1. Introduction
The concept of metric space has been extensively studied in the literature, among other reasons, due to its usefulness in many fields of Science as Physics, Biology, Computer Science, … Indeed, it is an essential tool to quantify the proximity between objects in a real problem. Nevertheless, sometimes the nature of the problem under consideration requires a way of quantify such a proximity for which the concept of metric is too restrictive. This fact has motivated the introduction of different generalizations of the concept of metric by means of deleting or relaxing some of axioms which define it. Among others, we can find the quasi-metrics, in which the symmetry is not demanded, or the partial metrics, for those the self-distance is not necessary zero. These last ones were introduced by Matthews in [
1] where, in addition, he showed a duality relationship between them and a subclass of quasi-metrics, the so-called weighted quasi-metrics.
Coming back to the restrictiveness of the notion of metric space to be used in many real problems, sometimes the considered problem involves some uncertainty, which makes it more appropriate to provide a way of measuring the proximity between objects framed in the fuzzy setting. In this direction, George and Veeramani introduced, in [
2], a notion of fuzzy metric by slightly modifying a previous one given by Kramosil and Michalek in [
3]. This concept has been extensively studied by different authors, both from the theoretical point of view (see, for instance, Ref. [
4,
5,
6,
7,
8,
9,
10,
11,
12] and references therein) and by its applicability to engineering problems (see, for instance, Ref. [
13,
14,
15,
16,
17]). Different fuzzy concepts, based on the notion of fuzzy metric due to George and Veeramani, have appeared in the literature (see, for instance, Ref. [
9,
18,
19,
20]). In this direction, here we adopt the concept of fuzzy quasi-metric (see Definition 5) appeared in [
18], according to a modern concept of quasi-metric (see [
21]). Additionally, we adopt the concept of fuzzy partial metric (see Definition 6), defined by means of the residuum operator of a continuous
t-norm, appeared in [
9], which, also, is according to the notion of partial metric.
The aim of this paper is to retrieve to the fuzzy setting the duality relationship between quasi-metrics and partial metrics defined on a non-empty set
that was established by Matthews in the classical case. To this end, we introduce a subclass of fuzzy quasi-metrics, the so-called fuzzy weighted quasi-metrics (see Definition 7). Subsequently, we provide a way to construct a fuzzy quasi-metric
on
, from a given fuzzy partial metric space
(see Theorem 2). Furthermore, as in the classical case, we show that
(see Proposition 1), and also that
is weightable (see Theorem 4). On the other hand, to obtain the converse, we construct a fuzzy partial metric
on
, from a given fuzzy weighted quasi-metric space
(see Theorem 3). Besides, we show that
(see Proposition 4). In both cases, we demand on the
t-norm ∗ to be Archimedean. The consistency of our constructions is detailed in Remarks 2 and 3. Several examples are provided for illustrating the theory. It is worth to mentioning that a part of the content of the paper is included in the PhD dissertation of the third author [
22].
The reminder of the paper is organized as follows.
Section 2 compiles the basics used throughout the paper. Subsequently,
Section 3 is devoted to obtain a fuzzy quasi-metric deduced from a fuzzy partial one in such a way that the topology is preserved and, in
Section 4 is approached the conversely case. In
Section 5 a brief discussion is provided. Finally,
Section 6 exposes the conclusions of the present work and some lines of research to continue it.
2. Preliminaries
We begin recalling the notion of quasi-metric space that we manage throughout this paper (see [
18,
21]).
Definition 1. A quasi-metric space is a pair where is a non-empty set, and is a mapping such that, for each , the following conditions are satisfied:
- (Q1)
if and only if for every .
- (Q2)
.
As usual, we also say that q is a quasi-metric on .
In a similar way that a metric, given a quasi-metric space , then q induces a topology on , which has as a base the family of open balls , where , for each .
We continue recalling the notion of partial metric space introduced by Matthews in [
1].
Definition 2. A partial metric space is a pair where is a non-empty set, and is a mapping such that, for each , the following conditions are satisfied:
- (P1)
if and only if .
- (P2)
.
- (P3)
.
- (P4)
.
Again, we also say that p is a partial metric on .
Besides, Matthews showed in [
1] that a partial metric
p on a non-empty set
induces a
topology
on
which has as a base the family of open balls
, where
, for each
.
