Abstract
In the present article, the Schauder-type fixed point theorem for the class of fuzzy continuous, as well as fuzzy compact operators is established in a fuzzy normed linear space (fnls) whose underlying t-norm is left-continuous at . In the fuzzy setting, the concept of the measure of non-compactness is introduced, and some basic properties of the measure of non-compactness are investigated. Darbo’s generalization of the Schauder-type fixed point theorem is developed for the class of -set contractions. This theorem is proven by using the idea of the measure of non-compactness.
Keywords:
Schauder fixed point theorem; fuzzy normed linear space; t-norm; measure of non-compactness MSC:
03B52; 03E72; 46B20; 46B99; 46A19; 03E70; 15A03; 54H25
1. Introduction
In 1930, Schauder established an important theorem in the field of fixed point theory. The theorem stated that “If B is a compact, convex subset of a Banach space X and is a continuous function then f has a fixed point.” However, to develop more results in functional analysis, Schauder relaxed the compactness by closedness. The theorem has an enormous influence on the theory of differential equations. At first, the Schauder-type fixed point theorem was applied to Peano’s existence theorem for the first order differential equations. After that, many interesting applications of this theorem were given to differential equations. For example, in 2007, Chu and Torres [1] proved the existence of positive solutions to the second order singular differential equations with the help of this fixed point theorem. In 2009, A. F. Dizaji et al. [2] determined the sufficient condition for the existence of periodic solution of the initial value problems, which correspond to the Duffing’s oscillator with time varying coefficients as an application of the Schauder-type fixed point theorem. Recently, in 2019, Shengjun Li et al. [3] established the existence of the periodic orbits of rapidly symmetric systems with a repulsive singularity. The line of proof of this existence problem is based on the use of Schauder’s fixed point theorem. Moreover, the global existence of the solution for a class of functional equations is also studied using the Schauder fixed point theorem, which arises in various types of neural networks such as the Hopfield neural network, the Cohen–Grossberg neural network, cellular networks, etc. For the references, please see [4,5,6].
Due to its huge application in real-life problems, much scientific attention has been drawn towards the generalization of this theorem. In 1935, A. N. Tychonoff [7] extended Schauder’s theorem to locally convex spaces. In 1950, M. Hukuhara [8] unified both the theorem of Schauder and Tychonoff. In 1955 [9], G. Darbo extended the Schauder theorem to a more general class of mappings, the so-called -set contractions, which contain compact, as well as continuous mappings. Darbo proved this theorem using the concept of Kuratowski’s measure of non-compactness. In 1961 [10], Ky Fan generalized both Schauder’s and Tychonoff’s theorem for the class of continuous set-valued mappings. In recent years, a significant contribution has been made towards the generalization of Schauder’s fixed point theorem. For example, in 2012, R. L. Pouso [11] introduced a new version of Schauder’s theorem for the class of discontinuous operators. In 2013, R. P. Agarawal et al. [12] established this theorem in semilinear Banach spaces. In 2016, Wei-Shih Du [13] generalized this theorem in an another direction, i.e., the compactness assumption is replaced by the finite open cover, and the continuity condition is totally removed.
On the other hand, several authors, viz. Xio and Zhu, Bag and Samanta, and Zhang and Guo, have played important roles in the process of the formulation of the Schauder-type fixed point theorem in the fuzzy setting. For the references, please see [14,15,16]. However, all of them considered the underlying t-norm as the continuous t-norm. Therefore, naturally, a question may arise: Is it possible to prove the Schauder-type fixed point theorem in a fuzzy normed linear space (fnls) w.r.t. the general t-norm?
In this paper, we try to give an affirmative answer to this question.
In this paper, we develop the Schauder-type fixed point theorem for a fuzzy continuous, as well as a fuzzy compact operator in an fnls whose underlying t-norm is left-continuous only at We also establish Darbo’s generalization of the Schauder-type fixed point theorem in the fuzzy setting for the class of -set contraction mappings using the properties of the measure of non-compactness.
