Abstract
The symmetry of fuzzy metric spaces has benefits for flexibility, ambiguity tolerance, resilience, compatibility, and applicability. They provide a more comprehensive description of similarity and offer a solid framework for working with ambiguous and imprecise data. We give fuzzy versions of some celebrated iterative mappings. Further, we provide different concrete conditions on the real valued functions for the existence of the best proximity point of generalized fuzzy -iterative mappings in the setting of fuzzy metric space. Furthermore, we utilize fuzzy versions of -proximal contraction, -interpolative Reich–Rus–Ciric-type proximal contractions, -Kannan type proximal contraction and -interpolative Hardy Roger’s type proximal contraction to examine the common best proximity points in fuzzy metric space. Also, we establish several non-trivial examples and an application to support our results.
1. Introduction
Fixed point theory is one of the most appealing areas of study. The techniques for determining a solution to a nonlinear equation of the pattern , where is self mapping, are discussed in fixed point theory. However, in various cases, the singular solution does not exist. Best approximation theorems and best proximity point theorems are helpful in solving the aforementioned problem. The best proximity point theorems have been generalized in a number of ways by numerous authors, and they provide an approximate optimal solution. If the mapping is self-mapping, then the best proximity point theorems become a fixed point.
In 1968, Kannan [1], introduced a new kind of contraction for discontinuous mappings and proved several fixed point results. He provided a new way for researchers to solve fixed point problems. Karapinar [2] introduced iterative Kannan–Mier-type contractions. Karapinar et al. [3] provided new results on Perov interpolative contractions of Suzuki type mappings. Karapinar and Agarwal [4] established interpolative Rus–Reich–Ciric-type contractions via simulation functions. Karapinar et al. [5] offered a new result for Hardy–Rogers-type interpolative contractions.
Altun et al. [6] gave some best proximity point results for p-proximal contractions. Further, Altun and Aysenur [7] proved some best proximity point results for interpolative proximal contractions. Shazad et al. [8] provided some common best proximity point results. Basha [9] developed common best proximity point results for global minimal solutions. Moreover, Basha [10] examined common best proximity point for multi-objective functions. Deep and Betra [11] introduced some common best proximity point results under proximal F-contraction. Mondal and Dey [12] proved some common best proximity point results in complete metric spaces. Shayanpour and Nematizadeh [13] presented some common best proximity point results in the setting of complete fuzzy metric space (in short, CFMS). Hierro [14] presented Proinov-type fixed point results in fuzzy metric spaces (FMS). Then, Zhou et al. [15] modified the results of [14] and introduced new Proinov-type fixed point results in FMS. Uddin et al. [16] proved several new results for a new extension to the intuitionistic FM-like spaces. Saleem et al. [17] provided a unique soltion for integral equations via intuitionistic extended fuzzy b-metric-like spaces. Saleem et al. [18] presented a result for graphical FMS applied to fractional differential equations. Hussain et al. [19] proved a result for fixed point in FMS. Nazam et al. [20] established several results for generalized interpolative contractions. Naseem et al. [21] worked on the analytical approximation of fractional delay differential equations.
In this paper, we introduce fuzzy versions of -proximal contractions, -interpolative Reich–Rus–Ciric-type proximal contractions, -interpolative Kannan-type proximal contractions, and -interpolative Hardy Roger’s type proximal contractions to examine the common best proximity point in the setting of FMS. We provide several non-trivial examples and an application to integral equations to support our results.
2. Preliminaries
In this section, we provide definitions from the existing literature that will help readers to understand the main section.
Definition 1
([9]). Let be a metric space. The mappings and are said to commute proximally if they satisfy the below condition
for all in .
