1. Introduction
In the study of fractals, best proximity points can be used. Best proximity points can be used to estimate or comprehend the behavior of these fractals at various scales because fractals are frequently generated through iterated processes. In this case, optimal proximity points could be used to predict how iterated mappings will behave in the setting of the Julia set or Mandelbrot set (fractal sets constructed through iteration). Modeling complex phenomena requires the use of fractional calculus, which deals with derivatives and integrals of noninteger order. Best proximity points are often utilized to approximately solve fractional differential equations. Finding precise answers to these problems can be difficult since they sometimes require fractional-order derivatives. In certain situations, the best proximity points can offer approximations of solutions. In conclusion, the mathematical methods and applications of fixed point theorems, best proximity point theorems, fractals, and fractional calculus are connected. Together, they are frequently employed to comprehend and simulate intricate nonlinear circumstances, particularly when classical calculus is insufficient.
In 1906, the theory of metric space was introduced by Fréchet [
1]. From 1906 to now, numerous generalizations of metric space have been introduced by altering the metric function. Fixed point (FP) theory is an important tool for obtaining a unique solution of different type of problems. A mapping
has an FP if
. The Banach contraction principle [
2] is an origin of FP theory. Even in the present time, for the benefit of human beings, researchers of several fields including computers, physics, applied mathematics, and many others are benefiting from using the Banach contraction principle. Sessa et al. [
3] demonstrated some FP results and provided an application for nonlinear differential equation. In 1968, Kannan [
4] gave some FP results and enhanced the era of fixed point theory. Then, in 1968, Fan [
5] proved some FP results by the extension of two FP theorem of Browder. In 2018, Karapinar [
6] re-examined the Kannan FP theorem with regards to interpolation. Ishtiaq et al. [
7] demonstrated FP results with the help of interpolation and gave the application for fractional differential equations.
In 1997, the concept of best proximity point (BPP) and best approximity was given by Basha and Veeramani [
8]. In 2011, Basha [
9] initiated some BPP theorems for contractive non-self mappings. In 2012, Basha and Shahzad [
10] provided the BPP theorem for generalized proximal contractions of the first and second kind in the setting of complete metric space. In 2020, Altun et al. [
11] presented the concept of p-proximal contraction and p-proximal contractive non-self mappings on metric space. In 2021, Altun et al. [
12] derived some BPP theorems for interpolative proximal contraction (IPC) and proved Reich–Rus–Ceric and Kannan-type proximal contraction of the first and second kind. Ishtiaq et al. [
13] provided common BPP theorems for proximal contractions, Kannan-type IPC, Reich–Rus–Ciric-type IPC, and Hardy–Rogers-type IPC. Karapinar [
6] initiated Kannan-type IPC and proved some FP theorems. Karapinar et al. [
14] initiated Reich–Rus–Ciric-type IPC and proved some FP theorems.
Mutlu and Gurdal [
15] established the notion of bipolar metric space (BMS) and discussed the basic properties and derived some FP results. Mani et al. [
16] demonstrated the FP results in the context of BMS under the simulation function. Kurepa [
17] presented the notion of pseudo-metric space (PMS). Khajasteh et al. [
18] introduced simulation function and proved some FP results for bipolar metric space. Semet et al. [
19] proved some FPs results for
contractive mappings in complete metric space. Gurdal et al. [
20] proved some FP results for
contractive mappings in bipolar metric spaces. Lateef [
21] proved best proximity points in
-metric spaces. Nashine et al. [
22] proved several best proximity point theorems for rational proximal contractions.
In this work, we prove some BPP results in a complete bipolar metric spaces (CBMS). Moreover, we introduce proximal contraction (PC), Reich–Rus–Ceric-type IPC, Kannan-type IPC of the first and second kind. Also, we provide some examples to illustrate the validity of our results, an application to find the solution to an integral equation, and a nonlinear fractional differential equation.
2. Preliminaries
In this section, we provide some basic definitions and results that will help to the readers to understand the main results.
Definition 1 ([
17])
. A PMS is a set together with a non-negative real valued function , called a PM, such that for every :- 1.
- 2.
- 3.
Like a metric space, points in PMS need not be distinguishable, that is, one may have for distinct values of .
Definition 2 ([
15])
. Let , and be a function, satisfying some of the axioms: - (a1)
if then , ∀;
- (a2)
if then , ∀;
- (a3)
, ∀;
- (a4)
, ∀ and .
