kind of contractive mappings and proved fuzzy fixed point theorems in GV-spaces and KM-spaces by using a strong condition for completeness, now called the completeness in the sense of Grabiec or G-completeness, which can be considered a fuzzy version of the Banach contraction theorem. These results have become recently of interest for many authors.

However, as a complete fuzzy metric space in the usual sense, that is, M-complete, i.e., the Cauchy sequence in the usual George and Veeramani’s sense is convergent (defined, for short, M-Cauchy), needs not be G-complete (see [2, 6]). Being aware of this problem, Gregori and Sapena in [5] raised the question whether the fuzzy contractive sequences are M-Cauchy. Very recently, many papers have appeared concerning this subject (see, for example, [710]). In particular, in [10], Wardowski considered a generalization of a fuzzy contractive mapping of Gregori and Sapena in M-complete GV-spaces, also in [7], Mihet defined a new fuzzy contraction called fuzzy ψ-contraction which enlarges the class of fuzzy contractive mappings of Gregori and Sapena and considered these mappings in KM-spaces. They have shown that every generalized fuzzy contractive sequence is M-Cauchy in respective fuzzy metric spaces and proved fuzzy contraction fixed point theorems under different hypotheses. For instance, Mihet assumed that the space under consideration is an M-complete non-Archimedean KM-space. Moreover, he posed an open question whether this fixed point theorem holds if the non-Archimedean fuzzy metric space is replaced by a fuzzy metric space. Vetro [8] introduced a notion of weak non-Archimedean fuzzy metric space and proved common fixed point results for a pair of generalized contractive-type mappings. Wang [9] gave a positive answer for the open question.

Motivated by the works mentioned above, in this paper, we will establish fixed point theorems for weakly fuzzy contractive set-valued mappings on M-complete GV-spaces. To this end, we first introduce a new concept called fw-distance here. Next, using this fw-distance, we introduce a fuzzy ψ-p-contractive set-valued mapping and formulate the conditions guaranteeing the convergence of a fuzzy ψ-p-contractive sequence and the existence of fixed points of a fuzzy ψ-p-contractive set-valued mapping in M-complete GV-spaces and KM-spaces. The established notion of contraction turns out to be a generalization of the fuzzy contractive condition of Gregori and Sapena. Moreover, the paper includes a comprehensive set of examples showing that a fuzzy ψ-p-contractive mapping is fuzzy ψ-contractive and the converse is false. So our results and demonstration are also a generalization of those of [7, 9]. To further illustrate the applicability of the fw-distance, we give characterizations of fuzzy metric completeness, that is, a GV-space X is M-complete if and only if every fuzzy ψ-p-contractive mapping from X into itself has a fixed point in X.

Finally, the idea of the present paper has originated from the study of an analogous problem examined by Suzuki [20] for set-valued contractive mappings and [21] for single-valued contractive mappings on complete determinacy metric spaces.

2 Preliminaries

Let us recall [3] that a continuous t-norm is a binary operation :[0,1]×[0,1][0,1] such that ([0,1],,) is an ordered Abelian topological monoid with unit 1. In this sequel, we always assume that ∗ is positive, i.e., ab>0 for all a,b(0,1].

As examples of t-norm satisfying the conditions above, we enumerate ab=ab, ab=min{a,b} and ab=ab/max{a,b,λ} for 0<λ<1, respectively.

Definition 2.1 [2]

A fuzzy metric space is an ordered triple (X,M,) such that X is a (non- empty) set, ∗ is a continuous t-norm, and M is a fuzzy set on X×X×(0,+) that satisfies the following conditions for all x,y,zX:

  1. (F1)

    M(x,y,t)>0 for all t>0,

  2. (F2)

    M(x,x,t)=1 for all t>0 and M(x,y,t)=1 for some t>0 implies x=y,

  3. (F3)

    M(x,y,t)=M(y,x,t) for all t>0,

  4. (F4)

    M(x,y,t)M(y,z,s)M(x,z,t+s) for all s,t>0 and

  5. (F5)

    M(x,y,):(0,+)[0,1] is continuous.

In the definition of Kramosil and Michalek [1], M is a fuzzy set on X×X×[0,) that satisfies (F3) and (F4), while (F1), (F2), (F5) are replaced by (K1), (K2), (K5), respectively, as follows:

  1. (K1)

    M(x,y,0)=0;

  2. (K2)

    M(x,y,t)=1 for all t>0 if and only if x=y;

  3. (K5)

    M(x,y,):[0,)[0,1] is left continuous.