Definition 2
([9]). Let be a metric space. A mapping dominates proximally to a mapping if there exists a non-negative number such that
for all
Definition 3
([15]). A binary operation (where ) is said to be a continuous t-norm (ctn) if it satisfies the below axioms:
- (1)
- andfor all
- (2)
- * is continuous;
- (3)
- σ for all
- (4)
- when and with
Definition 4
([15]). A triplet is termed as FMS if * is a ctn, is arbitrary set, and ϑ is a fuzzy set on fulfilling the below conditions for all and
- (i)
- (ii)
- if and only if
- (iii)
- (iv)
- (v)
Example 1.
Suppose and , consider a ctn as . Then, is a FMS.
Definition 5
([13]). A sequence in a FMS is said to be convergent to a point if for each and , there exists such that for all or , for all ; in this case, we say that limit of sequence exists.
Definition 6
([13]). A sequence in a FMS is said to be convergent to a point if for each and , there exists such that for all and every or , for all and .
Also, an FMS is said to be complete if and only if every Cauchy sequence in is convergent.
Definition 7
([13]). Let be a FMS and , Then
which is said to be a fuzzy distance between .
Definition 8
([13]). Let be a FMS and , We define the following sets.
Definition 9
([13]). Let be an FMS, , and be two mappings. We say that an element is a common best proximity point of the mappings Υ and Γ, if
Definition 10
([13]). Let be a FMS, , and be two mappings. We say that are commute proximally if
then , where .
Definition 11
([13]). Let be a FMS, , and be two mappings. We say that the mapping Υ is to dominate Γ proximally if
for all then there exists such that for all ,
where and .
Definition 12
([15]). We denote by the the family of the pairs of a functions : satisfying the given properties below:
- (s1)
- is nondecreasing,
- (s2)
- for any
- (s3)
- for any
- (s4)
- if is such that then
3. Main Results
In this section, we provide several common best proximity point results by utilizing generalized fuzzy interpolative contractions, and we prove non-trivial examples.
3.1. Fuzzy -Proximal Contraction
Let and . The mappings and are called fuzzy -proximal if
for all and
Example 2.
Let be a FMS with ϑ. Let and . Define mappings and as
and
Then, , and . Then clearly and . Define the functions by
We show that Γ and Υ are fuzzy -proximal in FMS. Consider , and
then
This implies that
and similar in other cases. This shows that mappings Γ and Υ are fuzzy -proximal. However, the following shows that Γ and Υ are not proximal in FMS. We know that
If there exists a non-negative number then
This is a contradiction. Hence, mappings Γ and Υ are not fuzzy proximal.
Example 3.
Let be a FMS define by ϑ with ctn as . Let and . Define mappings and as
and,
Then, , and . Then, clearly and . Define the functions by
The mappings Γ and Υ are fuzzy -proximal. Here, we show that Γ and Υ are not fuzzy proximal. We have
Then, there exists a non-negative number such that
which is a contradiction. Hence, Γ and Υ are not fuzzy proximal.
To obtain the proofs of the key results, the following lemmas will be used.
Lemma 1
([14]). Let be a FMS and be a sequence verifying . If the sequence is not a Cauchy sequence, then there are subsequences , and such that
Lemma 2
([14]). Let . Then the following conditions are equivalent:
- (i)
- for every
- (ii)
- for any
- (iii)
- implies that
Lemma 3.
Assume is a sequence such that and the mappings and satisfying (1). If the functions with
- (1)
- for any
Then is a Cauchy sequence.
Proof.
Let us suppose that the sequence is not a Cauchy sequence; then, by Lemma 1, there exist two subsequences , of and such that the Equations (2) and (3) hold. From Equation (2), we get that . Since, for , we have
Thus, from Equation (1), we have
for all Let and , we have
From Equations (2) and (3), we have and . From Equation (4), we get that
This is a contradiction to condition (i). That is, is a Cauchy sequence in . □
Theorem 1.
Let in CFMS such that is AC with respect to . Also, assume that and and . Let and satisfying the following conditions
- (i)
- Υ dominates Γ and are fuzzy -proximal,
- (ii)
- Γ and Υ are compact proximal,
- (iii)
- is non-decreasing function and for any ,
- (iv)
- Γ and Υ are continuous,
- (v)
- and
Then, Υ and Γ have a unique element such that
Proof.
