1. Introduction
In 1922, Banach [
1] gave an important result named the Banach contraction principle in fixed point theory (in short, FPT). Applications of FPT are found in many other fields of mathematics, including nonlinear analysis. It is an attractive and quickly expanding subject of study. Given that a map that adheres to the Banach contraction principle is continuous, it makes sense to inquire as to whether or not a discontinuous map fulfilling comparable contractive requirements has a fixed point. For this question Kannan [
2] defined a contractive condition for discontinuous map
R, as follows:
for all
and
. Moreover, he demonstrated the existence and uniqueness of FP in the setting of complete metric spaces.
The fuzzy set has gained popularity since Zadeh [
3] introduced the fuzzy set theory in 1965 as a logical development of the idea of a set and laid the foundation for fuzzy mathematics. Schweizer and Sklar [
4] presented the concept of continuous t-norm (CTN). In [
5], a new concept of fuzzy space was introduced by combining the probabilistic metric spaces with the fuzzy set. This concept has applications in various mathematical disciplines, including logic, analysis and algebra, artificial intelligence, fixed point theory, and applied science fields like signal processing and medical imaging. Fuzzy sets have been widely used by numerous writers in a variety of mathematical fields. One of the most researched areas in fuzzy set theory is fuzzy metric spaces, which were first presented by Karamosil and Michalek [
6]. Following that, a number of writers expanded and developed the idea of fuzzy metric space in different ways. By modifying the concept of fuzzy metric space, George and Veeramani [
7], for instance, demonstrated that each fuzzy metric generates a Hausdorff topology.
First of all, Proinov [
8] defined auxiliary function
such that
- (i)
for any
- (ii)
for any
- (iii)
is non-decreasing and for any
- (iv)
If and are convergent sequences with the same limit, is strictly decreasing.
Moreover, he proved FPT and showed the existence of uniqueness of a fixed point for complete metric spaces. Hierro et al. [
9] proved some auxiliary function in fuzzy metric space (in short, FMS) and showed FPT. Then, Zhou et al. [
10] also improved the results of Hierro et al. [
9]. Ishtiaq et al. [
11] used auxiliary function and iterative mappings to find out FPT.
For non-self mapping, Basha [
12] gave a new way to attain an optimal solution, which is the best proximity point (in short, BPP). Then, Jleli and Samet [
13] found some BPP for
proximal contractive mappings. Vetro and Salimi [
14] showed BPP results in non-Archimedean FMS. Furthermore, Paknazar [
15] found BPP results in non-Archimedean FMS. First of all, Farheen et al. [
16] defined fuzzy multiplicative metric spaces and proved BPP for fuzzy multiplicative metric spaces. Some common BPP theorems were discussed in [
17,
18] by Ishtiaq et al. in FMS. Jahangeer et al. [
19] found some BPP theorems by using iterative mappings in bipolar metric spaces. Alamri [
20] developed fixed point theorems for F-bipolar metric spaces, expanding the concept of rational
-contractions. These new contractions make it easier to derive fixed-point theorems for contravariant mappings. Maheswari et al. [
21] extended fixed point theory by providing new theorems for bipolar fuzzy b-metric spaces. Their research gave a better understanding of fixed point existence and uniqueness in these generalized metric spaces. These new contractions not only increase the scope of fixed point theorems but they also generalize some well-known existence proofs from the literature.
The symmetric property plays a crucial role in establishing fixed points for contraction mappings by ensuring that the distance between any two elements remains invariant under permutation, which facilitates the analysis of convergence behavior. In the context of contraction mappings, symmetry ensures that the iterative application of the mapping yields consistent distances, preventing directional bias and enabling balanced error estimates. This property helps in proving the uniqueness of fixed points by allowing contraction conditions to hold uniformly in both forward and reverse directions, thus strengthening the validity of the Banach contraction principle and its extensions in fuzzy and bipolar metric spaces. Alnabulsi et al. [
22] introduced several novel concepts within the framework of fuzzy bipolar b-metric spaces. They focused on various mappings, such as
-contractive and
-contractive mappings, which are essential to quantify distances between dissimilar elements. They developed fixed-point theorems for these mappings, establishing the existence of invariant points under specific conditions. Kumar et al. [
23] proposed a generalized parametric bipolar metric space, which combines and expands the concepts of generalized parametric and bipolar metric spaces. They also presented Boyd–Wong type contractions for both covariant and contravariant mappings, which provided a framework for determining fixed point results in this newly defined space. Mani et al. [
24] introduced Menger probabilistic bipolar metric spaces, along with related notions and definitions. They developed various novel fixed point theorems that handled both covariant and contravariant mappings. These theorems are novel generalizations of standard results such as the Banach contraction principle, Kannan theorem, and Reich-type theorem, tailored to the framework of Menger probabilistic bipolar metric spaces. Zararsiz and Riaz [
25] defined fuzzy bipolar metric spaces (in short, FBMS) and their topological properties. In addition, Bartwal et al. [
26] showed FPT in FBMS.