As we have mentioned, we refer to these spaces as KM-spaces and refer to the spaces given in Definition 2.1 as GV-spaces. In addition, when X is called a fuzzy metric space means, it may be a GV-space or a KM-space.

In this sense, M is called a fuzzy metric on X. Some simple but useful facts are that

  1. (I)

    M(,,t) is a continuous function on X×X for t(0,) and

  2. (II)

    M(x,y,) is nondecreasing for all x,yX.

The first fact for the proof we refer to [[22], Proposition 1]. To prove the second fact, by (F4), we notice that M(x,y,t)M(x,y,s)M(y,y,ts)=M(x,y,s)1=M(x,y,s) for s,t[0,) with t>s.

Let (X,M,) be a GV-space. For t>0 and r(0,1), the open ball B(x,t,r) with center xX is defined by

B(x,t,r)= { y X : M ( x , y , t ) > 1 r } .

A subset AX is called open if for each xA, there exist t>0 and 0<r<1 such that B(x,t,r)A. Let T denote the family of all open subsets of X. Then T is a topology on X induced by the fuzzy metric M. This topology is metrizable (see [23]). Therefore, A closed subset B of X is equivalent to xB if and only if there exists a sequence { x n }B such that { x n } topologically converges to x. In fact, the topological convergence of sequences can be indicated by the fuzzy metric as follows.

Definition 2.2 [2]

Let (X,M,) be a fuzzy metric space.

  1. (i)

    A sequence { x n } in X is said to be convergent to a point xX, denoted by lim n x n =x, if lim n M( x n ,x,t)=1 for any t>0.

  2. (ii)

    A sequence { x n } in X is called Cauchy sequence if for each ε>0 and t>0, there exists n 0 N such that M( x n , x m ,t)>1ε for any m,n n 0 .

  3. (iii)

    A fuzzy metric space (X,M,), in which every Cauchy sequence is convergent, is said to be complete.

There exist two fuzzy versions of Cauchy sequences and completeness, i.e., besides called M-Cauchy sequence and M-completeness in the sense of Definition 2.2, G-Cauchy sequence defined by lim n M( x n + p , x n ,t)=1 for all t,p>0 and corresponding G-completeness introduced by [4]. In [6], the authors have pointed out that a G-Cauchy sequence is not an M-Cauchy in general. It is clear that an M-Cauchy sequence is G-Cauchy, and hence, a fuzzy metric space is M-complete if it is G-complete. From now on, by Cauchy sequence and completeness we mean an M-Cauchy sequence and M-completeness.

We now introduce a new notion as follows.

Definition 2.3 Let (X,M,) be a fuzzy metric space. A fuzzy set P on X×X×(0,) is said to be an fw-distance if the following hypotheses are satisfied:

  1. (w1)

    P(x,y,t)P(y,z,s)P(x,z,t+s) for all x,y,zX and all s,t>0.

  2. (w2)

    For any xX, t(0,), P(x,,t):X[0,1] is upper semicontinuous, and P(x,y,):(0,+)[0,1] is left continuous for x,yX.

  3. (w3)

    Let x,yX. For any ε(0,1) and t>0, there exists δ(0,1) and zX such that P(z,x,t/2)1δ and P(z,y,t/2)1δ imply M(x,y,t)1ε.

Note that neither of the implications P(x,y,t)=1x=y (namely (F2)) necessarily hold, and P is nonsymmetric, i.e., in general, P does not satisfy (F3).

The fuzzy metric M is an fw-distance on X. In fact, (F4) implies that (w1) holds. The properties I and II of M combining conditions (F5) or (K5) guarantee that (w2) is valid. Finally, for any ε(0,1) and t>0, from the properties of ∗, we can take a small enough δ>0 such that (1δ)(1δ)1ε. Now, putting M(z,x,t/2)1δ and M(z,y,t/2)1δ, by means of (F4), we have

M(x,y,t)M(z,x,t/2)M(z,y,t/2)(1δ)(1δ)1ε.

This implies that (w3) holds. However, some other following examples of fw-distances show that the converse is false.

Example 2.4 Let f:X R + be a one-to-one continuous function, and let g: R + [0,+) be an increasing continuous function. Define ab=ab for all a,b[0,1]. Fixed α,β>0, define M and P by, respectively,

M(x,y,t)= ( ( min { f ( x ) , f ( y ) } ) α + g ( t ) ( max { f ( x ) , f ( y ) } ) α + g ( t ) ) β ,P(x,y,t)= ( g ( t ) ( f ( y ) ) α + g ( t ) ) β .