Let . Since guarantees the existence of an element such that . Also, we have , ∃ an element such that This process of existence of points in is implied to have a sequence such that
for all positive integral values of since
Since ∃ an element in such that
Further, it follows from the choice of and that
If,
See that, if ∃ some such that , then from Equation (6), the point is a common best proximity point of the mappings and . On the other hand, if for all , then from Equation (6), we have
Thus, from Equation (1), we have
for all Let , we have
Since is non-decreasing, from Equation (7), we get for all . This shows that the sequence is positive and strictly non-decreasing. Hence, it converges to some element . We show that . Suppose on the contrary that and from Equation (7), we get the equation below:
This contradicts to assumption (iii), hence, and . By assumption (iii) and Lemma 3, we deduce that is a Cauchy sequence. Since is a CFMS, . Since , there exists an element in such that . Moreover,
Also,
Therefore, and also as . As and commute proximally, and are identical. Since is AC with respect to , ∃ a subsequence of and of such that and as . Moreover, by letting in the below equation,
we have
Since, , so and ∃. Similarly , so and ∃ such that
Now, by Equations (8), (9) and (1), we have
Since is non-decreasing function, we have
This implies and are identical. Finally, by Equation (6), we have
This shows that the point is a common best proximity point of the pair of mappings and □
Theorem 2.
Let in a CFMS such that is AC with respect to . Also, assume that and , Let and satisfying the following conditions:
- (i)
- Υ dominates Γ and are fuzzy -proximal.
- (ii)
- Γ and Υ are compact proximal.
- (iii)
- is non-decreasing and and are convergent sequences such that , then .
- (iv)
- Γ and Υ are continuous.
- (v)
- and
Then Υ and Γ have a unique element such that
Proof.
Proceeding as in the proof of Theorem 1, we get
By Equation (10), we infer that is a strictly nondecreasing sequence (in short, sds). We have two cases here; either the sequence is bounded above, or not. If is not bounded above, then
It follows from Lemma 1 that as . Secondly, if the sequence is bounded above, then it is a convergent sequence. By Equation (10), the sequence also converges. Furthermore, both have the same limit. By condition (iii), we get , or for any sequence in . Now, following the proof of Theorem 1, we have
This shows that the point is a common best proximity point of the pair of the mapping and □
3.2. Fuzzy -Interpolative Reich–Rus–Ciric-Type Proximal Contractions
Let and . The mappings and are called fuzzy -interpolative Reich–Rus–Ciric-type proximally contractiona if
for all
Example 4.
Let be a CFMS defined as ϑ. Let and . Define mappings and as
and
Then, , and . Then clearly and Define the functions by
Under the conditions of Example 2, Γ and Υ are fuzzy -interpolative Reich–Rus–Ciric-type proximal in FMS. However, the following shows that Γ and Υ are not fuzzy interpolative Reich–Rus–Ciric type proximal. We know that
Then there exists a non negative number such that
which is a contradiction. Hence, Γ and Υ are not fuzzy interpolative Reich–Rus–Ciric-type proximal.
Theorem 3.
Let in a CFMS such that is AC with respect to . Also, assume that and ,. Let and , satisfying the following conditions
- (i)
- Υ dominates Γ and are fuzzy -interpolative Riech–Rus–Ciric-type proximal;
- (ii)
- Γ and Υ are compact proximal;
- (iii)
- is a nondecreasing function, and for any ;
- (iv)
- Γ and Υ are continuous;
- (v)
- and
Then, Υ and Γ have a unique element such that
Proof.