Routaray et al. [
27] introduced the fuzzy differential transform method to solve a set of nonlinear fuzzy integro-differential equations. These equations are part of a mathematical model that depicts the coexistence of biological organisms. Acharya et al. [
28] investigated the controllability of fuzzy solutions for second-order nonlocal impulsive neutral functional differential equations. Their study addresses both nonlocal and impulsive conditions in the fuzzy framework. Using the Banach fixed point theorem, they established a sufficient condition for controllability. Chalishajar and Ramesh [
29] investigated the existence and uniqueness of fuzzy solutions to abstract second-order differential systems. Their work emphasizes the benefits of nonlocal conditions above local ones. Zhang et al. [
30] analyzed singular fractional-order systems with
. Their research focused on key characteristics of these systems, such as regularity, non-impulsiveness, stability, and admissibility. Zhang et al. [
31] studied the properties of singular fractional-order systems with fractional orders, including their regularity, non-impulsiveness, stability, and admissibility. Their research provides insights into the fundamental characteristics of complex systems, including both theoretical and practical aspects.
Motivated by the aforementioned studies, we delve into the investigation of several BPP results within the framework of a complete fuzzy bipolar metric space (CFBMS). The paper is structured into four comprehensive sections, each contributing to a deeper understanding of the topic.
In the second section, we revisit and refine the essential concepts and definitions of the existing literature to establish a solid foundation for our work. This includes a review of the fundamental principles of bipolar metric spaces, proximal contractions, and relevant fixed-point theorems. By consolidating these core ideas, we aim to provide a seamless transition to the novel contributions of this study.
The third section introduces our primary findings, including several innovative contraction mappings. Specifically, we define the -proximal contraction (abbreviated as PC), -Reich–Rus–Ceric type interpolative proximal contraction (IPC), -Kannan type IPC, and -Hardy–Rogers type IPC. For each of these contractions, we establish the corresponding BPP results, which extend and generalize existing fixed-point theorems to this new context. To enhance comprehension and illustrate the applicability of these results, we provide carefully constructed examples that validate the theoretical findings.
In the fourth section, we turn our attention to practical applications, showcasing the relevance and utility of our theoretical results. Specifically, we apply the best proximity point theorems developed to prove the existence and uniqueness of a solution to an integral equation. This application highlights the versatility of the contractions in addressing real-world mathematical problems and underscores their potential for broader applicability in related fields.
Finally, in the fifth section, we summarize the findings of the study and offer concluding remarks. This section not only synthesizes the key contributions but also outlines potential directions for future research. We emphasize how the introduced notions and results can pave the way for further exploration in fixed point theory, metric spaces, and their applications in diverse mathematical and scientific domains.
3. Main Results
In this part, we present some BPP results by utilizing generalized interpolative contractions including -proximal contraction, Reich–Rus–Ciric type IPC, Kannan type IPC, Hardy–Rogers type IPC. Moreover, we provide some examples that verify our results.
Definition 11. Suppose is an FBMS, and V and are non-empty closed subsets of an FBMS. We consider the below subsets, respectively,Furthermore, Example 2. Let and be equipped with for all and . Then, is an FBMS with CTN . Let and define the mapping by for . Then, we have the above definition.
