1. Introduction
The fuzzy numbers can be treated as the imprecise data. For example, in the financial market, the data may not be precisely measured owing to the fluctuation. However, based on the knowledge of experts, it may be said that each numerical data will be around some certain value. In this case, these imprecise data can be described as the fuzzy numbers. In other words, the fuzzy sets theory may provide a useful tool to tackle this kind of imprecision. The basic ideas and applications of fuzzy sets theory can refer to the monographs [
1,
2,
3,
4,
5,
6].
Let
denote the family of all fuzzy numbers, which will be described in detail below. However, this family
cannot form a vector space. The main reason is that each fuzzy number in
does not have the additive inverse element. Although the space
is not a vector space, the Hahn-Banach extension theorems on
still can be studied by referring to Wu [
7]. On the other hand, the fixed point theorems in fuzzy metric space have been studied in [
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19]. However, the fuzzy metric space is completely different from the near metric space of fuzzy numbers that is adopted in this paper. The purpose of this paper is to study the near fixed point theorem in the near metric space
.
Some of the conventional fixed point theorems were established in normed space. Since is not a vector space, it cannot also be a normed space even though we can define a norm structure on . Therefore, the conventional fixed point theorems will not be applicable in . In this paper, based on the norm structure defined on , the concept of Cauchy sequence in can be similarly defined. In this case, the Banach space of fuzzy numbers can be defined according to the concept of Cauchy sequence. The main aim of this paper is to study and establish the so-called near fixed point theorems in Banach space of fuzzy numbers.
Let
U be a topological space. The
fuzzy subset of
U is defined by a
membership function . The
-level set of
, denoted by
, is defined by
for all
. The 0-level set
is defined as the closure of the set
.
Let ⊙ denote any one of the four basic arithmetic operations
between two fuzzy subsets
and
. The membership function of
is defined by
for all
. More precisely, the membership functions are given by
where
.
Let U be a real topological vector space. We denote by the set of all fuzzy subsets of U such that each satisfies the the following conditions:
is normal, i.e., for some ;
is convex, i.e., the membership function is quasi-concave;
the membership function is upper semicontinuous;
the 0-level set is a compact subset of U.
In particular, if then each element of is called a fuzzy number.
For , it is well-known that, for each , the -level set is a bounded closed interval in , which is also denoted by .
We say
is a
crisp number with value a if and only if the membership function of
is given by
It is clear that each -level set of is a singleton set for . Therefore, the crisp number can be identified with the real number a. In this case, we have the inclusion . For convenience, we also write .
Let
and
be two fuzzy numbers with
and
for
. It is well known that
and, for
,
For any
and
, it is clear to see that
Suppose that
. Then we have
which says that each
-level set
is an “approximated real zero number” with symmetric uncertainty
. It is also clear that the real zero number has the highest membership degree 1 given by
. In this case, we can say that
is a fuzzy zero number.
Equivalently,
if and only if
and
for all
, i.e.,
where the bounded closed interval
is an “approximated real zero number” with symmetric uncertainty
. In other words, each
is a fuzzy zero number. We also call
as the
null set in
. It is also clear that
the crisp number with value 0 is in the null set
. Since the null set
collects all of the fuzzy zero numbers, it can be regarded as a kind of “zero element” of
. The true zero element of
is
, since it is clear that
for any
. On the other hand, since
is not a zero element of
, this says that
cannot form a vector space under the above fuzzy addition and scalar multiplication.
Recall that the (conventional) normed space is based on the vector space. Since is not a vector space, we cannot consider the (conventional) normed space . Therefore we cannot study the fixed point theorem in using the conventional way. In this paper, although is not a vector space, we still can endow a norm to in which the axioms are almost the same as the axioms of conventional norm. The only difference is that the concept of null set is involved in the axioms. Under these settings, we shall study the so-called near fixed point theorem in the near normed space of fuzzy numbers .
Let be a function from into itself. We say that is a fixed point if and only if . Since lacks the vector structure, we cannot expect to obtain the fixed point of the mapping using the conventional ways. In this paper, we shall try to find a fuzzy number satisfying for some . Since the null set can play the role of “zero element” in , i.e., the elements and can be ignored in some sense, this kind of fuzzy number is said to be a near fixed point of the mapping .
