1. Introduction
In 1911, Brouwer proved that if is a nonempty, bounded, closed, and convex set and is continuous, then has a fixed point; that is, there exists a point for which .
In 1930, Schauder [
1] first established an infinite–dimensional generalization of Brouwer’s fixed point theorem (
FPT for brief) as follows.
Theorem 1. Let be a nonempty, compact, and convex subset of a Banach space . If is continuous, then φ has a fixed point.
We mention that if is a nonempty subset of a Banach space , then a function is a compact operator whenever maps bounded sets into relatively compact sets. In this situation, we can consider the following more useful version of Schauder’s FPT.
Theorem 2 (Schauder’s FPT). Let be a nonempty, bounded, closed, and convex subset of a Banach space . If is a continuous and compact operator, then φ has a fixed point.
The Schauder’s FPT is one of the most powerful tools in dealing with nonlinear problems in analysis, and, in particular, it has played a major role in the development of fixed point theory and the theory of differential equations.
Due to the fact that Schauder’s FPT has fundamental importance, the theorem has been generalized in various directions by different methods. These generalizations can be divided into two kinds. The first one is purely topological, and the second one is of probabilistic interest in connection with stochastic analysis and stochastic finance.
Let
be a metric space. A mapping
is said to be
a contraction if there exists a constant
such that
Moreover, the mapping
is called a
contractive mapping provided that
Clearly, the class of contractive maps contains the family of contractions.
In 1922, Banach established the following FPT in his thesis in order to guarantee the existence of a solution to an integral equation.
Theorem 3 (Banach’s FPT). Let be a complete metric space and be a contraction mapping. Then φ has a unique fixed point, and for each , the iterate sequence converges to the fixed point.
Banach’s FPT is extremely helpful to solve integral and differential equations, providing a constructive method to approximate their solutions with an adjustable accuracy.
It is worth noticing that Theorem 3 does not hold for contractive maps. For instance, if we consider the space
consisting of the real-valued continuous functions defined on
equipped with the supremum norm and if we set
Then
M is a closed subset of
, and so it is a complete metric space. Now, it is easy to see that the self-mapping
defined by
is a contractive mapping that is fixed-point-free.
In 1962, Edelstein ([
2]) extended the Banach contraction principle to contractive self-mappings as follows.
Theorem 4 (Edelstein’s FPT). Let be a compact metric space and be a contractive mapping. Then φ has a unique fixed point, and for each , the iterate sequence converges to the fixed point.
In [
3], Krasnoselskii observed that in some of the problems, the integration of a perturbed differential operator gives rise to a sum of two applications, a contraction and a compact application. So, he combined Banach’s
FPT and Schauder’s
FPT and obtained the next widely used result.
Theorem 5 (Krasnoselskii’s FPT). Let be a nonempty, closed, and convex subset of a Banach space . Suppose and are two maps such that
- (i)
φ is a contraction;
- (ii)
ψ is a continuous and compact operator;
- (iii)
.
Then the operator has a fixed point; that is, there exists an element for which .
Krasnoselskii’s FPT is useful in establishing existence results in some mathematical problems. Since then, a huge number of papers have appeared, contributing generalizations or modifications of Krasnoselskii’s fixed point theorem and their applications.
Meanwhile, a large class of problems, for instance in integral equations and stability theory, has been adapted by Krasnoselskii’s fixed point method. Several extensions of the theorem have been made in the literature in the course of time by modifying the conditions (i), (ii), and (iii).
Inspired by Krasnoselskii’s
FPT, Dhage in [
4] proved the following
FPT for multiplication of two maps in the framework of Banach algebras.
We recall that a Banach space
is a Banach algebra provided that there exists an operator
with
for all
which is associative and bilinear and that
Theorem 6 (Dhage’s FPT). Let be a nonempty, bounded, closed, and convex subset of a Banach algebra and let , be two operators such that
- (i)
φ is a contraction with the contractive constant ;
- (ii)
ψ is a continuous and compact operator;
- (iii)
.
If , where , then has a fixed point, i.e., there exists a point such that .