Definition 12. Suppose V and X are closed nonempty subsets of an FBMS . We say that is approximately compact (in short, AC) with respect to , if every BS in satisfies the following:for some , which has a BC sub-sequence. Definition 13. Suppose V and X are closed nonempty subsets of an FBMS . An element is called a BPP of the mapping , if it holds the equation Example 3. From above Example 2, we have to find BPPHence, 0 is the BPP. Definition 14. Suppose V and X are non-empty, closed subsets of an FBMS . A mapping is said to be proximal contraction (in short, PC) on BMS if there exists a real number such thatfor all , , , Example 4. Let and be equipped with for all and . Then, is an FBMS with CTN . Let and define the mapping by for . Thus, , and . Consider, , and , and Hence, R is a PC. Definition 15. Suppose V and X are closed nonempty subsets of an FBMS . A mapping is said to be Reich–Rus–Ciric type IPC, if there exists a real number and such thatfor all , , , . Example 5. Let and be equipped with for all and . Then, is an FBMS with CTN . Let and define the mapping by for . Thus, , and . Consider, , and , and Similarly, this holds for all other cases, as shown in Figure 1. Hence, R is a Reich–Rus–Ciric type IPC. Definition 16. Suppose V and X are non-empty, closed subsets of an FBMS . A mapping is said to be Kannan type IPC, if there exists a real number and such thatfor all , , , . Example 6. Let , and be equipped with for all and . Then, is an FBMS with CTN . Let and define the mapping by for . Thus, , and . Consider, , and , and Hence, R is a Kannan type IPC. 3.1. -Proximal Contraction
This section applies the prior findings of [
12,
13,
19] to the framework of the
-proximal contractions for non-self mappings. This approach is especially useful for dealing with problems involving coupled spaces or interactions between different structures. We use
-proximal contractions to provide novel convergence and stability criteria for iterative algorithms in such situations, guaranteeing their robustness and efficiency.
Definition 17. Suppose V and X is a non-empty, closed subset of an FBMS . A mapping is said to be -proximal contraction ifwhich impliesfor all , , , with and where, are two function such that for The following example shows that is PC.
Example 7. Let and be equipped by for all and . Then, is an FBMS, with CTN . Let and define the mapping by for . Thus, , and . Then clearly, . The functions and are defined as follows: Hence, R is a -PC. Moreover, the other requirements of the definition (4) are satisfied. Then, 0 is a BPP of the mapping R. Consider, , and , , and ; then,which implies thatwhich is a contradiction. Hence, R is not a PC without . Lemma 1. Let be an FBMS and be a BS in that is not Cauchy BS and . Then, there exists and two bisubsequences and of such that Proof. Since
is not a Cauchy bi-sequence and
, there exists for
and
such that for each
there exists
such that
Thus, we can make two subsequences of
and
of
such that
From these inequalities and triangular inequality, we obtain
By the Sandwich theorem, we obtain (
5). Furthermore, we have
which implies the second limit (
6). From the following two inequalities,
we deduce the first and third limits in (
6). □
Lemma 2. Let . Then the following axioms are equivalent:
- (i)
for every
- (ii)
for every
- (iii)
implies that
Proof. (i) ⇒ (ii): Assume that condition (i) holds and that for some . This implies that for all . Since it follows that condition (ii) is satisfied.
(ii) ⇒ (iii): Let us assume that condition (ii) is valid and that for a sequence . Suppose does not tend to zero. There exists and a subsequence such that for all . Given that it follows that contradicting condition (ii). Consequently, we obtain proving that (iii) holds.
(iii) ⇒ (i): Suppose condition (iii) is true and assume for contradiction that for some . So there must exist a subsequence such that for all and . By condition (iii) that is this contradicts the assumption that . Therefore the condition (i) must be hold. □
Lemma 3. Let be a BS in such that and be a mapping satisfying (4). If the functions are such that - (1)
for any
Then is CBS.
Proof. Suppose that the BS
is not CBS, then by Lemma 1, there exist two bi subsequences
,
of
and
such that the Equations (
5) and (
6) hold. By (
5), we obtain that
. Since, for
, we have
thus, by (
4), we have
For if
and
, we have
By (
5) and (
6), we have
and
. By (
7), we obtain that
This is conflicted with the axioms (1). Consequently,
is a CBS in
. □
Now, we present the main results.
Theorem 1. Suppose V and X are nonempty closed subsets of a CFBMS such that is AC with respect to . A mapping is a -PC if
- (i)
is a nondecreasing function, and for any
- (ii)
is a nonempty subset of such that
Then, R has a BPP.
Proof. Suppose that
. Since
, then ∃
such that
Similarly, since
, ∃
such that
During this process, we establish a BS
such that
If
, then from (
9), obviously,
is a BPP of the mapping
R. Consider,
for all
, then
and
Then by using (
4), we have
Letting
, we have
is nondecreasing, so by (
10), we have
∀
. Hence, the BS
is positive and strictly decreasing (in short, PASD). Thus, it converges to some element
such that
. Now, from (
10) we obtain the following
Hence, from supposition (i), it is conflicted thus,
and
. Now, from supposition (i) and Lemma 3, we wind up with the BS
being a CBS in
.