In
Section 2, the concept of the null set in fuzzy numbers is proposed, where some interesting properties are derived in order to study the near fixed point theorem. In
Section 3 and
Section 4, the concepts of near metric space and near normed space of fuzzy numbers are proposed, where some interesting properties are also derived for further discussion. In
Section 5, the concepts of Cauchy sequence in metric space and normed space of fuzzy numbers are similarly defined according to the conventional way. In
Section 6, the concept of near fixed point of fuzzy-number-valued function is proposed. Also, three concepts of metric contraction of fuzzy-number-valued functions are proposed. Using the completeness of near metric space of fuzzy numbers, many near fixed point theorems are established. In
Section 7, we also propose three concepts of norm contraction of fuzzy-number-valued functions. In this case, many near fixed point theorems in near Banach space of fuzzy numbers are established.
2. Space of Fuzzy Numbers
Under the fuzzy addition and scalar multiplication in
, it is clear to see that
cannot form a vector space. One of the reasons is that, given any
, the difference
is not a zero element of
. It is clear to see that
is a zero element, since
for any
. However, we cannot have
for any
. We also recall that the following family
is called the null set of
, which can be regarded as a kind of “zero element” of
. In this section, we shall present some properties involving the null set
, which will be used for establishing the so-called near fixed point theorems in
. For further discussion, we present some useful properties.
Proposition 1. The following statements hold true.
for and ;
for and ;
implies .
for with .
Ω is closed under the fuzzy addition; that is, for any .
Since the null set can be regarded as a kind of “zero element”, we can propose the almost identical concept for elements in .
Definition 1. Given any , we say that and are almost identical if and only if there exist such that . In this case, we write .
Given any with , we cannot obtain the equality as the usual sense. As a matter of fact, we can just have . Indeed, since , by adding on both sides, we obtain , where . This says that .
Proposition 2. The binary relation is an equivalence relation.
Proof. For any
,
implies
, which shows the reflexivity. The symmetry is obvious by the definition of the binary relation
. Regarding the transitivity, for
and
, we want to claim
. By definition, we have
for some
for
. Then
which shows
, since
is closed under the fuzzy addition as shown in Proposition 1. This completes the proof. ☐
According to the equivalence relation
, for any
, we define the equivalence class
The family of all classes
for
is denoted by
. In this case, the family
is called the
quotient set of
. We also have that
implies
. In other words, the family of all equivalence classes form a partition of the whole set
. We also remark that the quotient set
is still not a vector space. The reason is
for
, since
for
with
.
4. Near Normed Space of Fuzzy Numbers
Recall that is not a vector space. Therefore we cannot endow a norm to in the conventional way to consider the normed space . However, we can propose the so-called near normed space of fuzzy numbers involving the null set as follows.
Definition 3. Given the nonnegative real-valued function defined on , we consider the following conditions:
- (i)
for any and ;
- (i′)
for any and with .
- (ii)
for any .
- (iii)
implies .
We say that satisfies the null condition when condition (iii) is replaced by if and only if . Different kinds of near normed space of fuzzy numbers are defined below.
We say that is a near pseudo-seminormed space of fuzzy numbers if and only if conditions () and (ii) are satisfied.
We say that is a near seminormed space of fuzzy numbers if and only if conditions (i) and (ii) are satisfied.
We say that is a near pseudo-normed space of fuzzy numbers if and only if conditions (), (ii) and (iii) are satisfied.
We say that is a near normed space of fuzzy numbers if and only if conditions (i), (ii) and (iii) are satisfied.
Now we consider the following definitions:
We say that satisfies the null super-inequality if and only if for any and .
We say that satisfies the null sub-inequality if and only if for any and .
We say that satisfies the null equality if and only if for any and .
For any
, since
, we have
Example 2. For any , we define Then we have the following properties.
if and only if . Indeed, if , then for all , which also says that for all . This shows that . For the converse, if then for all . This shows that . Therefore satisfies the null condition.
For any , i.e., for all , we have
We conclude that is a near normed space of fuzzy numbers such that the null condition and null equality are satisfied.