Then M is a fuzzy metric, and (X,M,) is a GV-space (see [24]), P is an fw-distance but not a fuzzy metric on X.

Proof We observe that

P ( x , z , t + s ) = ( g ( t + s ) ( f ( z ) ) α + g ( t + s ) ) β = ( g ( t + s ) ( f ( y ) ) α + g ( t + s ) ) β ( ( f ( y ) ) α + g ( t + s ) ( f ( z ) ) α + g ( t + s ) ) β ( g ( t ) ( f ( y ) ) α + g ( t ) ) β ( g ( s ) ( f ( z ) ) α + g ( s ) ) β .

Hence, P(x,z,t+s)P(x,y,t)P(y,z,s), i.e., (w1) holds. (w2) is valid. Trivial. For any ε(0,1) and t>0, set δ(0,ε/3] and zX such that (1δ)(1δ)1ε and P(z,x,t/2)1δ and P(z,y,t/2)1δ, we can distinguish two cases:

f(x)f(y)andf(y)f(x).

Now, we have, respectively,

M(x,y,t) ( ( f ( x ) ) α + g ( t / 2 ) ( f ( x ) ) α + g ( t / 2 ) ) β ( ( f ( x ) ) α + g ( t / 2 ) ( f ( y ) ) α + g ( t / 2 ) ) β

and

M(x,y,t) ( ( f ( y ) ) α + g ( t / 2 ) ( f ( y ) ) α + g ( t / 2 ) ) β ( ( f ( y ) ) α + g ( t / 2 ) ( f ( x ) ) α + g ( t / 2 ) ) β .

It is easy to verify that in the two cases, the inequality

M(x,y,t)P(z,x,t/2)P(z,y,t/2)(1δ)(1δ)1ε

holds, that is, (w3) is met. This reduces that P is an fw-distance.

However, P is not a fuzzy metric since it is nonsymmetric. □

Example 2.5 Let X=R with the fuzzy metric M(x,y,t)= e | x y | / g ( t ) with g as in Example 2.4. Fixed 0<α<β1. Define P by

P(x,y,t)= e m ( x , y ) / g ( t )

with m(x,y)=max{α(xy),β(yx)} and t>0. Then P is an fw-distance but not a fuzzy metric on (X,M,).

Some properties for the fw-distance are useful in this sequel.

Proposition 2.6 Let (X,M,)’ be a fuzzy metric space, and let P be an fw-distance on X. Then for sequences { x n } and { y n } in X, the function sequences { a n (t)} and { b n (t)} with a n , b n :(0,)[0,1) converging to 0 for t>0, and x,y,zXwe have the following:

  1. (1)

    if, for t>0, P( x n ,y,t/2)1 a n (t/2) and P( x n ,z,t/2)1 b n (t/2) for any nN, then y=z; in particular, if P(x,y,t)=1 and P(x,z,t)=1, then y=z;

  2. (2)

    if, for t>0, P( x n , y n ,t/2)1 a n (t/2) and P( x n ,z,t/2)1 b n (t/2) for any nN, then { y n } converges to z;

  3. (3)

    if, for t>0, P( x n , x m ,t/2)1 a n (t/2) for any n,mN with m>n, then { x n } is a Cauchy sequence;

  4. (4)

    if, for t>0, P(y, x n ,t/2)1 a n (t/2) for any nN, then { x n } is a Cauchy sequence;

  5. (5)

    if xX and { y n } in X with lim n y n =y and P(x, y n ,t)ω for some ω=ω(x)(0,1), then P(x,y,t)ω.

Proof (1) For any ε(0,1) and t>0, let δ=ε. By our assumptions, there exists nN such that a n (t/2)<δ and b n (t/2)<δ which implies that P( x n ,y,t/2)1 a n >1δ and P( x n ,z,t/2)1 b n >1δ for large enough n. In view of (w3), one has M(y,z,t)1ε. Now, the arbitrariness of ε implies that M(y,z,t)=1, i.e., y=z.

(2) Similarly to the argument of (1), for any ε(0,1) and t>0, we can find n 0 N such that M( y n ,z,t)1ε for each n n 0 , that is, lim n y n =z.