This article is divided into three parts. Section 2 deals with preliminary results, which are used in the subsequent sections. In Section 3, the Schauder-type fixed point theorem for the class of fuzzy continuous, as well as fuzzy compact mappings is established in generalized fnls. In Section 4, the definition of the measure of non-compactness is given, and some basic properties are studied to prove Darbo’s generalization of the Schauder-type fixed point theorem.
2. Preliminaries
Definition 1
([17]). Let X be a linear space over the field (). A fuzzy subset N of ( is the set of all real numbers) is called a fuzzy norm on X if:
(N1)
(N2)
(N3)
(N4)
(N5) is a non-decreasing function of and
The triplet is referred to as an fnls.
Throughout the paper, we assume the following conditions:
- For each is a left-continuous function w.r.t.
- The t-norm ∗ is left-continuous at one with respect to the first or second component.
Theorem 1
([17]). Let be a finite-dimensional fnls in which the underlying t-norm ∗ is continuous at Then, a subset A is compact iff A is closed and bounded.
Lemma 1
([18]). Let be an fnls. Then:
Proposition 1
([18]). Let be an fnls. Then, the function defined by is a fuzzy metric space defined by H. Wu [19]. Thus, the family (the collection of all neighborhoods ) induces a Hausdorff topology τ such that is a base for τ and τ also satisfies the first countability axiom, where
Definition 2
([20]). A fuzzy metric space is called compact if is compact.
Theorem 2
([20]). A fuzzy metric space is fuzzy totally bounded iff every sequence has a Cauchy subsequence.
Note 1.
The above result is also true ifis the H. Wu-type fuzzy metric space.
Definition 3
([21]). Let be an fnls. Let be a sequence in Then, is said to be convergent if such that:
In that case, x is called the limit of the sequence and is denoted by
Definition 4
([21]). A subset A of an fnls is said to be fuzzy bounded if for each such that
Definition 5
([21]). Let be an fnls. A subset F of X is said to be closed if for any sequence in F, it converges to x, i.e.,
implies that
Definition 6
([21]). Let be an fnls. A subset B of X is said to be the closure of F if for any ∃, a sequence in F such that:
We denote the set B by
Definition 7
([21]). Let be an fnls. A subset A of X is said to be compact if any sequence in A has a subsequence converging to an element of
Definition 8
([21]). A sequence is said to be Cauchy if
This definition of a Cauchy sequence is equivalent to Throughout the paper, we use this as the definition of the Cauchy sequence.
Lemma 2
([22]). Let be an fnls. If is fuzzy bounded, then is also.
Definition 9
([22]). Let and be two fnlss. A linear operator is called a fuzzy compact linear operator if for every fuzzy bounded subset M of X, the subset of Y is relatively compact, i.e., is a compact set w.r.t. .
Theorem 3
([22]). Let be a linear operator and be continuous at Then, T is a fuzzy compact linear operator iff it maps every bounded sequence in onto a sequence in , which has a convergent subsequence.
Lemma 3
([23]). A fuzzy metric space is sequentially compact iff it is compact.
Note 2.
By Lemma 3, in an fnls, Definition 2 and Definition 7 are equivalent.
Theorem 4
([24]). In an fnls , a subset A of X is fuzzy bounded iff A is bounded in topology
Theorem 5
([24]). In an fnls the following statements are equivalent:
- (i)
- A is fuzzy totally bounded.
- (ii)
Theorem 6
([24]). Let be an fnls and be a compact set in Then, K is fuzzy totally bounded.
Definition 10
([25]). An fnls is a fuzzy Banach space if its induced fuzzy metric is complete.
Definition 11
([26]). A subset A of an fnls is called fuzzy totally bounded if:
Theorem 7
([26]). Let be a mapping where and are fnlss. Then, the following statements are equivalent:
- (i)
- T is fuzzy continuous on
- (ii)
- T is continuous on
- (iii)
- T maps a fuzzy bounded set to a fuzzy bounded set.
Theorem 8.