Proposition 3. Let be a near pseudo-seminormed space of fuzzy numbers such that satisfies the null super-inequality. For any , we have Proof. This completes the proof. ☐
Proposition 4. According to Definitions 1 and 3, the following statements hold true.
- (i)
Let be a near pseudo-seminormed space of fuzzy numbers such that satisfies the null equality. For any , if , then .
- (ii)
Let be a near pseudo-normed space of fuzzy numbers. For any , we have that implies .
- (iii)
Let be a near pseudo-seminormed space of fuzzy numbers such that satisfies the null super-inequality and null condition. For any , we have that implies .
Proof. To prove part (i), we see that
implies
for some
. Therefore, using the null equality, we have
To prove part (ii), suppose that . Then , i.e., for some . By adding on both sides, we have for some , which says that .
To prove part (iii), for
, we have
for some
. Since
is closed under the fuzzy addition, it follows that
for some
. Using the null super-inequality, null condition and (
8), we have
This completes the proof. ☐
6. Near Fixed Point Theorems in Near Metric Space of Fuzzy Numbers
Let be a fuzzy-number-valued function from into itself. We say that is a fixed point of if and only if . The well-known Banach contraction principle presents the fixed point of function when is taken to be a metric space. Since presented in Example 1 is not a metric space (it is a near metric space), we cannot study the Banach contraction principle on this space . In other words, we cannot study the fixed point of contractive mappings defined on into itself in the conventional way. However, we can investigate the so-called near fixed point defined below.
Definition 11. Let be a fuzzy-number-valued function defined on into itself. A point is called a near fixed point of if and only if .
By definition, we see that if and only if there exist such that one of the following equalities is satisfied:
;
;
.
We also see that if then , since the crisp number with value 0 is in and .
Definition 12. A fuzzy-number-valued function is called a metric contraction on if and only if there is a real number such thatfor any . Given any initial element
, we define the iterative sequence
using the fuzzy-number-valued function
as follows:
Under some suitable conditions, we are going to show that the sequence can converge to a near fixed point. If the near metric space of fuzzy numbers is complete, then it is also called a complete near metric space of fuzzy numbers.
Theorem 1. (Near Fixed Point Theorem) Let be a complete near metric space of fuzzy numbers such that d satisfies the null equality. Suppose that the fuzzy-number-valued function is a metric contraction on . Then has a near fixed point satisfying . Moreover, the near fixed point is obtained by the limitin which the sequence is generated according to (14). We also have the following properties. The uniqueness is in the sense that there is a unique equivalence class such that any cannot be a near fixed point.
Each point is also a near fixed point of satisfying and .
If is a near fixed point of , then , i.e., . Equivalently, if and are the near fixed points of , then .
Proof. Given any initial element
, we have the iterative sequence
according to (
14). We are going to show that
is a Cauchy sequence. Since
is a metric contraction on
, we have
For
, using the triangle inequality, we obtain
Since
, we have
in the numerator, which says that
This proves that is a Cauchy sequence. Since the near metric space of fuzzy numbers is complete, there exists such that , i.e., according to Definition 5 and Proposition 6.
We are going to show that any point
is a near fixed point. Now we have
Therefore we obtain
which implies
as
, i.e.,
for any point
.
Now we assume that there is another near fixed point
of
with
, i.e.,
. Then
for some
,
. Since
is a metric contraction on
and
d satisfies the null equality, we obtain
Since , we must have , i.e., , which contradicts . Therefore, any cannot be a near fixed point. Equivalently, if is a near fixed point of , then . This completes the proof. ☐
Example 5. Continued from Example 3, the near metric space of fuzzy numbers is complete. Given a real number , we consider the fuzzy-number-valued function Then, using (16) and (3), we havewhich says that is a metric contraction. Theorem 1 says that has a near fixed point. It is clear to see that the crisp number with value 0 is a near fixed point, since Now, given any , we see that . It is not hard to show that there exists another such that In this case, we havewhich shows that is a near fixed point. Therefore, we obtain the unique equivalence classfor , which illustrates the first property of Theorem 1. Definition 13. A fuzzy-number-valued function is called a weakly strict metric contraction on if and only if the following conditions are satisfied:
, i.e., implies ;
, i.e., implies .