(3) For any ε(0,1) and t>0, there exists n 0 N such that a n (t/2)<ε for n n 0 . Let m 1 , m 2 N with m 1 , m 2 >n> n 0 . Then, by means of the assumption of (3), we have P( x n , x m 1 ,t/2)1 a n (t/2) and P( x n , x m 2 ,t/2)1 a n (t/2). (w3) guarantees that M( x m 1 , x m 2 ,t)1ε. From Definition 2.2(ii) { x n } is a Cauchy sequence.

As an analogous argument in (3), we can verify that (4) is valid.

(5) If lim n y n =y and P(x, y n ,t)ω for some ω=ω(x)(0,1), by (w2) P(x,y,t) lim sup n P(x, y n ,t)ω. Therefore, (5) holds. □

3 Fixed point theorems

In the sequel, by CB(X), we denote the collection consisting of all nonempty closed subsets of X (obviously, every closed subset of X is bounded in the sense of fuzzy metric spaces). Let (X,M,) be a fuzzy metric space and T:XCB(X) be a set-valued mapping. An element xX is called a fixed point of T if xTx.

The following collection Ψ of functions is given in [7], that is, ψΨ implies that ψ from [0,1] into itself is continuous, nondecreasing and ψ(t)>t for each t(0,1).

Let ψΨ and P be an fw-distance. The set-valued mapping T is called a fuzzy ψ-p-contractive mapping if the following implication takes place: for any x 1 , x 2 X and y 1 T x 1 , there exists y 2 T x 2 such that P( x 1 , x 2 ,t)>0P( y 1 , y 2 ,t)ψ(P( x 1 , x 2 ,t)) for each t>0. In particular, the fuzzy ψ-M-contraction corresponds to the fuzzy ψ-contraction according to [[7], Definition 3.1]. A fuzzy ψ-p-contractive sequence in X is any sequence { x n } in X such that P( x n + 2 , x n + 1 ,t)ψ(P( x n + 1 , x n ,t)) for all nN and t>0.

Theorem 3.1 Let (X,M,) be a complete fuzzy metric space, and let T be a fuzzy ψ-p-contractive set-valued mapping from X into CB(X). If there exists xX such that P(x,y,t)>0 for some yTx and any t>0, then T has at least a fixed point x 0 X. Moreover, if P( x 0 , x 0 ,t)>0, then P( x 0 , x 0 ,t)=1 for all t>0.

Proof From our assumption, there exists u 0 X such that P( u 0 , u 1 ,t)>0 for some u 1 T u 0 and any t>0. For fixed u 1 , by the contractive condition, there exists u 2 T u 1 such that

P( u 1 , u 2 ,t)ψ ( P ( u 0 , u 1 , t ) ) P( u 0 , u 1 ,t)>0

for all t>0. Applying again the contractive condition for u 1 , u 2 , we can choose u 3 T u 2 such that

P( u 2 , u 3 ,t)ψ ( P ( u 1 , u 2 , t ) ) P( u 1 , u 2 ,t)>0.

Thus, by induction, we obtain a sequence { u n } in X such that u n + 1 T u n and

P( u n , u n + 1 ,t)ψ ( P ( u n 1 , u n , t ) ) P( u n 1 , u n ,t)>0

for every t>0 and nN. Next, for each nN, we prove by induction that, for all kN,

P( u n , u n + k ,t)>0,t>0.
(1)

We have shown that the claim is true for k=1. Assume that P( u n , u n + l ,t)>0 for all t>0 and lN with 1l<k. Then, by virtue of (w1), we have

P( u n , u n + k ,t)P( u n , u n + k 1 ,t/2)P( u n + k 1 , u n + k ,t/2).

Since P( u n , u n + k 1 ,t/2)>0, P( u n + k 1 , u n + k ,t/2)>0, from the fact that ∗ is positive we have

P( u n , u n + k ,t)P( u n , u n + k 1 ,t/2)P( u n + k 1 , u n + k ,t/2)>0

for all t>0, (1) is valid.

Now, any fix t>0. Let a n = a n (t/2)=1 inf m n P( u n , u m ,t/2) for m,nN. Then { a n } is a function from (0,) into [0,1) and

P( u n , u m ,t/2)1 a n

for any n,mN with m>n. We will prove that { a n } converges to 0. To this end, it is sufficient to verify that

lim n c n =1
(2)

with c n = inf m n P( u n , u m ,t/2). For mn+1, by (1) we have

P( u n + 1 , u m ,t/2)ψ ( P ( u n , u m 1 , t / 2 ) ) P( u n , u m 1 ,t/2).