In a fuzzy Banach space if a subset A of X is fuzzy totally bounded, then it is compact in
Proof.
Consider a sequence in By Theorem 2, has a Cauchy subsequence. Since is fuzzy Banach space, then the Cauchy subsequence of is convergent in Therefore, by Definition 7, A is compact in □
Definition 12
([27]). (Fuzzy continuous) A mapping T from to is said to be fuzzy continuous at if for given such that :
If T is fuzzy continuous at each,
, then T is fuzzy continuous on
Definition 13
([27]). (Sequentially fuzzy continuous) A mapping T from to is said to be sequentially fuzzy continuous at if for any sequence with implies i.e.,
Theorem 9
([27]). Let be a mapping where and are fnlss. Then, T is fuzzy continuous iff it is sequentially fuzzy continuous.
Note 3.
From Definition 9, it is clear that if T is a fuzzy compact linear operator, then T maps bounded sets of X to bounded sets of Y by Theorem 4. Thus, T is a continuous mapping from to
3. Schauder-Type Fixed Point Theorem
In this section, we first define the uniformly fuzzy convergence and pointwise fuzzy convergence for a sequence of functions and investigate the relation between them. After that, we propound three types of Schauder-type fixed point theorems for the fuzzy compact class, as well as the fuzzy continuous linear operator in a generalized fnls and try to prove them.
Definition 14.
Let be a family of functions.
- (i)
- is said to be uniformly fuzzy convergent to a function f on a subset A of X if for eachi.e., for each and for each such that:
- (ii)
- is said to be pointwise fuzzy convergent to a function f on a subset A of X if for each for each such that:
From the definition, it is obvious that implies , but does not imply We verify this by the following example.
Example 1.
Let us consider a real nls (normed linear space) where is the set of all real numbers and Define two functions as follows:
Define by Now, if we consider , then is pointwise fuzzy convergent, but not uniformly fuzzy convergent.
Lemma 4.
Let f be self-mapping defined on a fuzzy Banach space and f also be a fuzzy compact linear operator on a subset M of Then, there exists a sequence of continuous mappings such that:
- (i)
- is uniformly fuzzy convergent to
- (ii)
- generates a finite-dimensional subspace of
Proof.
Since f is a fuzzy compact linear operator, thus the set is a fuzzy compact set, i.e., is a compact set w.r.t. Now, by Theorem 6, is fuzzy totally bounded. Let and be a strictly decreasing sequence that tends to Then, for each , we can find a finite No. of elements such that:
We now define on for each by:
Since the family is a continuous function on X for each and f is continuous on M by Note 3, so is continuous on Thus, each is a continuous function on Now,
Now, define by Thus, by Inequality (1),
Thus,
Since is arbitrary, then the above relation is true for each Thus, uniformly fuzzy converges to Condition is automatically valid by the construction of □
Remark 1.
In Lemma 4, each contains a fixed point, say This can be shown in the following way:
Now, the sequence , which is uniformly fuzzy convergent to f, is of the form:
Now, if we choose (convex closure of ), , then is a closed, bounded, convex subset of the finite-dimensional subspace of X and (by the definition of ). Each is continuous. Now, by the Brouwer fixed point theorem, ∃ a point such that
Remark 2.
If is uniformly fuzzy convergent to f on X, then for each
Proof.
Since is uniformly fuzzy convergent to f, then pointwise fuzzy converges to Thus:
Now, from Lemma 1, the required result follows immediately. □
Lemma 5.
Let be a sequence of fuzzy compact linear operators defined on where is an fnls. Again, is uniformly fuzzy convergent on Then, the set is a fuzzy compact set, i.e., compact w.r.t. the topology
Proof.