Since
is a CFBMS, then BS
converges, thus BC to a point
such that
. From Equation (
9),
Therefore,
as
. Since
is AC with respect to
, there exists a subsequence
of
such that
as
. Therefore, by taking
in
we have
Since
. Furthermore, since
, there exists
such that
Suppose that
∀
. There exists subsequences
of
such that
. Now, from (
11), (
12), and the inequality (
4), we obtain that
Since
is a nondecreasing function (in short, ND), we have
for all
. Thus, letting
, we have
or
. Finally, by (
12), we have
Thus,
is a BPP of the mapping
R. □
Theorem 2. Suppose V and X are non-empty, closed subsets of a CFBMS such that is AC with respect to . A mapping is a -Pc if
- (i)
is a nondecreasing function, and are BC such that then the
- (ii)
is a nonempty subset of such that
Then, R has a BPP.
Proof. Starting with the proof of Theorem 1, we have
By (
13), we infer that
is strictly decreasing BS. There are two cases; either the BS
is bounded below or not. If
is not bounded below, then
From Lemma 2,
as
Secondly, if the BS
is bounded below, then it is BCS. By (
13), the BS
is also BC; moreover, both have the same limit. By supposition (i), we have
, or
for any BS
in
. The remaining proof of the Theorem is taken the same as the proof of Theorem 1; therefore, we have
Hence,
is a BPP of the mapping
R. □
3.2. -Interpolative Reich–Ciric–Rus
Type Proximal Contraction
In this part, we will develop conditions for determining the best proximity point for Reich–Rus–Ciric type contractions and generalize the findings of [
17,
18,
19] to the framework of FBMS. In order to overcome the difficulties caused by nonlinearity and imprecision, we use the dual metrics and fuzzy parameters to construct adequate requirements for the existence and uniqueness of BPP for such contractions. This generalization offers a throughout framework for resolving BPP problems in FBMS by introducing new iterative schemes and convergence studies to consolidate and expand on previous findings.
Definition 18. Suppose V and X are closed nonempty subsets of an FBMS . A mapping is said to be -Reich–Rus–Ciric type IPC if there exists , verifyingwhich impliesfor all , , , and with where, are two function such that for Example 8. Let and be equipped with for all and . Then, is an FBMS with CTN . Let and define the mapping by for all . Thus, , and . Then clearly, . Define the function byHence, R is a Reich–Rus–Ciric type IPC. Furthermore, the other requirements of the definition (14) are satisfied. Then, 0 is the BPP. Consider, , , , , , and This implies thatwhich is a contradiction. Hence, R is not a Reich–Rus–Ciric type IPC. Theorem 3. Suppose V and X are non-empty, closed subsets of a CFBMS such that is AC with respect to . Suppose a mapping is a Reich–Rus–Ciric type IPC if
(i) is nondecreasing, and for any
(ii) is a nonempty subset of such that
Then R has a BPP.
Proof. Taking the same step of Theorem 1, we establish a BS
in
such that
If
, then from (
15), obviously,
is a BPP of the mapping
R. Consider,
for all
, then
and
Then, by using (
14), we have
for all distinct
. Since
∀
, by (
16), we have
Since
is NDF, we have
This implies that
This implies that
for all
This shows that the BS
is PASD. Hence, it converges to some element
such that
. Now from (
16), we obtain the following
This conflicts with supposition (i), hence,
and
. From supposition (i) and Lemma 3, we wind up with the BS
being a CBS in
. The remaining proof of the Theorem is taken as the same as the proof of Theorem 1. Hence, we find that
is a BPP of the mapping
R. □
Theorem 4. Suppose V and X are closed non-empty subsets of a CFBMS such that is AC with respect to . Suppose a mapping is a Reich–Rus–Ciric type IPC if
- (i)
is nondecreasing, and are convergent BS such that then the
- (ii)
is a nonempty subset of such that
Then, R has a BPP.