This yields that c n + 1 c n for all nN, i.e., { c n } is a decreasing sequence. So { c n } is convergent. Let lim n c n =p. By virtue of the continuity of ψ, we have pψ(p) which yields that p=1, and hence (2) is valid. Moreover, by virtue of Proposition 2.6(3), we see that { u n } is a Cauchy sequence. Hence { u n } converges to a point v 0 X by the completeness of X.

Fix a large enough nN. Since { u m } converges to v 0 and P( u n ,,t) is upper semicontinuous, we have

P( u n , v 0 ,t) lim sup m P( u n , u m ,t) c n >0.
(3)

This implies that

lim n P( u n , v 0 ,t)=1.
(4)

Again, the contractive hypothesis reduces that there exists w n T v 0 such that P( u n , w n ,t)ψ(P( u n 1 , v 0 ,t))P( u n 1 , v 0 ,t)>0. Consequently, we have a sequence { w n }T v 0 such that P( u n , w n ,t)>0, P( u n , v 0 ,t)>0 for all t>0 and nN. Fix t>0, let

a n =1P( u n , w n ,t/2), b n =1P( u n , v 0 ,t/2).

In view of (4), we obtain that { b n } converges to 0. By this, combining P( u n , w n ,t/2)P( u n 1 , v 0 ,t/2), we have {P( u n , w n ,t/2)} converging to 1, which implies that { a n } converges to 0. By Proposition 2.6(2), { w n } converges to v 0 . Since T v 0 is closed, v 0 T v 0 , i.e., v 0 is a fixed point of T.

Finally, for such v 0 , if P( v 0 , v 0 ,t)>0, there exists v 1 T v 0 such that P( v 0 , v 1 ,t)ψ(P( v 0 , v 0 ,t))P( v 0 , v 0 ,t)>0. Thus, we also have a sequence { v n } in X such that v n + 1 T v n and P( v 0 , v n + 1 ,t)ψ(P( v 0 , v n ,t))P( v 0 , v n ,t)>0 for every nN. Let a n =1P( v 0 , v n ,t/2) for fixed t>0. Repeating the proof process of (2), we can infer that a n 0 as n. By Proposition 2.6(4), { v n } is a Cauchy sequence. Hence { v n } converges to a point x 0 X. Since P( v 0 ,,t) is upper semicontinuous, 1P( v 0 , x 0 ,t) lim sup n P( v 0 , v n ,t)=1, and hence P( v 0 , x 0 ,t)=1 for all t>0. For any nN,

P( u n , x 0 ,t)P( u n , v 0 ,t/2)P( v 0 , x 0 ,t/2)P( u n , v 0 ,t/2)1=P( u n , v 0 ,t/2).

By (4) and Proposition 2.6(1), we have x 0 = v 0 which implies that P( v 0 , v 0 ,t)=1. This proof is complete. □

Example 3.2 Let X=[0,), ab=ab for any a,b[0,1] and M(x,y,t) be given as in Example 2.4 with α=β=1, g(t)=t and f(x)=x. For given λ>0, the set-valued mapping T:XX as follows

Tx={ { x + λ } , x + λ 1 , [ x , x + λ ] , x + λ > 1

has a fixed point in X.

Proof Using similar arguments as the ones in [[12], Theorem 16], one can show that (X,M,) is a complete GV-space. Let ψ(t)= t for t[0,1]. Then ψΨ. Let

P(x,y,t)={ y , 0 y 1 , 1 y , y > 1 , x,yX,t>0.

It is not hard to verify that P is an fw-distance. For any x 1 , x 2 X and y 1 T x 1 , if x 2 +λ1, then x 2 <1 and choose y 2 = x 2 + λ T x 2 , we have

P( y 1 , y 2 ,t)= x 2 + λ > x 2 =ψ ( P ( x 1 , x 2 , t ) ) .

If x 2 +λ>1, choose y 2 = x 2 T x 2 , we have

P( y 1 , y 2 ,t)= x 2 =ψ ( P ( x 1 , x 2 , t ) )

if x 2 1 and

P( y 1 , y 2 ,t)= 1 x 2 =ψ ( P ( x 1 , x 2 , t ) )

if x 2 >1. Consequently, T is ψ-p-contractive and all conditions of Theorem 3.1 are satisfied. Hence, T has a fixed point (in fact, 1T1). □

Remark 3.3 We observe that T in Example 3.2 is not fuzzy ψ-contractive. Hence, there exists a mapping which is fuzzy ψ-p-contractive but not fuzzy ψ-contractive. However, every fuzzy ψ-contractive mapping is obviously fuzzy ψ-p-contractive.