We show that is fuzzy totally bounded. Then, by Theorem 8, the assertion of the lemma is automatically valid. Let be an arbitrary No. and be given. Then, by the left-continuity of ∗ at such that:
Since uniformly fuzzy converges to T, then such that:
Again, the sets are fuzzy compact sets, i.e., compact w.r.t by the definition of the fuzzy compact linear operator. Therefore, is compact w.r.t. By Theorem 6, is fuzzy totally bounded. Now, by the definition of the fuzzy total boundedness, we can find such that:
Now, for any if , we have:
If , then:
Thus, is fuzzy totally bounded. This completes the proof. □
Lemma 6.
Let T be a continuous self-mapping on and dim Then, T is a fuzzy compact linear operator.
Proof.
Let be a fuzzy bounded sequence. Then, by Theorem 7, is a fuzzy bounded sequence. Again, the range set of say is fuzzy bounded. Now, by Lemma 2, is fuzzy bounded. Since is finite-dimensional, thus is fuzzy compact. Therefore, has a fuzzy convergent subsequence. Thus, T is a fuzzy compact linear operator by Theorem 3. □
Lemma 7.
Let be an fnls. For each such that:
Proof.
Suppose Then, also belongs to By the left-continuity of at such that:
Let Thus, where Now:
This completes the proof. □
Theorem 10.
(Schauder-type fixed point theorem) Let be an fnls, C be a bounded, closed, convex subset in X w.r.t. , and be a fuzzy compact linear operator. Then, there exists a point such that
Proof.
Since f is a fuzzy compact linear operator, then by Lemma 4 and Remark 1, there exists a sequence of continuous mappings , which is uniformly fuzzy convergent to f, and each contains a fixed point, say , i.e.,
Since each , then by Lemma 5, has a fuzzy convergent subsequence, say , i.e., Now, for any with we have:
Since uniformly fuzzy converges to f, then by Remark 2, for
Again, each is continuous, so ,
Taking in both sides of Inequality 6, we get,
This completes the proof. □
Theorem 11.
Let be an fnls. Let C be a convex, compact subset of X and f be a continuous operator from C into Then, there exists such that
Proof.
Since C is compact w.r.t. , thus by Theorem 6, C is fuzzy totally bounded. Now, consider a strictly decreasing sequence with then such that,
Now, define a family of functions such that:
where
Let and
Since so such that Now:
Since is arbitrary, thus uniformly fuzzy converges to Again, is a family of continuous functions from to itself. For each maps from C to the closed convex hull of Since C is convex, then We constrict the restricted mapping and it turns out that it maps the compact, convex subset of a finite-dimensional set of the span of into itself. Thus, by the Browder fixed point theorem, such that Since C is compact w.r.t. has a convergent subsequence, say w.r.t. fuzzy norm N and Now, consider
Taking on both sides, we get Again, is arbitrary.
□
Theorem 12.
Let be a fuzzy Banach space, C be a closed and convex subset of X, and be a continuous mapping such that the image of C is contained ina compact set. Then, such that
Proof.
Let Consider (where is the convex combination of the element of ). It is clear that K is a convex subset of We show that K is compact w.r.t. We have a compact subset of X w.r.t. Therefore, B is fuzzy totally bounded.
Let Then, such that Again, since such that:
Let Thus, x is of the form where Again, each , Therefore, for each for some such that:
Here:
where Since each fnls is a topological vector space:
Thus:
Here, is a closed bounded subset of Therefore, is compact w.r.t. Thus, such that:
Thus, we get that is totally bounded and complete, i.e., compact w.r.t. Again, By theorem 11, such that
4. Darbo’s Generalization of the Schauder-Type Fixed Point Theorem Using the Concept of the Measure of Non-Compactness
In this section, we first consider two types of fuzzy bounded subsets of a KM-type fuzzy metric space (i.e., M is a left-continuous function w.r.t. t, and ∗ is left-continuous at ). We renamed them as strongly and weakly and studied the relation between them. After that, the measure of the non-compactness of a strongly fuzzy bounded subset of the fuzzy metric space is defined. Using this concept, a family of -set contraction mapping is specified, and Darbo’s generalization of the Schauder-type fixed point theorem is established for these types of contraction mappings.
Theorem 15.