Then,
- (i)
If and hold, then is said to be a bipolar pseudo-semimetric (BPSM) on the pair .
- (ii)
If is a BPSM verifying , it said to be a bipolar pseudo-metric (BPM).
- (iii)
A BPM satisfying (a1), is called a BMS.
Definition 3 ([
15])
. Let and be a BPSM. A map is called continuous at a point , if for every , there exists a such that whenever and , . It is continuous at a point if for each , there exists a such that whenever and , . If is continuous at every point and , then it is said to be continuous.
Definition 4 ([
15])
. Let be a BPSM. - (i)
A sequence on the set is said to be a bisequence (in short, BS) on .
- (ii)
If both sequences and converge, then the BS is said to be convergent. If and both converge to the same point , then this BS is said to be biconvergent (in short, BC).
- (iii)
A bisequence on is said to be Cauchy bisequence (in short, CBS), if for each , there exists a number , such that for all positive integers , .
Definition 5 ([
15])
. A BMS is called complete if every CBS in this space is convergent. Theorem 1 ([
15])
. Let be a complete BPSMS and a contraction . Then, it has a unique FP. Definition 6 ([
11])
. Let be an MS and ,. A mapping is said to be a proximal contraction if there exists a real number such thatthis gives usfor all . Definition 7 ([
12])
. Let be an MS and ,. We will consider the following subsets:and Definition 8 ([
12])
. Let be an MS and ,. We say that is acompact with respect to if each sequence in verifyingfor some has a convergent subsequence. Definition 9 ([
12])
. Let be an MS and ,. An element in is called a BPP of the mapping , if the following equation,is satisfied. 3. Main Results
In this section, we prove several BPP results by utilizing generalized interpolative contractions on BMS and provide some nontrivial examples.
Definition 10. Let be a BMS, and and be nonempty subsets of and . We will consider the following subsets:and Definition 11. Let be a BMS and and be nonempty subsets of and , respectively. We say that is acompact with respect to if every sequence in satisfying the followingfor some has a convergent subsequence. Definition 12. Let be a BMS and and be nonempty subsets of and , respectively. An element is called a BPP of the mapping if it satisfies the equationSome generalized definitions are given below. Definition 13. Let be a BMS and and be nonempty subsets of and , respectively. The mapping is called proximal contraction (in short, PC) on BMS if there exists a real number such thatfor all , , , Definition 14. Let be a BMS and and be nonempty subsets of and . The mapping is called K-PC on BMS if there exists a real number such thatfor all , , , . Definition 15. Let be a BMS and and be nonempty subsets of and , respectively. The mapping is called Reich–Rus–Ciric-type IPC on BPS if there exists a real number such thatfor all , , , . In this paper, we aim to obtain some BPP results via the interpolative idea. Now, we give some definition via interpolative contraction.
Definition 16. Let be a BMS and and be nonempty subsets of and . The mapping is called Reich–Rus–Ciric-type IPC of the first kind on BMS if there exists a real number and such thatfor all , , , . Definition 17. Let be a BMS and and be nonempty subsets of and . The mapping is called Reich–Rus–Ciric-type IPC of the second kind on bipolar metric space if there exists a real number and such thatfor all , , , . Definition 18. Let be a BMS and and be nonempty subsets of and . The mapping is called Reich–Rus–Ciric-type IPC of the first kind on bipolar metric space if there exists a real number and such thatfor all , , , . Definition 19. Let be a BMS and and be nonempty subsets of and . The mapping is called Reich–Rus–Ciric-type IPC of the second kind on BMS if there exists a real number and such thatfor all , , , . Note that if we take
, then the inequalities (
4) and (
6) become
and
for all
, respectively. The mapping
satisfying (
8) (respectively, (
9)) is called Reich–Rus–Ciric (respectively, Kannan)-type IPC on BMS in the literature.
Similarly, when
, the inequalities (
5) and (
7) become
and
for all
, respectively.
Now, we present our main results.
Theorem 2. Let be a CBMS, ,, , and such that is acompact with respect to . Let be a proximal contraction such that is nonempty and . Then has a BPP.
Proof. Suppose that
. Since
, then there exists
such that
Similarly, since
, there exists
such that
Carrying on this process, we can produce a sequence
in
such that
Thus, if there exists some
such that
, then from (
11), the point
is a BPP of the mapping
. On the other hand, if
for all
then
and
then by using (
1), we have
for all
. Therefore, the sequence
is decreasing BS of positive real numbers. Hence, it converges to some element
such that
. Now from (
12), we have
for all
. Supposing
in the last inequality, we have
. Now, for
with
, say
and
, we obtain
and similarly
.