It is clear that if is a metric contraction on , then it is also a weakly strict metric contraction on .
Theorem 2. (Near Fixed Point Theorem)
Let be a complete near metric space of fuzzy numbers. Suppose that the fuzzy-number-valued function is a weakly strict metric contraction on . If forms a Cauchy sequence for some , then has a near fixed point satisfying . Moreover, the near fixed point is obtained by the limitAssume further that d satisfies the null equality. Then we also have the following properties.
The uniqueness is in the sense that there is a unique equivalence class such that any cannot be a near fixed point.
Each point is also a near fixed point of satisfying and .
If is a near fixed point of , then , i.e., . Equivalently, if and are the near fixed points of , then .
Proof. Since is a Cauchy sequence, the completeness says that there exists such that , i.e., according to Definition 5 and Proposition 6. Therefore, given any , there exists an integer N such that for . Since is a weakly strict metric contraction on , we consider the following two cases.
Suppose that
. Then
Suppose that
. Then
The above two cases say that
. Using the triangle inequality, we obtain
which says that
, i.e.,
. This shows that
is a near fixed point.
Assume further that
d satisfies the null equality. We are going to claim that each point
is also a near fixed point of
. Since
, we have
for some
. Then, using the null equality for
d, we obtain
We can similarly obtain
as
. Using the triangle inequality, we have
which says that
. Therefore we conclude that
for any
.
Suppose that
is another near fixed point of
. Then
and
, i.e.,
. Then
for some
for
. Therefore we obtain
This contradiction says that cannot be a near fixed point of . Equivalently, if is a near fixed point of , then . This completes the proof. ☐
Now we consider another fixed point theorem based on the weakly uniformly strict metric contraction which was proposed by Meir and Keeler [
21]. Under the near metric space of fuzzy numbers
, we have
for
. Therefore we propose the following different definition.
Definition 14. A fuzzy-number-valued function is called a weakly uniformly strict metric contraction on if and only if the following conditions are satisfied:
for , i.e., , ;
for , i.e., , given any , there exists such that
Remark 1. We observe that if is a weakly uniformly strict metric contraction on , then is also a weakly strict metric contraction on by taking .
Lemma 1. Let be a weakly uniformly strict metric contraction on . Then the sequenceis decreasing to zero for any . Proof. For convenience, we write for all n. Let .
Suppose that
. By Remark 1 since
is also a weakly strict metric contraction on
, we have
Suppose that
. Then, by the first condition of Definition 14, we have
The above two cases say that the sequence is decreasing. We consider the following cases.
Let
m be the first index in the sequence
such that
. Then we want to claim
. Since
, we have
Using the first condition of Definition 14, we also have
which says that
, i.e.,
. Using the similar argument, we can obtain
and
. Therefore the sequence
is decreasing to zero.
Suppose that
for all
. Since the sequence
is decreasing, we assume that
, i.e.,
for all
n. Then there exists
such that
for some
m, i.e.,
By the second condition of Definition 14, we have
which contradicts
. Therefore we must have
.
This completes the proof. ☐
Theorem 3. (Near Fixed Point Theorem) Let be a complete near metric space of fuzzy numbers with the null set Ω, and let be a weakly uniformly strict metric contraction on . Then has a near fixed point satisfying . Moreover, the near fixed point is obtained by the limit Assume further that d satisfies the null equality. Then we also have the following properties.
The uniqueness is in the sense that there is a unique equivalence class such that any cannot be a near fixed point.
Each point is also a near fixed point of satisfying and .
If is a near fixed point of , then , i.e., . Equivalently, if and are the near fixed points of , then .
Proof. According to Theorem 2 and Remark 1, we just need to claim that if
is a weakly uniformly strict metric contraction, then
is a Cauchy sequence for
. Suppose that
is not a Cauchy sequence. Then there exists
such that, given any
N, there exist
satisfying
. Since
is a weakly uniformly strict metric contraction on
, for
, there exists
such that
Let
. For
, we are going to claim
Indeed, if
, then it is done, and if
, i.e.,
, then
. This proves the statement (
17).