(Strongly fuzzy boundedness) Let be a fuzzy metric space. A subset Q of X is said to be strongly fuzzy bounded if such that for each :
i.e., fuzzy diameter of Q () less than ∞ where
(defined by Bag and Samanta in the paper [28].)
An example is presented to understand the strongly fuzzy boundedness more clearly.
Example 2.
Let (the set of all ordered pairs of the elements of the set of all real numbers) and where are two norms on Clearly, Define a function by:
Then, M is a fuzzy metric on X w.r.t. the min t-norm. Clearly,
Consider Now:
∴A is strongly fuzzy bounded.
The fuzzy boundedness defined in Definition 4 is renamed as the weakly fuzzy bounded subset of a fuzzy metric space From the two definitions, it is clear that strongly fuzzy bounded implies the weakly fuzzy boundedness, but the converse may not be. This can be justified by the following example.
Example 3.
Consider the fuzzy metric:
Now, Let Since so A is weakly fuzzy bounded. However, Thus, A is not strongly fuzzy bounded.
The weakly fuzzy bounded subset of a fuzzy metric space can also be defined as if , then A is weakly fuzzy bounded where The equivalence between these two definitions was already proved in the paper [29].
Definition 16.
(Kuratowski’s measure of non-compactness) Let be a fuzzy metric space and Q be a strongly fuzzy bounded subset of Then, Kuratowski’s measure of the non-compactness of Q denoted by is defined as:
From the definition, it is clear that for each strongly fuzzy bounded subset Q of
Definition 17.
(α-level Kuratowski measure of non-compactness) Let be a fuzzy metric space and Q be a weakly fuzzy bounded subset (or strongly fuzzy bounded subset) of Then, for each , the α-level Kuratowski measure of the non-compactness of Q denoted by is defined as:
where defined by Bag and Samanta [28].
From the definition of and it is clear that if Q is a strongly fuzzy bounded subset, then , i.e.,
Lemma 8.
Let be strong fuzzy bounded subsets of a complete fuzzy metric space Then:
- (i)
- is compact w.r.t.
- (ii)
- (iii)
- (iv)
Again, if is an fnls, then the followings properties also hold.
- (v)
- (vi)
- (vii)
- (viii)
Proof.
(i) First, we suppose that Then, for each with such that Now, if Q is totally bounded, then is also, and we get the required result. Let and Consider a fixed for each Then, it is clear that
Thus, Q is totally bounded. Conversely, suppose that is compact w.r.t. Then, Q is totally bounded. Let be given. Then, for any , and for, such that Consider:
Then, where for each Since is arbitrary, thus
(ii) We first prove that Then, the required result follows immediately. Obviously, For the reverse part, let Then, and in Q such that:
Here:
Thus, we arrive at the required conclusion.
(iii) For the set
(iv) From (iii), follows. The reverse part is similar to a crisp set. For the references, please see [30].
For (v), (vi), (vii), and (viii), we first prove that in an fnls, the following properties hold.
- (1)
- (2)
- (3)
- (4)
Then rest of the proof of (v), (vi), (vii), and (viii) is similar to the classical version of this theorem.
(1) Now:
(2) Again:
(3)
(4) is obvious as We only show that for a fixed and for a fixed
Since and are arbitrary, thus
Consider Thus,
∴ we arrive at the required conclusion. □
Definition 18.
(Axiomatic approach) Let be a complete fuzzy metric space and the family of strongly fuzzy bounded subsets of A map is called a measure of non-compactness if it satisfies the following properties:
- (1)
- is fuzzy totally bounded,
- (2)
- (3)
Using this axiomatic approach, we give some examples of the measure of the non-compactness in a fuzzy metric space.
Example 4.
Let (the set of all ordered pairs of the elements of the set of all real numbers) and where are two norms on Clearly, Define a function by:
Then, M is a fuzzy metric on X w.r.t. the min t-norm. Clearly,
Define functions and from the set of all strongly fuzzy bounded subsets of X to by:
and
Both and satisfy all the conditions of Definition 18. Therefore, both are the measure of the non-compactness of fuzzy metric space
Theorem 13.