Proof. Chasing the starting steps taken in proof of Theorem 3, we have
Now, the remaining proof is taken the same as the proof of 2. Thus, we obtain
is a BPP of the mapping
R. □
3.3. -Interpolative Kannan Type
Proximal Contraction
In this part, we will determine the BPP of the Kannan type IPC within the context of FBMS. Using the extensive structure of FBMS, we intend to generalize and extend the findings reported in [
17,
18,
19], which mostly concentrate on standard metric spaces or specialized contractive mappings. Furthermore, the proposed constraints guarantee the presence and uniqueness of the BPP.
Definition 19. Suppose V and X are non-empty, closed subsets of an FBMS . A mapping is said to be -Kannan type IPC if there exists , verifyingwhich impliesfor all , , , and with where are two function such that for Example 9. Let and be equipped with for all and . Then, is an FBMS with CTN . Let and define the mapping by for all . Thus, , and . Then clearly, . Define the function byHence, R is a Kannan type IPC. Furthermore, the other requirements of the definition (18) are held. Therefore, 0 is the BPP of mapping R. Consider, , , , and and .This implies thatwhich is conflicted. Hence, R is not a Kannan type IPC. Theorem 5. Suppose V and X are closed non-empty subsets of a CFBMS such that is AC with respect to . Suppose a mapping is a -Kannan type IPC if
- (i)
is nondecreasing, and for any
- (ii)
is a nonempty subset of such that
Then, R has a BPP.
Proof. Taking the same steps in Theorems 1 and 3, we can build a BS
in
such that
If
, then from (
15), obviously,
is a BPP of the mapping
R. Consider,
for all
, then
and
Then, by using (
18), we have
for all distinct
. Since
for all
, by (
20), we have
Since
is NDF, we have
This implies that
This implies that
for all
This shows that the BS
is PASD. Hence, it converges to some element
such that
. Now from (
20), we obtain the following:
This conflicts with supposition (i); hence,
and
. From supposition (i) and Lemma 3, we wind up with the BS
being a CBS in
. The remaining proof of the Theorem is taken as the same as the proof of Theorems 1 and 3. Hence, we find that
is a BPP of the mapping
R. □
Theorem 6. Suppose V and X are closed non-empty subsets of a CFBMS such that is AC with respect to . Let be a Kannan type IPC if
- (i)
is nondecreasing, and and are convergent sequences such that then the
- (ii)
is a nonempty subset of such that
Then, R has a BPP.
Proof. Chasing the starting steps taken in proof of Theorem 3, we have
Now, the remaining proof is taken the same as the proof of Theorems 2 and 4. Hence we obtain that
is a BPP of the mapping
R. □
3.4. -Interpolative Hardy–Rogers
Type Proximal Contraction
In this part, we will extend the findings of [
17,
18,
19] by introducing a generalized framework for the
-interpolative Hardy–Rogers type proximal contraction in the context of FBMS. We shall develop adequate requirements to ensure the existence of a best proximity point that is unique to this generalized contraction type. Our findings show that
-interpolative Hardy–Rogers type contractions can be used in FBMS. This considerably expands the scope of proximal contraction theory and its possible applications. This framework not only contains the classical results of [
17,
18,
19] but also opens up new directions for investigating fixed-point and best proximity point issues in more complicated and less restrictive spaces.
Definition 20. Suppose V and X is a nonempty, closed subset of an FBMS . A mapping is said to be -Hardy–Rogers type IPC if there exists satisfyingwhich impliesfor all , , , with where are two functions such that for Example 10. Let , be equipped with for all and . Then is an FBMS with CTN . Let . Define the mapping by for all . Thus, , and . Then clearly, . Define the mapping byHence, R is a Hardy–Rogers type IPC. Furthermore, the other requirements of the Definition (22) are held. Thus, 0 is the BPP of the mapping R. On the other hand, consider , , , and and .This implies thatwhich is a contradiction. Hence, R is not a Hardy–Rogers type IPC. Theorem 7. Suppose V and X are closed nonempty subsets of a CFBMS such that is AC with respect to . Suppose a mapping is a Hardy–Rogers type IPC if
- (i)
is nondecreasing, and for any
- (ii)
is a nonempty subset of such that
Then, R has a BPP.