In fact, set λ=0.005 and take x 1 =0.005, x 2 =0.04 in Example 3.2, we have T x 1 = x 1 + λ =0.1, T x 2 = x 2 + λ = 0.045 . Note that

M(0.1,0.2,t)= 0.1 + t 0.2 + t ,M( x 1 , x 2 ,t)=M(0.005,0.04,t)= 0.005 + t 0.04 + t .

Let y 1 =T x 1 =0.1 and y 2 =T x 2 = 0.045 . Then M( y 1 , y 2 ,t)<M(0.1,0.2,t). Take t=1, we have

M(0.1,0.2,1)= 1.1 1.2 < 1.005 1.04 =ψ ( M ( 0.005 , 0.04 , 1 ) ) =ψ ( M ( x 1 , x 2 , t ) ) ,

that is, M( y 1 , y 2 ,1)<ψ(M( x 1 , x 2 ,1)). Consequently, T is not fuzzy ψ-M-contractive.

Let (X,M,) be a fuzzy metric space and T a single-valued mapping from X into itself. T is said to satisfy nonzero property if there exists xX such that P(x,Tx,t)>0 for all t>0.

Corollary 3.4 Let (X,M,) be a complete fuzzy metric space, and the mapping T from X into itself is fuzzy ψ-p-contractive with the fw-distance P satisfying P(x,y,t)>0 for any (x,y,t)X×X×(0,). If T satisfies the nonzero property, then T has a unique fixed point x 0 X. Further, x 0 satisfies P( x 0 , x 0 ,t)=1 for all t>0.

Proof From Theorem 3.1, there exists x 0 X with T x 0 = x 0 and P( x 0 , x 0 ,t)=1 for all t>0. Let y 0 =T y 0 . If p( x 0 , y 0 ,t)<1 then P( x 0 , y 0 ,t)=P(T x 0 ,T y 0 ,t)ψ(P( x 0 , y 0 ,t))>P( x 0 , y 0 ,t)>0. This contradiction implies that p( x 0 , y 0 ,t)=1. So, by P( x 0 , x 0 ,t)=1 and Proposition 2.6(1), we have x 0 = y 0 . □

Remark 3.5 In the case of P=M, T is exactly fuzzy ψ-contractive initiated by Mihet [7]. So Corollary 3.4 is a positive answer for the open question of [7], but also an essential extension and improvement of Theorem 3.1 in [7] (see [25]) and Theorem 3 in [9], also, the corresponding results of [5, 26].

4 Characterizations of completeness

As an application of Corollary 3.4 and the fw-distance, we propose the following profounder result of fuzzy fixed point theory which gives characterizations of the fuzzy metric completeness. We need the following assumption:

ababfor all a,b(0,1].

We first list the following lemmas regarding the fw-distance which plays a key role in this section.

Lemma 4.1 Let X be a GV-space with the fuzzy metric M, let P be an fw-distance on X, and let Q be a function from X×X×(0,+) into [0,1] satisfying (w1), (w2) in Definition  2.3. Suppose that Q(x,y,t)P(x,y,t) for every x,yX, t(0,+). Then Q is also an fw-distance on X. In particular, if Q satisfies (w1), (w2) in Definition  2.3 and Q(x,y,t)M(x,y,t) for every x,yX, t(0,+), then P is an fw-distance on X.

Proof We show that Q satisfies (w3). Let ε(0,1) and t>0. Since P is an fw-distance, there exists a positive number δ(0,1) and zX such that P(z,x,t/2)1δ and P(z,y,t/2)1δ imply that M(x,y,t)1ε. Then Q(z,x,t/2)1δ and Q(z,y,t/2)1δ imply that M(x,y,t)1ε. This proof is complete. □

Lemma 4.2 Let (X,M,) be a GV-space and AX contain at least two points, and c(t)=inf{M(x,y,t):x,yA}>0. Then the fuzzy subset p:X×X×(0,+)[0,1] defined by

p(x,y,t)={ M ( x , y , t ) , x , y A , d ( t ) , others

is an fw-distance on (X,M,), where d(t) is a nondecreasing continuous function with 0<d(t)<c(t).