The hybrid FPTs in Banach algebras are also useful for proving the existence theorems for certain nonlinear differential and integral equations. Here in this paper, we illustrate the applicability of an extension of Dhage’s FPT (Corollary 4) by considering nonlinear functional integral equations (see Examples 3 and 4).
The current paper consists of five sections.
Section 1 is the introduction, and
Section 2 describes the concepts of proximal pairs, projection operators, and best proximity points for non-self-maps and relates some basic facts.
In
Section 3, we present the best proximity version of Edelstein, Krasnoselskii, and Dhage
FPTs (Theorems 4–6).
Section 4 is devoted to obtaining a generalization of Sadovskii’s
FPT, which leads to obtaining extensions of Darbo and Schauder
FPTs in the setting of strictly convex Banach spaces.
Finally, in
Section 5, we use our existence results to give an application to complex function theory and find a solution to a class of nonlinear functional integral equations.
We also define a notion of mutually nearest solutions for a system of integral equations and study their existence by applying a best proximity version of Schauder’s FPT.
2. Preliminaries
We recall that a Banach space is said to be strictly convex if for any two distinct points such that , it is the case that . Hilbert spaces and spaces are instances of strictly convex Banach spaces.
Let
and
be nonempty subsets of a metric space
. We will say that a pair
has a property if and only if both the sets
and
have that property. For instance,
being closed means that both
and
are closed subsets of
. We set
Also, the
proximal pair of the pair
is denoted by
, where
In general, the proximal pairs may be empty. However, if is a compact pair in a metric space M or is a bounded and closed pair in a reflexive Banach space , then its proximal pair is nonempty.
Definition 1.
A nonempty pair in a metric space is said to be proximinal if and .
For a nonempty subset
of a metric space
M, a
metric projection operator is defined with
It is worth mentioning that if is a nonempty, bounded, closed, and convex subset of a reflexive and strictly convex Banach space , then the metric projection is a single-valued map from onto .
The next proposition plays a fundamental role in the proof of our main corollaries in this paper.
Proposition 1 ([
5])
. Assume is a strictly convex Banach space and is a nonempty, closed, and convex pair in for which is nonempty. Define a map withThen the following statements hold:- (i)
for any and is cyclic on , i.e., and ;
- (ii)
and are isometry;
- (iii)
and are affine;
- (iv)
and , where denotes the identity mapping on a nonempty subset A of .
Here, we recall a geometric concept on a nonempty pair of subsets of a metric space which was first introduced in [
6].
Definition 2.
Let be a pair of nonempty subsets of a metric space such that . The pair is said to have the P-property if and only ifwhere and . It is clear that for a nonempty subset of a metric space , the pair has the P-property.
Remark 1.
It was proved in [
7]
that every nonempty and convex pair in a strictly convex Banach space has the P-property. Furthermore, it is worth noticing that the strict convexity assumption of the Banach space in Proposition 1 can be replaced by the P-property of (see [
7]
for more details). Definition 3.
Let be a pair of nonempty disjoint subsets of a metric space and be a non-self-mapping. A point is said to be a best proximity point of φ provided that The relevance of best proximity points is that they provide optimal solutions for the problem of best approximation between two disjoint sets.
We mention that in 2011, Sadiq Basha [
8] introduced a class of non-self-maps, called proximal contractions of the first and second kinds, to investigate the existence, uniqueness, and convergence of a best proximity point (see also [
9] for more details).
4. Sadovskii Proximal Condensing Operators
In this section, we apply a concept of measure of noncompactness to introduce a new family of condensing operators that satisfy the Sadovskii contractive condition.
To this end, we recall the notion of measure of noncompactness, which was used to extend Schauder’s FPT. Throughout this section, stands for the set of all nonempty and bounded (compact) subsets of a Banach space .
Definition 5. A function is said to be a measure of noncompactness (MNC) if it satisfies the following axioms:
- (1)
The family is nonempty and ;
- (2)
, ;
- (3)
If , then , where ;
- (4)
, where denotes the convex hull of the set ;
- (5)
If for a nonincreasing sequence of nonempty, bounded and closed subsets of , then Note that .
A trivial example of MNCs is the function
We refer to [
10] for more interesting examples and applications of MNCs.