Let
. Since the sequence
is decreasing to zero by Lemma 1, we can find
N such that
. For
, we have
which says that
. Since the sequence
is decreasing by Lemma 1 again, we obtain
For
j with
, using the triangle inequality, we also have
We want to show that there exists
j with
such that
and
Let
for
. Then (
18) and (
19) says that
and
. Let
be an index such that
Then we see that
, since
. By the definition of
, we also see that
and
which also says that
; otherwise,
that is a contradiction. Therefore, from (
22), expression (
21) will be sound if we can show that
. Suppose that this is not true, i.e.,
. We also see that
. Since
is decreasing, from (
19) and (
20), we have
This contradiction says that (
21) is sound. Since
, using (
17), we see that (
21) implies
Therefore, using the triangle inequality, we obtain
which contradicts (
21). This contradiction says that every sequence
is a Cauchy sequence. This completes the proof. ☐
7. Near Fixed Point Theorems in Near Banach Space of Fuzzy Numbers
Let be a near Banach space of fuzzy numbers. In this section, we shall study the near fixed point in .
Definition 15. Let be a near pseudo-seminormed space of fuzzy numbers. A fuzzy-number-valued function is called a norm contraction on if and only if there is a real number such thatfor any . Theorem 4. Let be a near Banach space of fuzzy numbers with the null set Ω such that satisfies the null equality. Suppose that the fuzzy-number-valued function is a norm contraction on . Then has a near fixed point satisfying . Moreover, the near fixed point is obtained by the limit in which the sequence is generated according to (14). We also have the following properties. The uniqueness is in the sense that there is a unique equivalence class such that any cannot be a near fixed point.
Each point is also a near fixed point of satisfying and .
If is a near fixed point of , then , i.e., . Equivalently, if and are the near fixed points of , then .
Proof. Given any initial element
, we are going to show that
is a Cauchy sequence. Since
is a norm contraction on
, we have
For
, using Proposition 3, we obtain
Since
, we have
in the numerator, which says that
This proves that
is a Cauchy sequence. Since
is complete, there exists
such that
We are going to show that any point
is a near fixed point. Now we have
for some
. Using the triangle inequality and the fact of norm contraction on
, we have
which implies
as
. We conclude that
for any point
by part (ii) of Proposition 4.
Now assume that there is another near fixed point
of
with
, i.e.,
. Then
for some
,
. Since
is a norm contraction on
and
satisfies the null equality, we obtain
Since , we conclude that , i.e., , which contradicts . Therefore, any cannot be the near fixed point. Equivalently, if is a near fixed point of , then . This completes the proof. ☐
Definition 16. Let be a near pseudo-normed space of fuzzy numbers. A fuzzy-number-valued function is called a weakly strict norm contraction on if and only if the following conditions are satisfied:
, i.e., implies .
, i.e., implies .
By part (ii) of Proposition 4, we see that if , then , which says that the weakly strict norm contraction is well-defined. In other words, should be assumed to be a near pseudo-normed space of fuzzy numbers rather than pseudo-seminormed space of fuzzy numbers. We further assume that satisfies the null super-inequality and null condition. Part (iii) of Proposition 4 says that if is a norm contraction on , then it is also a weakly strict norm contraction on .
Theorem 5. Let be a near Banach space of fuzzy numbers with the null set Ω. Suppose that satisfies the null super-inequality and null condition, and that the fuzzy-number-valued function is a weakly strict norm contraction on . If forms a Cauchy sequence for some , then has a near fixed point satisfying . Moreover, the near fixed point is obtained by the limit Assume further that satisfies the null equality. Then we also have the following properties.
The uniqueness is in the sense that there is a unique equivalence class such that any cannot be a near fixed point.
Each point is also a near fixed point of satisfying and .
If is a near fixed point of , then , i.e., . Equivalently, if and are the near fixed points of , then .
Proof. Since
is a Cauchy sequence, the completeness says that there exists
such that
Therefore, given any , there exists an integer N such that for . We consider the following two cases.
Suppose that
. Since
is a weakly strict norm contraction on
, it follows that
by part (iii) of Proposition 4.