In addition, Matthews showed a duality relationship between partial metrics and quasi-metrics. Such a relationship is given by the fact that, from each partial metric
p on a non-empty set
we can construct a quasi-metric
on
defining
, for each
. In order to obtain a similar construction in the converse case, Matthews introduced, in [
1], the following notion of weighted quasi-metric space.
Definition 3. A weighted quasi-metric space is a tern , where q is a quasi-metric on and w is a function defined on satisfying, for each , the following conditions:
- (w1)
;
- (w2)
.
Subsequently, Matthews established a way to construct a partial metric from a given weighted quasi-metric space , defining a partial metric on given by , for each .
Moreover, Matthews showed that both constructions preserve the topology. Indeed, given a partial metric space then, . Conversely, given a weighted quasi-metric space then, .
Now, we recall the notion of fuzzy metric space given by George and Veeramani in [
2].
Definition 4. A fuzzy metric space is an ordered triple such that is a (non-empty) set, ∗ is a continuous t-norm (see [23]) and M is a fuzzy set on satisfying, for all and , the following conditions: - (GV1)
- (GV2)
if and only if
- (GV3)
- (GV4)
- (GV5)
The assignment , given by for each , is a continuous function.
As usual, we will say that , or simply M, if confusion does not arise, is a fuzzy metric on .
George an Veeramani showed in [
2] that every fuzzy metric
M on
defines a topology
on
X, which has as a base the family of open balls
, where
for all
,
and
.
In the next, we recall two significant examples of fuzzy metrics given in [
2].
Example 1. Let be a metric space and let the function on defined by Then, is a fuzzy metric space, where denotes the minimum t-norm (i.e., , for each ). is called the standard fuzzy metric induced by d. The topology coincides with the topology on deduced from d.
Example 2. Let be a metric space and let the function on defined by Afterwards, is a fuzzy metric space and will be called the exponential fuzzy metric induced by d. Again, the topology coincides with the topology on deduced from d.
Gregori and Romaguera in [
18] introduced two concepts of fuzzy quasi-metric. Here, we deal with the following concept which is according to Definition 1.
Definition 5. A fuzzy quasi-metric space is a tern , such that is a non-empty set, ∗ is a continuous t-norm and Q is a fuzzy set on satisfying, for all and , the following conditions:
- (QGV1)
;
- (QGV2)
if and only if ;
- (QGV3)
;
- (QGV4)
The assignment , given by for each , is a continuous function.
In such a case, , or simply Q, is called a fuzzy quasi-metric on .
Gregori and Romaguera proved in [
18] that every fuzzy quasi-metric
Q on
generates a
topology
on
that has as a base the family of open sets of the form
, where
for all
,
and
.
Now, we recall the concept of fuzzy partial metric space introduced by Gregori et al. in [
9].
Definition 6. Afuzzy partial metric spaceis an ordered triple , such that is a (non-empty) set, ∗ is a continuous t-norm and P is a fuzzy set on satisfying, for all and , the following conditions:
- (FPGV1)
- (FPGV2)
if and only if
- (FPGV3)
- (FPGV4)
- (FPGV5)
The assignment , given by for each , is a continuous function.
Similarly to the previous cases, Gregori et al. proved in [
9] that that every fuzzy partial metric
P on
generates a
topology
on
which has as a base the family of open sets of the form
, where
for all
,
and
.
In the previous definition,
denotes the residuum operator of the continuous
t-norm ∗ (see, for instance, [
24] in order to find a deeper treatment on it), which can be obtained by next formula:
To finish this section, we recall some aspects on continuous t-norms and their residuum operator, which will be useful later.
First, recall that an additive generator
of a
t-norm ∗ is a strictly decreasing function which is right-continuous at 0, satisfying
, and such that for
we have
and also
where
denotes the pseudo-inverse of the function
(see [
24]).
This concept allows for characterizing a family of continuous t-norms, the so-called Archimedeans (i.e., those continuous t-norms ∗ such that for each ) as shows the next theorem.
Theorem 1. A binary operator ∗ in is a continuous Archimedean t-norm if and only if there exists a continuous additive generator of ∗.
Moreover, an additive generator
of a continuous Archimedean
tnorm ∗ allows us to obtain a simpler formula of the ∗-residuum, as follows:
Note that the pseudo-inverse of a continuous additive generator
is given by
By Formula (
6), we conclude that, for each continuous Archimedean t-norm ∗, it is held
for each
.