Let . Since guarantees the existence of an element such that, . Also, we have , ∃ an element such that This process of existence of points in is implied to have a sequence such that
for all positive intergral values of because
Since ∃ an element in such that
Further, it follows from the choice of and that
if
See that if ∃ some such that , then by Equation (12), the point is a common best proximity point of the mappings and . On the other hand, if for all , then by Equation (12), we get
Thus, by Equation (11), we have
for all Since, for all by Equation (13), we have
Thus, is non-decreasing function, and we get
This implies that
Let , we have
This implies for all . This shows that the sequence is PSD. Thus, it converges to some element . We show that . On the contrary, let so that by Equation (13), we get the following:
This contradicts condition (iii); hence, and . By the condition (iii) and Lemma 3, we deduce that is a Cauchy sequence. Since is a CFMS and . Since, , there exists an element in such that . Moreover,
Also,
Furthermore, , and also , as . As and CP, and are identical. Since is AC with respect to , there exists a subsequence of and of Such that and as . Moreover, by letting in the below equation,
We have,
Since, , so and ∃. Similarly , so and there exists such that
Now, bearing in mind Equations (14) and (15), from (11), we have
Since is non-decreasing function, we have
This implies and are identical. Finally, by Equation (12), we have
This shows that the point is a common best proximity point of the pair of mappings and □
Theorem 4.
Let in a CFMS such that is AC with respect to . Also, assume that and , . Let and , satisfying the following conditions
- (i)
- Υ dominates Γ and are fuzzy -interpolative Riech–Rus–Ciric-type proximal;
- (ii)
- Γ and Υ are compact proximal;
- (iii)
- is non-decreasing and and are convergent sequences such that , then ;
- (iv)
- Γ and Υ are continuous;
- (v)
- and
Then, Υ and Γ have a unique element such that
Proof.
Proceeding from the proof of Theorem 3, we have
By Equation (16), we infer that is sds. We have two cases here; either the sequence is bounded above, or it is not. If is not bounded below, then
It follows from Lemma 1 that as . Secondly, if the sequence is bounded above, then it is a convergent sequence. By Equation (16), the sequence also converges. Furthermore, both have the same limit. By condition (iii), we get or for any sequence in . Now, following the proof of Theorem 3, we obtain
This shows that the point is a common best proximity point of the pair of the mapping and □
3.3. Fuzzy -Kannan Type Proximal Contraction
Let . The mappings and are called fuzzy -Kannan-type proximal contractions if
for all
Example 5.
Let be a CFMS with ϑ. Let and . Define mappings and as
and
Then, , and . Then clearly and Define the functions by
Under the conditions of Example 2, Γ and Υ are fuzzy -interpolative Kannan-type proximal in FMS. However, the following shows that Γ and Υ are not fuzzy interpolative Kannan-type proximal. We know that
Then there exists a non negative number such that
which is a contradiction. Hence, Γ and Υ are not fuzzy interpolative Kannan-type proximal.
Theorem 5.
Let in a CFMS such that is AC with respect to . Also, assume that and , . Let and satisfying the following conditions:
- (i)
- Υ dominates Γ and are fuzzy -interpolative Kannan type proximal;
- (ii)
- Γ and Υ are compact proximal;
- (iii)
- is non-decreasing function and for any ;
- (iv)
- Γ and Υ are continuous;
- (v)
- and
Then, Υ and Γ have a unique element such that
Proof.
Let . Since guarantees the existence of an element s.t. . Also, we have , ∃ an element such that This process of existence of points in implies to have a sequence such that
for all positive intergral values of because
Since ∃ an element in such that
Further, it follows from the choice of and that
if
Notice that, if there exists some such that , then from Equation (18), the point is a common best proximity point of the mappings and . On the other hand, if for all , then from Equation (18), we get
Thus, from Equation (17), we have
for all Since for all from Equation (19), we have
Thus, is non-decreasing function, and we get
This implies that
Let , we have
This implies for all . This shows that the sequence is positive and strictly non-decreasing. Hence, it converges to some element . We show that . On the contrary, let ; from Equation (19), we get the following:
This contradicts assumption (iii). Hence, and . By condition (iii) and Lemma 3, we deduce that is a Cauchy sequence. Since is a CFMS and . Since, , there exists an element in such that . Moreover,
Also,
Therefore, , and , as . As and are compact proximal, and are identical. Since is AC with respect to , there exists a subsequence of and of such that and as . Moreover, by letting in the below equation,
we have
Since, , so and there exists . Similarly , so and there exists such that
Now, bearing in mind Equations (20) and (21), from (17)), we have
Since is non-decreasing function, we have
This implies and are identical. Finally, from Equation (18), we have
This shows that the point is a common best proximity point of the pair of mappings and □
Theorem 6.