Suppose that
. Since
is a weakly strict norm contraction on
, we have
The above two cases say that
. Using Proposition 3, we obtain
which says that
, i.e.,
by part (ii) of Proposition 4. This shows that
is a near fixed point.
Assume that
satisfies the null equality. We are going to claim that each point
is also a near fixed point of
. Since
, we have
for some
. Then, using the null equality for
, we obtain
Using the above argument, we can also obtain
as
. Using Proposition 3, we have
which says that
. Therefore we conclude that
for any point
by part (ii) of Proposition 4.
Suppose that
is another near fixed point of
. Then
and
, i.e.,
. Then
and
, where
for
. Therefore we obtain
This contradiction says that cannot be a near fixed point of . Equivalently, if is a near fixed point of , then . This completes the proof. ☐
Now we consider another fixed point theorem based on the concept of weakly uniformly strict norm contraction which was proposed by Meir and Keeler [
21].
Definition 17. Let be a near pseudo-normed space of fuzzy numbers with the null set Ω. A fuzzy-number-valued function is called a weakly uniformly strict norm contraction on if and only if the following conditions are satisfied:
for , i.e., , ;
for , i.e., , given any , there exists such that implies .
By part (ii) of Proposition 4, we see that if , then , which says that the weakly uniformly strict norm contraction is well-defined. In other words, should be assumed to be a near pseudo-normed space of fuzzy numbers rather than pseudo-seminormed space of fuzzy numbers.
Remark 2. We observe that if is a weakly uniformly strict norm contraction on , then is also a weakly strict norm contraction on .
Lemma 2. Let be a near pseudo-normed space of fuzzy numbers with the null set Ω, and let be a weakly uniformly strict norm contraction on . Then the sequence is decreasing to zero for any .
Proof. For convenience, we write for all n. Let .
Suppose that
. By Remark 2, we have
Suppose that
. Then, by the first condition of Definition 17,
The above two cases say that the sequence is decreasing. We consider the following cases.
Let
m be the first index in the sequence
such that
. Then we want to claim
. Since
, we have
Using the first condition of Definition 17, we also have
which says that
, i.e.,
. Using the similar arguments, we can obtain
and
. Therefore the sequence
is decreasing to zero.
Suppose that
for all
. Since the sequence
is decreasing, we assume that
, i.e.,
for all
n. There exists
such that
for some
m, i.e.,
By the second condition of Definition 17, we have
which contradicts
. Therefore we must have
.
This completes the proof. ☐
Theorem 6. Let be a near Banach space of fuzzy numbers with the null set Ω. Suppose that satisfies the null super-inequality, and that the fuzzy-number-valued function is a weakly uniformly strict norm contraction on . Then has a near fixed point satisfying . Moreover, the near fixed point is obtained by the limit Assume further that satisfies the null equality. Then we also have the following properties.
The uniqueness is in the sense that there is a unique equivalence class such that any cannot be a near fixed point.
Each point is also a near fixed point of satisfying and .
If is a near fixed point of , then , i.e., . Equivalently, if and are the near fixed points of , then .
Proof. According to Theorem 5 and Remark 2, we just need to claim that if
is a weakly uniformly strict norm contraction, then
forms a Cauchy sequence. Suppose that
is not a Cauchy sequence. Then there exists
such that, given any
N, there exist
satisfying
. Since
is a weakly uniformly strict norm contraction on
, for
, there exists
such that
Let
. For
, we are going to claim
Indeed, if then it is done, and if , i.e., , then .
Let
. Since the sequence
is decreasing to zero by Lemma 2, we can find
N such that
. For
, we have
which implicitly says that
. Since the sequence
is decreasing by Lemma 2 again, we obtain
For
j with
, using Proposition 3, we have
We want to show that there exists
j with
such that
and
Let
for
. Then (
25) and (
26) says that
and
. Let
be an index such that
Then we see that
, since
. By the definition of
, we also see that
and
, which also says that
. Therefore expression (
28) will be sound if we can show that
Suppose that this is not true, i.e.,
. From (
27), we have
This contradiction says that (
28) is sound. Since
, using (
24), we see that (
28) implies
Therefore we obtain
which contradicts (
28). This contradiction says that the sequence
is a Cauchy sequence, and the proof is complete. ☐