Remark 1. Attending to Formula (6), it is obvious that given a continuous Archimedean t-norm ∗, its ∗-residuum is continuous on . Nevertheless, the such an affirmation is not true, in general. Indeed, the residuum operator of the non-Archimedean continuous t-norm is given byand one can easily observe that is not continuous on . Corollary 1. Let ∗ be a continuous Archimedean t-norm, and let be its continuous additive generator. Then, for every , we have that .
3. From Fuzzy Partial Metrics to Fuzzy Quasi-Metrics
In this section, we provide a way of constructing a fuzzy quasi-metric from a fuzzy partial metric. To obtain such an aim, we are based on the classical techniques given by Matthews in [
1].
We begin this section introducing two examples of fuzzy quasi-metric spaces. They generalize, in some sense, the exponential and standard fuzzy metric spaces deduced from a classic metric (see
Section 2). Both examples will be useful later.
Example 3. Let be a quasi-metric space.
- (i)
We define the fuzzy set on , as follows After a tedious computation, one can prove that is a fuzzy quasi-metric space. It will be called the exponential fuzzy quasi-metric space deduced from q.
- (ii)
We define the fuzzy set on as Afterwards, is a fuzzy quasi-metric space (see [18]), where denotes the usual product t-norm (i.e., for each ). It is left to the reader to show that is also a fuzzy quasi-metric space.
Observe that both and are also fuzzy quasi-metric spaces for each continuous t-norm ∗, since for each t-norm ∗.
Now, we show the next theorem.
Theorem 2. Let be a fuzzy partial metric space, where ∗ is a continuous Archimedean t-norm. Then, is a fuzzy quasi-metric space, where is the fuzzy set on given by:for each Proof. We will see that fulfills Definition 5.
- (QGV1)
As , then . Hence, .
- (QGV2)
implies that and for each . Hence, and . Therefore, and . On the other hand, if for some , we have that . Hence, as and , we have that for some , and so .
- (QGV3)
It is straightforward due to axiom (PGV4).
- (QGV4)
By axiom (FPGV5) we have that and are continuous functions on Furthermore, since , on account of Remark 1 we conclude that is a continuous function due to it is a composition of continuous functions.
Hence, is a fuzzy quasi-metric space. □
We cannot remove the condition of being ∗ Archimedean in the previous theorem, as the next example shows.
Example 4. Let . We define the fuzzy set P on as In [9], the authors proved that is a fuzzy partial metric space. Nevertheless, if we define the fuzzy set on by , for each and , then does not satisfy axiom . Indeed, on account of Example 4.2 of [9], we have that Obviously, is not a continuous function.
We illustrate the construction presented in Theorem 2 applying it to some particular cases of fuzzy partial metric space.
Example 5. Let be a partial metric space. First, recall that, following the Matthews’ construction we have that is a quasi-metric on , where for each .
- (i)
By Proposition 3.3 in [9], is a fuzzy partial metric space, where , for each . Since is a continuous Archimedean t-norm then, by Theorem 2, we have that is a fuzzy quasi-metric space, where is given byfor each . It will be called the exponential fuzzy partial metric deduced from p. Recall that an additive generator of is given by , for . So, on account of Formula (6) we have, for each , that Then, for each , we obtain Thus, , for each .
- (ii)
By Proposition 3.4 in [9], is a fuzzy partial metric space, where , for each , and denotes the Hamacher product t-norm, which is given by the following expression:for each . It will be called the standard fuzzy partial metric deduced from p. In [24], it was pointed out that the function is an additive generator of and so, on account of Formula (7), the function is its pseudo-inverse. Attending to these observations and taking into account Formula (6), the expression of the -residuum is given by Because is a continuous Archimedean t-norm then, by Theorem 2, we have that is a fuzzy quasi-metric space, where is given byfor each . On account of Formula (18) we have, for each , that Thus, , for each .
Example 6. Let and consider the partial metric defined on , where for each . We define the fuzzy set on given by It is left to the reader to show that is a fuzzy partial metric space, where denotes the Lukasievicz t-norm, which is given by .
Recall that an additive generator of is given by for each . Accordingly, on account of Formula (6), the residuum operator of is given by Taking into account that is a continuous Archimedean t-norm then, by Theorem 2 we conclude that is a fuzzy quasi-metric space, where is given byfor each and . By Formula (23) we have, for each and , that Thus, , for each and .