Let in a CFMS such that is AC with respect to . Suppose that and , . Let and , satisfying the following conditions:
- (i)
- Υ dominates Γ and are fuzzy -interpolative Kannan-type proximal;
- (ii)
- Γ and Υ are compact proximal;
- (iii)
- is non-decreasing and and are convergent sequences such that , then ;
- (iv)
- Γ and Υ are continuous;
- (v)
- and
Then, Υ and Γ have a unique element such that
Proof.
Proceeding as in the proof of Theorem 5, we get
From Equation (16), we infer that is sds. We have two cases here; either the sequence is bounded above, or it is not. If is not bounded above, then
It follows from Lemma 1 that as . Secondly, if the sequence is bounded above, then it is a convergent sequence. From Equation (16), the sequence also converges. Furthermore, both have the same limit. From condition (iii), we get , or for any sequence in . Now, following the proof of Theorem 5, we have
This shows that the point is a common best proximity point of the pair of the mapping and □
3.4. Fuzzy -Interpolative Hardy–Rogers-Type Proximal Contraction
Let , . The mappings and are called fuzzy -interpolative Hardy Roger’s type proximal contraction if
for all
Example 6.
Let be a CFMS with ϑ. Let and . Define mappings and as
and
Then, , and . Then clearly, and Define the functions by
Under the conditions of Example 2, the mappings Γ and Υ are fuzzy -interpolative Hardy–Rogers-type proximal in FMS. However, the following shows that Γ and Υ are not fuzzy interpolative Hardy–Rogers-type proximal. We know that
If there exists a non-negative number Then,
which is a contradiction. Hence, mappings Γ and Υ are not fuzzy interpolative Hardy–Rogers-type proximal.
Theorem 7.
Let in a CFMS such that is AC with respect to . Also, assume that and , . Let and , satisfying the following conditions
- (i)
- Υ dominates Γ and are fuzzy -interpolative Hardy–Rogers-type proximal;
- (ii)
- Γ and Υ are compact proximal;
- (iii)
- is nondecreasing function and for any ;
- (iv)
- Γ and Υ are continuous;
- (v)
- and
Then, Υ and Γ have a unique element such that
Proof.
Let . Since guarantees the existence of an element such that, . Also, we have , ∃ an element such that This process of existence of points in is implied to have a sequence such that
for all positive integral values of because
Since , there exists an element in such that
Further, it follows from the choice of and that
if
Notice that, if there exists some such that , then by Equation (24), the point is a common best proximity point of the mappings and . On the other hand, if for all , then from Equation (24), we obtain
Thus, from Equation (23), we have
for all Since for all from Equation (25), we have
Thus, is a non-decreasing function, and we get
This implies that
Let , we have
Assume that for some . Since is non-decreasing, then by (25), we get . This is not possible. Hence, we obtain for all Thus, it converges to some element . We show that . On the contrary, let ; from Equation (25), we get the equation below:
This contradicts condition (iii), hence and . By condition (iii) and Lemma 3, we deduce that is a Cauchy sequence. Since is a CFMS and . Since , ∃ an element in such that . Moreover,
Also,
Therefore, and also as . As and are compact proximal, and are identical. Since is AC with respect to , ∃ a subsequence of and of such that and as . Moreover, by letting in the below equation,
we have
Since, , so and ∃. Similarly, , so and ∃ such that
Now, bearing in mind Equations (26) and (27), from (23), we have
Since is a non-decreasing function, we have
This implies and are identical. Finally, from Equation (24), we have
This shows that the point is a common best proximity point of the pair of mappings and □
Theorem 8.