Let be a complete fuzzy metric space. If is a decreasing sequence of non-empty closed, strongly fuzzy bounded subsets of X such that then the intersection is a non-empty compact subset of X w.r.t.
Proof.
Here, Thus, by Lemma 8, is compact w.r.t. as is closed. Now, we will show that is non-empty. Since so Let and i.e., , and so on. Consider Thus,
By Definition 17, for every such that Since for some , so Consider a subsequence of with for some Thus,
Similarly, we get a subsequence of of with i.e., This is true for any
Thus,
For any and such that:
is a Cauchy sequence w.r.t. i.e., converges to i.e. Thus, is non-empty. □
Definition 19.
Let be a complete fuzzy metric space and be a fuzzy continuous mapping. Then, f is called a ψ-set contraction if there exists such that for all strongly fuzzy bounded subsets C of the following relation holds, where ψ is the measure of the noncompactness of
This definition is inspired by the -set contraction in the classical set theory. For the references, please see the book [9].
Theorem 14.
(Darbo’s generalization of the Schauder-type fixed point theorem) Let be a fuzzy Banach space and C be a closed, strongly fuzzy bounded, and convex subset of If is a ψ-set contraction, then f has a fixed point in
Proof.
For each consider Clearly, Now, which is a closed and convex set, and Again,
Furthermore, By Theorem 13, is compact and non-empty. Thus, is a continuous mapping from a compact, convex set to itself. Thus, by Theorem 11, such that This completes the proof. □
Example 5.
Let (the set of all continuous functions over [0,1]) and be two norms on Clearly,
Define a function by:
Then, is fuzzy Banach space. Clearly,
Define a function with and where C is a strongly fuzzy bounded subset of Clearly,
∴f is a ψ-set contraction mapping. By Theorem 14, f has a fixed point in
Remark 3.
In Example 5, It is a closed, convex, bounded subset in where However, is not a Banach space. Therefore, the classical version of Darbo’s generalization of the Schauder-type fixed point theorem will not be able to give the existence result of a fixed point of which is defined in Example 5. In this scene, our theorem is more general than its classical form.
5. Conclusions
Schauder’s fixed point theorem and its generalizations play a pivotal role in this context of nonlinear functional analysis. The aim of this paper is to study different types of Schauder’s fixed point theorems in the context of fuzzy settings. For this reason, two types of fuzzy convergence are defined for a sequence of linear operators whose domain and range space are the fnlss. Moreover, the notion of two types of fuzzy bounded subsets of a fuzzy metric space is formulated, and the relation between them is studied. Further, the concept of Kuratowski’s measure of non-compactness in a fuzzy metric and an fnls are introduced for both fuzzy bounded subsets. This concept is used as a tool to prove Darbo’s generalization of the Schauder-type fixed point theorem. This is the first instance of studying the measure of the non-compactness in fuzzy settings. There is a huge scope of further research in this area, and many fixed point theorems can be developed by using these types of measures of non-compactness. Schauder’s fixed point theorem has various applications in the theory of differential equations such as Peano’s existence theorem for the first-order differential equations, the existence of the positive solution to the second-order singular differential equations, the existence of periodic orbits of rapidly symmetric systems, and so on. The theorems developed in this manuscript will promote future studies on the fuzzified area of the above-mentioned differential equations, as well as in the fuzzy neural networks.
Author Contributions
Conceptualization, S.C. and J.-G.L.; funding acquisition, J.-G.L.; writing, original draft, S.C.; Writing, review and editing, T.B. and J.-G.L. All authors have read and agreed to the published version of the manuscript.
Funding
This research is supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1D1A1B07049321).
Acknowledgments
The authors are grateful to the reviewers for their valuable suggestions and comments in rewriting the article in the present form. The authors are also thankful to the Editor-in-Chief of the journal for his valuable comments.
Conflicts of Interest
The authors declare no conflict of interest.
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