Let . Since , there exists an such that . Then and is a CBS.
Since
is complete.,
converges, thus, BC to a point
such that
. Moreover, from (
11), it can be noted that
Therefore,
as
. Since
is acompact with respect to
, there exists a subsequence
of
such that
as
. Therefore, by taking
in
, we have
, and so
. Also, since
, there esits
such that
Suppose that for all . Otherwise, there exists a subsequence of such that for all and so we can observe this subsequence in the following steps.
From (
11), (
13), and the inequality (
1), we obtain that
for all
. Thus, letting
, we have
That is,
. From (
13), the point
is a BPP of the mapping
. □
Theorem 3. Let be a CBMS and ,, and such that is acompact with respect to . Let be a Reich–Rus–Ciric-type IPC of the first kind such that and . Then has a BPP.
Proof. Suppose that
. Since
, then there exists
such that
Similarly, since
, there exists
such that
Carrying on this process, we can produce a sequence
in
such that
Now, if there exists
such that
, then from (
14), the point
is a BPP of the mapping
. Hence, we suppose that
for all
. Since
and
for all
, then by using (
4) we have
which produces that
for all
. Therefore, the sequence
is decreasing BS of positive real numbers. Thus, there exists
such that
. Now, from (
15) we have
for all
. Supposing
in the last inequality, we have
. Now, for
with
, say
and
, we obtain
and, similarly,
.
Let . Since , there exists an such that . Then and is a CBS.
Since
is complete,
converges, thus, BC, to a point
such that
. Moreover, from (
14), it can be noted that
Therefore,
as
. Since
is acompact with respect to
, there exists a subsequence
of
such that
as
. Therefore, by taking
in
, we have
, and so
. Also, since
, there exists
such that
Suppose that for all . Otherwise, there exists a subsequence of such that for all and so we can consider this subsequence in the following steps.
From (
14), (
16), and the inequality (
4), we obtain that
for all
. Thus, letting
, we have
That is,
. From (
16), the point
is a BPP of the mapping
. □
Theorem 4. Let be a CBMS and ,, , and such that is compact with respect to . Let be a Kannan-type IPC of the first kind such that is nonempty and . Then, has a best proximity point.
Proof. Chasing the steps in the proof of Theorems 2 and 3, we achieve the objective. □
If we take in Theorems 3 and 4, we obtain the following FP results:
Corollary 1. Let be a CBMS and be a Reich–Rus–Ciric-type IC. Then, has a unique FP.
Proof. It is easy to show on the lines of the Theorem in [
14]. □
Corollary 2. Let be a CBMS and be an Kannan-type IC. Then, has a unique FP.
Proof. It is immediate from Theorem in [
6]. □
Theorem 5. Let be a CBMS and and be nonempty, , and such that is approximately compact with respect to . Let be a Reich–Rus–Ciric-type IPC of the second kind such that is nonempty and . Then, has a BPP.
Proof. Proceeding as in Theorem 3, it is possible to find a sequence
in
such that
for all
. Now if there exists
such that
, then from (
14), the point
is a BPP of the mapping
. Hence, we suppose that
for all
. Since
and
for all
, then by using (
5) we have
which produces that
for all
. Eventually,
is a CBS in
. Since
is complete,
converges, thus, BC, to a point
such that
. Moreover, from (
17), it can be noted that
Therefore,
as
. Since
is Acompact with respect to
, there exists a subsequence
of
such that
as
. Therefore, by taking into account the continuity of
, we have from (
17)
Thus, the point is a BPP of the mapping □
Using the similar technique of Theorem 5, we can obtain the following theorem:
Theorem 6. Let be a CBMS and ,, and and such that is acompact with respect to . Let be a Kannan-type IPC of the second kind such that is nonempty and . Then, has a BPP.
Now, we present some illustrative examples.
Example 1. Let be a BMS. Define the BMS by . Let , and , where and . Define the mapping by . Thus, and , and . Then, clearly, . This shows that is a proximal contraction. Also, we can easily see that the other conditions of Theorem 2 hold. Then, has a BPP which is 0.