Remark 2. Observe, in the previous examples, that we obtain the same fuzzy quasi-metric, both if we construct the exponential (or standard) fuzzy quasi-metric deduced from and if we construct the fuzzy quasi-metric from the exponential (or standard) fuzzy partial metric deduced from p using Theorem 2. This fact shows, in some sense, the consistence of the construction provided in Theorem 2 when comparing with the classical one.
To finish this section, we will show that the topology induced by a fuzzy partial metric coincides with the topology induced by the fuzzy quasi-metric constructed from it by means of Theorem 2.
Proposition 1. Let be a fuzzy partial metric, where ∗ is a continuous Archimedean t-norm. Afterwards, , where is the fuzzy quasi-metric on constructed from P given in Theorem 2.
Proof. Let
be a fuzzy partial metric, where ∗ is a continuous Archimedean t-norm. Taking into account Remark 4.1 in [
9], we have that, for each
,
and
, the open balls are defined, as follows:
It ensures that
if and only if
. Indeed,
Hence, . □
4. From Fuzzy Quasi-Metrics to Fuzzy Partial Metrics
In this section, we tackle the conversely of the construction provided in
Section 3, i.e., we establish a way to construct a fuzzy partial metric from a fuzzy quasi-metric. To achieve such a goal, we begin introducing a notion of fuzzy weighted quasi-metric adapting the classical notion of weighted quasi-metric to our fuzzy context. Besides, some axioms have been added in order to maintain the “essence” of the George and Veeramani’s fuzzification.
Definition 7. We will say that is a fuzzy weighted quasi-metric space, provided that is a fuzzy quasi-metric space and W is a fuzzy set on , satisfying, for each , , the following properties:
- (WGV0)
;
- (WGV1)
.
- (WGV2)
The assignment , given by for each , is a continuous function.
In such a case, the fuzzy set W will be called the fuzzy weight function associated to the fuzzy quasi-metric space .
Moreover, we will say that a fuzzy quasi-metric space is weightable if there exist a weight function satisfying axioms (WGV0)–(WGV2).
After introducing the previous concept we provide, in the next two propositions, examples of fuzzy weighted quasi-metric spaces.
Proposition 2. Let be a weighted quasi-metric space. Then, is a fuzzy weighted quasi-metric space, whereand is the Hamacher product t-norm. Proof. On account of Example 3 (ii), we deduce that is a fuzzy quasi-metric space. Accordingly, we just need to show that satisfies, for each and , axiom (WGV1), since, by definition of , it is not hard to check that (WGV0) and (WGV2) are held,
Let
and
. On the one hand,
Because is a weighted quasi-metric space, then and so . □
Following similar arguments to the ones used in the preceding proof, one can show the next proposition.
Proposition 3. Let be a weighted quasi-metric space. Subsequently, is a fuzzy weighted quasi-metric space, whereand is the usual product t-norm. On account of Definition 7, one can observe that W is defined on according to the George and Veeramani’s context. The following theorem states a way to obtain a fuzzy partial metric from a fuzzy weighted quasi-metric.
Theorem 3. Let be a fuzzy weighted quasi-metric space, where ∗ is a continuous Archimedean t-norm. afterwards, is a fuzzy partial metric space, where is the fuzzy set on , given by: Proof. We will show that every axiom of Definition 6 is satisfied, for each and .
- (PGV1)
Let and . On the one hand, since W is a fuzzy weight function, axiom (WGV0) ensures that . On the other hand, . Thus,
- (PGV2)
Obviously, implies .
Now, suppose that
for some
,
. Afterwards, on the one hand,
Besides, because W is a fuzzy weight function, axiom (WGV1) ensures that . So, .
Because ∗ is an Archimedean t-norm and, and , then . Thus, axiom (QGV2) implies .
- (PGV3)
Let
. Because W is a fuzzy weight function, by axiom
(WGV1), we have that
- (PGV4)
Let and . We will see that the following holds:
To show it, we claim that , for each and .
Fix
and
. First, since ∗ is a continuous Archimedean t-norm, there exists an additive generator
of ∗. Subsequently, using equality (
6) and taking into account that
for each
, we have that
Observe that since . Indeed, if we suppose that then , a contradiction.
Therefore, .
- (PGV5)
The function is continuous because of the continuity of both and , and the continuity of the t-norm ∗.
Hence, is a fuzzy partial metric space. □
In the next example we will show that the assumption on the t-norm, which has to be Archimedean, cannot be removed in Theorem 3. For that purpose, we introduce the following lemma.