Proof It is clear that c(t)<1 for t>0 since A contains at least two points. If x,y,zA, we have

P(x,z,t+s)=M(x,z,t+s)M(x,y,t)M(y,z,s)=P(x,y,t)P(y,z,s).

In the other case, without loss of generality, we suppose that xA, then P(x,y,t)=d(t) and P(y,z,s)1. Hence,

P(x,z,t+s)=d(t+s)d(t)1p(x,y,t)p(y,z,s).

Let xX. If ad(t) for some t>0, we have {yX:P(x,y,t)a}=X. Let a>d(t) for all t>0. If xA, then P(x,y,t)a implies that yA. So, we have {yX:P(x,y,t)a}={yX:M(x,y,t)a}A. If xA, we have {yX:P(x,y,t)a}=. In each case, the set {yX:P(x,y,t)a} is closed. Therefore, P(x,,t):X(0,1] is upper semicontinuous. P(x,y,) is obviously continuous.

Let ε>0 and t>0. Then there exists a positive number τ(0,1/3) such that 0<τε<1 sup t > 0 d(t). Let δ=τε. Then P(z,x,t/2)1δ and P(z,y,t/2)1δ imply that x,y,zA. So, we have

M(x,y,t)M(z,x,t/2)M(z,y,t/2)=P(z,x,t/2)P(z,y,t/2) ( 1 δ ) 2 >1ε.

This proof is complete. □

Remark 4.3 If A is a compact subset of X, then c(t)>0 for all t>0. Indeed, suppose that this is not true, then there exists t 0 >0 such that c( t 0 )=0. Thus, for each nN, there exist x n , y n A such that M( x n , y n , t 0 )< 1 n . Since A is compact, there exist the subsequences { x n k }, { y n k } of { x n }, { y n }, respectively, such that lim k x n k =x and lim k y n k =y with x,yA. Note that M is continuous, we have M(x,y, t 0 )= lim k M( x n k , y n k , t 0 )=0, a contradiction. In addition, we observe that M(x,y,) is nondecreasing for any given x,yX. Therefore, c() is nondecreasing, and this guarantees the existence of d(t), say, d(t)=c(t)/2.

Theorem 4.4 Let (X,M,) be a fuzzy metric space. Then X is complete if and only if every fuzzy ψ-p-contractive mapping from X into itself satisfying the nonzero property has a fixed point in X.

Proof Since the ‘only if’ part is proved in Corollary 3.4, we only need to prove the ‘if’ part. Assume that X is not complete. Then there exists a sequence { x n } in X which is Cauchy and does not converge. So, there exists t n >0 such that lim m M( x n , x m , t n )<1 for any nN. Let S x ={t>0: lim m M(x, x m ,t)<1} for any xX. Moreover, we have also lim n lim m M( x n , x m ,t)=1 for all t>0. Thus, any fix iN, for some n i and each 4t S x n i , we can choose x n i + 1 { x n } such that lim m M( x n i + 1 , x m ,t)> lim m [ M ( x n i , x m , 4 t ) ] 1 / 8 . We now obtain a subsequence { x n i }{ x n } such that

lim j M( x n i + 1 , x n j ,t)> lim j [ M ( x n i , x n j , 4 t ) ] 1 / 8 for 4t S x n i .

Let

M sup (x,y,t)={ M ( x , y , t ) , t < sup S x , M ( x , y , sup S x ) , t sup S x

for sup S x <. Then we may assume that there exists a sequence { x n } in X satisfying the following conditions:

  1. (i)

    { x n } is Cauchy;

  2. (ii)

    { x n } does not converge;

  3. (iii)

    lim n M ˆ ( x i + 1 , x n ,t)> lim n [ M ˆ ( x i , x n , 4 t ) ] 1 / 8 M ˆ ( x i , x n ,t) for any iN, t>0, where

    M ˆ (x,y,t)={ M ( x , y , t ) , sup S x = , M sup ( x , y , t ) , sup S x < .

Put A={ x n :nN}. Then A is bounded and closed. We next prove that c(t) given as in Lemma 4.2 is positive. In fact, if c( t 1 )=0 for some t 1 >0, then for every kN, there exists n(k),m(k)N such that M( x n ( k ) , x m ( k ) , t 1 )<1/k which implies that lim k M( x n ( k ) , x m ( k ) , t 1 )=0. On the other hand, since { x n } is a Cauchy sequence, we have lim k M( x n ( k ) , x m ( k ) , t 1 )=1, a contradiction. Hence, c(t)>0 for all t>0.