Example 2. Let be a BMS. Define the bipolar metric space by . Let , and , where and . Define the mapping by . Thus, and , and . Then, clearly, . This shows that is a Kannan-type IPC of the first kind. Also, we can easily see that the other conditions of Theorem 4 hold. Then, has a best proximity point which is 0
. On the other hand, consider , , , and . This implies thatwhich is a contradiction. Hence, is not a proximal contraction. Also, for K-proximal contraction,which is a contradiction. That is, is not a K-proximal contraction of the first kind. Example 3. Let be a BMS. Define the bipolar metric space by . Let , and where, and . Define the mapping by . Thus, and , and . Then, clearly, . This shows that is a Reich–Rus–Ciric-type IPC of the first kind. Also, we can easily see that the other conditions of Theorem 3 hold. Then, has a BPP which is 0
. On the other hand, consider , , , and . This implies thatwhich is a contradiction. Hence, is not a Reich–Rus–Ciric-type IPC of the first kind. 4. Application
Now, we examine the existence and unique solution to an integral equation as an application for proximal contraction.
Theorem 7. Let us consider an integral equationwhere is a Lebesgue-measurable set. Suppose: - (1)
There is a continuous function and such thatfor ; - (2)
, i.e., .
Then, the integral equation has a unique solution in .
Proof. Let be a normed linear space, where are Lebesgue-measurable sets and .
Consider to be defined by for all . Then, is a CBMS.
Define the mapping
by
Hence, all conditions of Theorem 2 hold. That is, the integral equation has a unique solution. □
Theorem 8. Let be a CBMS, and be nonempty, , and such that is approximately compact with respect to . Let be a proximal contraction such that is nonempty and . Then, has a best proximity point.
Proof. Proceeding Theorem 2
for all
. Therefore, the sequence
is decreasing BS of positive real numbers. Thus, there exists
such that
. Assume that
. Let
and
, then
and
, for all
. Therefore,
which is a contradiction. Thus,
Now, we show that
is a CBS. On the contrary, assume that
is not a CBS. Then, there exists an
for which we can find a subsequence
of
such that
Suppose that
is the least integer exceeding
satisfying the inequality (
19). Then,
Suppose that for all . Otherwise, there exists a subsequence of such that for all and so we can consider this subsequence in the following steps.
From (
19), (
20) and the inequality (
1), we obtain that
for all
. Thus, letting
, we have
Therefore,
is a CBS. Since
is complete,
converges, thus, BC, to a point
such that
. Moreover, from (
18), it can be noted that
Therefore,
as
. Since
is a compact with respect to
, there exists a subsequence
of
such that
as
. Therefore, by taking
in
, we have
, and so
. Also, since
, there exists
such that
Suppose that for all . Otherwise, there exists a subsequence of such that for all and so we can consider this subsequence in the following steps.
From (
18), (
21) and the inequality (
1), we obtain that
for all
. Thus, letting
, we have
That is,
. From (
21), the point
is a BPP of the mapping
. That is,
. From (
21), the point
is a BPP of the mapping
. □
Theorem 9. Let us consider an integral equation,where is a Lebesgue-measurable set. Suppose: - (1)
There is a continuous function and such thatfor ; - (2)
, i.e., .
Then, the integral equation has a unique solution in .
Proof. Let be a normed linear space, where are Lebesgue-measurable sets and .
Consider to be defined by for all . Then, is a CBMS.
Define the mapping
by
Now, we have
which implies that
We consider the simulation function as
. Then,
Therefore, all conditions of Theorem 8 hold. Hence, the integral equation has a unique solution. □
5. Application to Nonlinear Fractional Differential Equation
In this section, we apply Theorem 2 to examine the existence and uniqueness of a solution of nonlinear fractional differential equation given by
with boundary conditions
where
means a Caputo-fractional derivative of order
, given by
and
is a continuous function. We assume that
into
with supremum
.
The Riemann–Liouville fractional integral of order
is provided by
Firstly, we examine the simple form for a nonlinear fractional differential equation before finding the existence of a solution. For this, assume the below fractional differential equation:
where
is a continuous function,
is continuous,
And verifying the below condition
for all
and
K is a constant with
, where
Then, Equation (
22) has a unique solution.
Proof. Let for all . □
Then,
is a complete BMS. We define a mapping
by
for all
. Equation (
22) has a unique solution
if and only if
for all
. Now,
By applying
and (
24), we obtain
That is, all the conditions of Theorem 2 are satisfied. Hence, has a unique solution.