Proof. Taking the same steps in Theorems 1, 3 and 5, we can construct a BS
in
such that
If
, then from Equation (
23), obviously,
is a BPP of the mapping
R. Consider,
for all
, then
and
Then, by using (
22), we have
for all distinct
. Since
for all
, we have
Since
is NDF, we have
Suppose
. This implies that
Suppose there exists some
such that
. Since
satisfies the ND property (
24) it follows that
which is a contradiction. The inequality
must hold for all
. As a result the sequence
is strictly increasing for all
. This indicates that the sequence
possesses the PASD property and consequently converges to a limit
such that
Applying Equation (
24) we derive the following result:
This conflicts with supposition (i); hence,
and
. From supposition (i) and Lemma 3, we wind up with BS
being a CBS in
. The remaining proof of the Theorem is taken as the same as the proof of Theorem 1. Hence, we find that
is a BPP of the mapping
R. □
Theorem 8. Suppose V and X are a closed nonempty subset of a CFBMS such that is AC with respect to . Suppose a mapping is a Hardy Rogers type IPC if
- (i)
is nondecreasing, and and are convergent BS such that then the
- (ii)
is a nonempty subset of such that
Then, R has a BPP.
Proof. Chasing the starting steps taken in proof of Theorem 3, we have
Now, the remaining proof is taken the same as the proof of Theorem 2. Then, we obtain that
is a BPP of the mapping
R. □
4. Application
Consider the Banach space
which consists of all continuous functions defined on the real interval
with
equipped with the supremum norm:
with the induced CFBMS with mapping. A mapping
for
with
where
are two function such that
for
On this setting, consider the following integral equation:
Consider the FBMS with the product of t-norm as follows:
Hence, this FBMS is complete.
Theorem 9. Suppose the integral operator on aswhere is such that , for all , and R satisfies the following condition:for all , whereThen, integral Equation (25) has a unique solution. Proof. As
, we have that
Therefore, the following holds:
Using (
26), we can write
which means that the following holds:
If we take
and
, then the above inequality can be written as follows:
Since all the conditions of the Theorem 1 hold, we conclude that (
25) has a unique solution. □
Theorem 10. Suppose an integral equationwhere is a Lebesgue measurable set. Suppose (1) There is a continuous function
and
such that
for
with
where
are two functions such that
for
(2) , i.e., .
Then, the integral equation has a unique solution in .
Proof. Let
and
be two normed linear spaces, Where
are a Lebesgue measurable set and
. Consider choosing
to be normed linear spaces (in short NLS), where
are Lebesgue measurable sets and
. Consider
. Then,
is a CBMS. Define the mapping
by
Now, we have
which means that the following holds:
If we take
and
, then the above inequality can be written as follows
Hence, all the conditions of Theorem 1 are held; the integral equation has a unique solution. □
Homotopy
Now, we study the existence of the unique solution in homotopy theory.
Theorem 11. Suppose is a CFBMS with a nonempty closed subset of V and X such that is AC with respect to . Suppose is an operator that satisfies the following conditions (a) for each and (here, is the boundary of in ); The is -PC if
- (i)
for all and
- (ii)
There are , such that
- (iii)
there exists such that for all and
- (iv)
Υ is nondecreasing and for any
- (v)
is a nonempty subset of such that
- (vi)
for all satisfying for some , there exists such that for all . If has a BPP in , then has a BPP in
Proof. Define a set
for all
. Therefore, the sequence
is PASD. Thus, there exists
such that
. Suppose that
. Let
and
, then
and
, for all
. Therefore,
which is conflicted. Thus,
Now, we show that
is a CBS. Consider that
,
is not a CBS. Then, there exists an
Suppose that
is the least integer exceeding
, satisfying the inequality (
29). Then,
Suppose that
for all
. Otherwise, there exists a subsequence
of
such that
for all
. From (
29), (
30), and the inequality (
4), we obtain that
for all
. Thus, letting
, we have
Furthermore,
is a CBS. Because
is complete,
converges, thus BC comes to a point
such that
. Now, by applying (
28), we have
Moreover,
as
. That is,
is AC with respect to
, and there exists a subsequence
of
such that
as
, such that
Let
. Therefore, there exists a subsequence
of
such that
for all
and we obtain a subsequence in the following steps.
By utilizing (
28), (
30), and the inequality (
4), we have
for all
. Therefore, by taking
, we obtain
Hence
. From the definition of
, we have
, and so
is closed in [0, 1].
Now, we shall show that is open. Let . Then, there exists such that . From (vi), for , there exists such that for all . If we consider the mappings for all , then, from (iii), the mappings are v proximal contraction. Therefore, all the hypotheses of Theorem 1 are satisfied. Hence, for all , has the best proximity in U. Moreover, . Hence, from (i) for all . Hence we have that is is open in . □