Lemma 1. Let be a fuzzy metric space, where ∗ is a continuous integral t-norm (i.e., if and only if ). Then, for every (fixed) , is a fuzzy weighted quasi-metric space, where and .
Proof. Let be a fuzzy metric space, where ∗ is a continuous integral t-norm, and let . Obviously, every is a fuzzy quasi-metric space. Accordingly, we need to prove that is a fuzzy weight function.
- (WGV0)
Suppose that for some and . Because ∗ is integral, our assumption implies that or , which is a contradiction. Hence, .
- (WGV1)
Let and . By axiom (GV3), we have that , so .
- (WGV2)
Obviously, for each the assignment is a continuous function on , since for each .
□
Now, the previous lemma allows for us to introduce the announced (counter) example.
Example 7. Let be the metric space, where and is the usual metric of restricted to .
Consider the stantard fuzzy metric deduced from , where is the minimum t-norm (see [25]) and Then, since is an integral t-norm is a fuzzy weighted quasi-metric space by Lemma 1, where for each . Let , and . We have that If we define , then does not fulfill axiom (PGV2). Indeed, as it has been shown, but .
In the following example, we introduce two fuzzy partial metrics using Proposition 2 and 3 and Theorem 3.
Example 8. Let be a weighted quasi-metric space. Following the Matthews’ construction, we have that is a partial metric on , where for each .
- (i)
By Proposition 2, is a fuzzy weighted quasi-metric space, whereand is the Hamacher product t-norm. Since is a continuous Archimedean t-norm then, by Theorem 3, we have that is a fuzzy partial metric space, where is given byfor each . Then, for each , we have that Thus, , for each .
- (ii)
By Proposition 3, is a fuzzy weighted quasi-metric space, whereand is the usual product t-norm. Since is a continuous Archimedean t-norm then, by Theorem 2, we have that is a fuzzy partial metric space, where is given byfor each . Then, for each , we have that Thus, , for each .
Remark 3. Again, the previous example shows the consistence of the construction provided in Theorem 3 comparing with the classical one. Indeed, we obtain the same fuzzy partial metric, both if we construct the exponential (or standard) fuzzy partial metric deduced from and if we construct the fuzzy partial metric from the exponential (or standard) fuzzy quasi-metric deduced from q while using Theorem 3.
Moreover, the next proposition shows that the topology induced by a fuzzy weighted quasi-metric coincides with the topology induced by the fuzzy partial metric constructed from it applying Theorem 3.
Proposition 4. Let be a fuzzy weighted quasi-metric space, where ∗ is a continuous Archimedean t-norm. Then, , where is the fuzzy partial metric on constructed from Q given in Theorem 3.
Proof. Let
be a fuzzy quasi-metric space, where ∗ is a continuous Archimedean t-norm. On the one hand, for each
,
and
, we have that
On the other hand, by Proposition 1 and Remark 4.1 in [
9] we have that
for each
,
and
.
Moreover, in the demonstration of Theorem 3, . Thus, it is obvious that, for each , and , if and only if . Hence, . □
To finish this section, we tackle a question related with the construction given in Theorem 2. In such a theorem, we provide a way of obtaining a fuzzy quasi-metric from a fuzzy partial one. It is based on the results given by Matthews in [
1] for the classical case. Taking into account that, in the construction of Matthews, the obtained quasi-metric from a partial one turns out to be weightable, we wonder if it is so in the fuzzy context. The next theorem affirmatively answers such a question.
Theorem 4. Let be a fuzzy partial metric space, where ∗ is a continuous Archimedean t-norm. Then, is a fuzzy weighted quasi-metric space, whereand Proof. Let be a fuzzy partial metric space, where ∗ is a continuous Archimedean t-norm. Theorem 2 ensures that is a fuzzy quasi-metric space. So, we just need to show that satisfies, for each and , axioms (WGV0)–(WGV2).
First, observe that ∗ is a continuous Archimedean t-norm, so there exists a continuous additive generator of ∗ Now, fix and
:
- (WGV0)
By definition of additive generator and taking into account Formula (6), since
by axiom
(PGV1), we have that
Hence,
- (WGV1)
As it was exposed above,
Analogously,
By axiom (PGV3), we have that Therefore, .
- (WGV2)
By axiom (PGV5), we deduce that the assignment is a continuous function. Thus, because for each then, the assignment is a continuous function.
Hence, is a fuzzy weighted quasi-metric space. □