Consider a non-self-map where is a nonempty, bounded, closed, and convex pair in a Banach space with and .
By we denote the set of all pairs such that is a nonempty, closed, convex and proximinal pair with and . It is worth noticing that .
We are now in a position to introduce a novel family of non-self-mappings by using the concept of MNC as follows.
Definition 6.
Let be a nonempty, bounded, closed, and convex pair in a Banach space such that , and let μ be an MNC
on . We say that is a Sadovskii proximal condensing
operator if and Note that if
in the above definition, then we get the concept of
-condensing operator, which was considered in [
11].
Here is the main result of this section.
Theorem 10. Suppose is a nonempty, bounded, closed, and convex pair in a strictly convex Banach space such that , and let μ be an MNC on . If is a continuous Sadovskii proximal condensing operator, then φ has a best proximity point.
Proof. Let
be such that
. Then
. Set
Note that
. Let
Then , and so, . Clearly, is closed, convex, and -invariant.
To show the proximinality of the pair , assume that . Then for each index i where . Since the pair is proximinal for all i, there is a point for which .
The strict convexity assumption of the Banach space implies that for all i, and so . Thus, the pair is also proximinal, which ensures that and that is a minimal element of w.r.t. the reverse inclusion relation.
Note that if
, then
. In this situation, the mapping
is a continuous and compact operator. By Proposition 1, since
is cyclic on
,
which concludes that
is a compact operator that maps the convex set
into itself, continuously. It now follows from Schauder’s
FPT that
Then
and the result follows in this case.
So, assume that
. Define
Note that , which deduces that . By definition, the pair is proximinal. Also, is closed and convex.
We show that is closed. Let be a sequence in such that . Then for each , there is a point such that . Since is continuous, . Also, by the fact that , we obtain . So, , that is, is closed.
To see the convexity of
, it is sufficient to note that by Proposition 1,
is affine, and the result follows. Furthermore,
and so,
Thus
which ensures that
is
-invariant. Hence,
and by the minimality of
, we must have
Now, by this reality that
is a Sadovskii proximal condensing operator, we have
which is a contradiction, and this completes the proof. □
Remark 4.
It is remarkable to note that we can replace the strict convexity assumption of the Banach space in Theorem 10 with the P-property of the pair .
The next results are obtained from Theorem 10.
Corollary 5 (Sadovskii’s
FPT; [
12])
. Suppose is a nonempty, bounded, closed, and convex subset of a Banach space , and let μ be an MNC
on . If is a continuous map such thatfor all nonempty set with , then φ has a fixed point. Proof. By considering in Theorem 10, the result follows. Note that we do not need the strict convexity of the Banach space , because has the P-property. □
Corollary 6
([
13])
. Suppose is a nonvoid, bounded, closed, and convex pair in a strictly convex Banach space such that and let μ be an MNC
on . If is a continuous map such that andfor some , then φ has a best proximity point. Corollary 7
(Darbo’s
FPT; [
14])
. Suppose is a nonempty, bounded, closed, and convex subset of a Banach space , and let μ be an MNC
on . If is a continuous map such that there exists for whichfor all nonempty set . Then φ has a fixed point. The next result is the best proximity version of Schauder’s FPT.
Corollary 8.
Let be a nonempty, bounded, closed, and convex pair in a strictly convex Banach space such that . Suppose is a compact and continuous operator for which . Then φ has a best proximity point.
5. Applications
In the latest section of this paper, we present some applications related to the previous results.
5.1. Application to Complex Function Theory
Theorem 11. Consider a nonempty, bounded, closed, and convex pair of subsets of a domain in the complex plane. Suppose φ is analytic in , which maps into , and is a mapping for which for all . If for all , then there exists a unique point such that Proof. Since
is a compact pair,
is nonempty. Moreover, since the complex plane with Euclidean norm is strictly convex and the pair
is convex, by a result of [
7],
has the
P-property.
Now let
be an arbitrary element. Then there is a point
such that
. From the hypothesis of the theorem, we must have
which implies that
and so,
. Furthermore, for any
we have
that is,
is a contractive non-self-mapping. Hence, the result follows by invoking Corollary 2. □
Corollary 9.