Let such that is AC with respect to . Also, assume that and , . Let and satisfy the following conditions:
- (i)
- Υ dominates Γ and are fuzzy -interpolative Hardy–Rogers-type proximal;
- (ii)
- Γ and Υ are compact proximal;
- (iii)
- is non-decreasing and and are convergent sequences such that , then ;
- (iv)
- Γ and Υ are continuous;
- (v)
- and
Then, Υ and Γ have a unique element such that
Proof.
Proceeding as in the proof of Theorem 7, we have
By Equation (28), we infer that is sds. We have two cases here; either the sequence is bounded above, or it is not. If is not bounded above, then
It follows from Lemma 1 that as . Secondly, if the sequence is bounded above, then it is a convergent sequence. By Equation (28), the sequence also converges. Furthermore, both have the same limit. By condition (iii), we get , or for any sequence in . Now, following the proof of Theorem 7, we obtain
This shows that the point is a common best proximity point of the pair of the mapping and □
4. Application
In this part, we utilize Theorem 1 to find the existence and uniqueness of a solution to UIE:
Depending on the integration region (IR), this integral equation involves both the Volterra integral equation (VIE) and the Fredholm integral equation (FIE). If , where a is fixed, then UIE is VIE. For this, we consider a common best proximity point approach. The common best proximity point technique is a straightforward and attractive way to demonstrate that each additional mathematical model has a singular solution.
Suppose IR is a set of finite measures, and
Define the norm by
The following formula of an equivalent norm is given:
Then, is a Banach space. Let . The FM associated with the norm is given by for all . Then is an CFMS. Let
- (A1)
- The Kernal satisfies Carthodory conditions, and
- (A2)
- The function is continuous and bounded on IR.
- (A3)
- There exists a positive constant C such that
- (A4)
- Let . Since guarantees the existence of an element such that, . Also, we have
- (A5)
- There exists a nonnegative and measurable function such thatand integrable over withfor all and .
Theorem 9.
Suppose the mapping f and mentioned above verify the conditions (A)–(A), then, the UIE Equation (29) has a unique solution.
Proof.
Define the pair of mappings , in accordance with the abovementioned notations, by
Let , since, for almost every
Conditions (A)–(A) imply that is continuous and compact mapping from to . By (A) we will check the contractive condition of Equation (7) of Theorem 1 in the next lines. By (A) and the Holder inequality, we have
This implies, by integrating with respect to ℏ,
Thus, we have
This implies that
That is
Define and ; then, we have
The defined and satisfy the remaining conditions of the Theorem 1. Hence, from Theorem 1, the operator has a unique point. This means that the UIE Equation (29) has a unique solution. □
5. Conclusions
In this manuscript, we have introduced several new types of contractive conditions that ensure the existence of common best proximity points in the framework of FMS. Our examples show that the new contractive conditions generalize the corresponding contractions from the existing literature. The contraction conditions (1), (11), (17) and (23) can be used to demonstrate the presence of solutions to the models of linear and nonlinear dynamic systems, depending on their nature (linear or nonlinear). This paper’s study expands on the worthwhile research that was previously published in [7,8,11,12,13].
Author Contributions
Conceptualization, U.I., I.K.A. and F.J.; methodology, D.A.K.; software, U.I.; validation, I.K.A., F.J. and D.A.K.; formal analysis, U.I.; investigation, U.I. and I.K.A.; resources, U.I.; data curation, F.J.; writing—original draft preparation, U.I.; writing—review and editing, I.K.A. and U.I.; visualization, D.A.K.; supervision, I.K.A.; project administration, U.I.; funding acquisition, D.A.K. and I.K.A. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Data Availability Statement
Data will be available on demand from the corresponding author.
Conflicts of Interest
The authors declare no conflict of interest.
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