Let us define the fuzzy set P ˆ on X×X×(0,+) by

P ˆ (x,y,t)={ M ˆ ( x , y , t ) , x , y A , d ( t ) , x A  or  y A ,

where d(t) is an increasing continuous function with 0<d(t) c 2 (t). It is clear that P ˆ is an fw-distance on X by Lemmas 4.1 and 4.2. Further, P ˆ (x,y,t)= P ˆ (y,x,t) for any x,yX and t>0, i.e., P ˆ satisfies the symmetry.

Define a mapping T:XX as follows:

Tx={ x 1 , x A , x i + 1 , x = x i ( i N ) .

Then it is easy to see that T has no fixed point in X. Moreover, from (F1), it follows that P ˆ ( x 1 ,T x 1 ,t)= P ˆ ( x 1 , x 2 ,t)=M( x 1 , x 2 ,t)>0, that is, T satisfies the nonzero property. To complete the proof, it is sufficient to show that T is fuzzy ψ- p ˆ -contractive with ψ(t)= t Ψ. If xA or yA, then

P ˆ (Tx,Ty,t)c(t) d ( t ) =ψ ( P ˆ ( x , y , t ) ) .

Let us assume that x,yA. Then, without loss of generality, we may assume that x= x i , y= x j and i<j. For any t>0, from (iii), combining the monotonicity of M ˆ (x,y,), it follows that

lim n M ˆ ( x i , x n , 2 t ) M ˆ ( x i , x j , t ) lim n M ˆ ( x j , x n , t ) M ˆ ( x i , x j , t ) lim n M ˆ ( x j 1 , x n , t ) M ˆ ( x i , x j , t ) lim n M ˆ ( x i + 1 , x n , t ) M ˆ ( x i , x j , t ) lim n [ M ˆ ( x i , x n , 4 t ) ] 1 / 8 M ˆ ( x i , x j , t ) lim n [ M ˆ ( x i , x n , 2 t ) ] 1 / 8 M ˆ ( x i , x j , t ) lim n M ˆ ( x i , x n , 2 t ) .

This implies that

lim n M ˆ ( x i , x n , 2 t ) M ˆ ( x i , x j ,t).
(5)

On the other hand, by (iii), combining (4) and the symmetry of P ˆ , we have

P ˆ ( T x i , T x j , t ) = P ˆ ( x i + 1 , x j + 1 , t ) = M ˆ ( x i + 1 , x j + 1 , t ) lim n M ˆ ( x i + 1 , x n , t / 2 ) lim n M ˆ ( x j + 1 , x n , t / 2 ) lim n M ˆ ( x i + 1 , x n , t / 2 ) lim n M ˆ ( x j , x n , t / 2 ) lim n M ˆ ( x i + 1 , x n , t / 2 ) lim n M ˆ ( x i + 1 , x n , t / 2 ) [ lim n M ˆ ( x i + 1 , x n , t / 2 ) ] 2 [ lim n M ˆ ( x i , x n , 2 t ) ] 1 / 4 M ˆ ( x i , x j , t ) = ψ ( M ˆ ( x i , x j , t ) ) = ψ ( P ˆ ( x i , x j , t ) ) .

This shows that T is fuzzy ψ- p ˆ -contractive. □

Example 4.5 For any nonempty set X, let us consider the fuzzy metric space (X,M,) with M(x,y,t) as in Example 3.2. Let X a =(a,) for any fixed a>1. Then the fuzzy metric space ( X a ,M,) is not complete.

Proof Consider the mapping Tx= x + λ with 0<λa(a1) and ψ(t)= t , we have ψΨ. Let P(x,y,t)= min { x , y } max { x , y } , we have P(x,y,t)M(x,y,t) for any x,yX and t>0. From Lemma 4.1, it follows that P is an fw-distance in X. Now, we have P(x,Tx,t)= min { x , x + 1 } max { x , x + 1 } >0 for all t>0 and

P(Tx,Ty,t)= x + 1 y + 1 > x y =ψ ( P ( x , y , t ) )

for xy. This implies that T is fuzzy ψ-p-contractive. We assert that T has no fixed point in X a . Indeed, if x=Tx, then x= 1 + 1 + 4 λ 2 a. Consequently, Theorem 4.4 guarantees that ( X a ,M,) is not complete. □