Let be a nonempty, bounded, closed, and convex subset of a domain in the complex plane. Assume that φ is analytic in , which maps into itself. If for all , then φ has a unique fixed point.
Proof. It is sufficient to consider and in Theorem 11. □
5.2. Application to Nonlinear Functional Integral Equations
In the continuation of this section, we focus on hybrid FPTs obtained in Corollary 3 and Corollary 4 to guarantee the existence of solutions of two classes of nonlinear functional integral equations.
The first class of integral equations, which is considered in Example 3, contains the sum of two operators, and the second class of integral equations, which appears in Example 4, consists of the multiplication of two operators.
In this way, for the first family of integral equations, we need to use an extension of Krasnoselskii’s FPT, which was concluded in Corollary 3, and for the second category of nonlinear functional integral equations, we apply a generalization of Dehage’s FPT, which was deduced in Corollary 4.
Example 3.
Given a closed interval and , the following nonlinear functional integral equation (NFIE)
where is a continuous and bounded function, has a solution. Proof. Consider a Banach space
endowed with the supremum norm and define
where
for some
. By using Arzela–Ascoli’s theorem, we find that
is a compact subset of
, and it is easy to see that
is convex. Let
and
be defined by
Note that
is continuous. Also, for all
we have
which deduces that
that is,
is a contractive map. Moreover, for any
we have
and
which implies that
. Now by applying Corollary 3, the NFIE (
1) has a solution. □
Example 4.
For some consider the following NFIE
where is a continuous function. If for all , then Equation (
2)
has a solution. Proof. Consider a Banach algebra
and define
Arzela–Ascoli’s theorem implies that
is a compact subset of
. Let
and
be defined as
By a similar proof of Example 3,
is contractive. Moreover,
is continuous and
and so,
. We also note that
for all
. Furthermore, for any
and
we have
Thereby,
. Thus, all of the assumptions of Corollary 4 are satisified, and so the NFIE (
2) has a solution. □
5.3. Application to a System of Integral Equations
As another application of our main conclusions, we investigate the existence of a mutually nearest solution for a system of integral equations that does not have a common solution.
To this end, let , , and be such that . Assume that are continuous non-negative real functions on R.
Also, let
be such that
for all
and
. Let us consider the following system:
We note that the above system does not have a common solution for both equations. To define an appropriate solution for this system, we need the following requirements.
Let
be renormalized according to
It is well-known that
is a non-reflexive strictly convex Banach space such that
for all
. Set
Obviously, the pair
is closed and convex in
and
. Suppose that
is a common bound for the functions
on
R. Choose
and consider the closed interval
. Now define a non-self-mapping
with
Then
, and clearly,
. Also, for any
we have
Thus, , and so, maps the set into .
We are now in a position to introduce the following notion for the system (
3).
Definition 7.
A function is a mutually nearest solution for the system of integral Equation (
3)
provided that ϰ is a best proximity point for the non-self-mapping φ defined in Equation (
4).
We now state the following existence result.
Theorem 12. Under the aforementioned notations and definitions, ifprovided that , then the system (
3)
has a mutually nearest solution. Proof. At first, let us estimate the distance between two sets
and
. For any
, we have
and so
It now follows from the definition of the norm
on
that
On the other hand, since
, we must have
. Thus,
. Also, since
is strictly convex, the proximal pair
is closed ([
7]), and it is easy to see that it is also convex.
We assert that
. In this regard, define a map
as follows:
Then
and
. Moreover,
which deduces that
maps the set
to the set
. Set
Hence for an element
by choosing the constant
we obtain
Thereby,
which yields that
Now to show
, suppose that
. Then there is an element
for which
. It follows from the inequality (
6) that
which guarantees that
. Furthermore,
is continuous, and for any
, we have
and so, the class of
is bounded. Furthermore, for any
and
we have
which concludes that
is equicontinuous. Hence, by applying Arzela–Ascoli’s theorem, the set
is relatively compact.
Now, Corollary 8 ensures the existence of a best proximity point for the mapping
, which is a mutually nearest solution for the system (
3). □