Abstract
The main objective of this paper is to deal with some properties of interest in two types of fuzzy ordered proximal contractions of cyclic self-mappings integrated in a pair of mappings. In particular, is a non-contractive fuzzy self-mapping, in the framework of non-Archimedean ordered fuzzy complete metric spaces and is a -cyclic proximal contraction. Two types of such contractions (so called of type I and of type II) are dealt with. In particular, the existence, uniqueness and limit properties for sequences to optimal fuzzy best proximity coincidence points are investigated for such pairs of mappings.
1. Introduction
Concepts and related results on fuzzy sets in several research disciplines are abundant in the background literature. From a mathematical context, studies are available, for instance, in [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18] and the references therein, following its introduction and characterization by Zadeh [4]. Among the research performed on the subject, effort has been devoted to the investigation of the existence and uniqueness of fixed points, best proximity points, fuzzy fixed points, fuzzy best proximity points, common fuzzy fixed points and optimal fuzzy coincidence points [15,16,17,18,19,20,21,22,23,24,25,26,27,28]. Also, research has been devoted to related properties of convergence of sequences to the abovementioned relevant points. Fixed Point Theory is also relevant to the stability properties of some iterative schemes of that of dynamic systems [29,30,31,32,33], as an alternative tool to other classical techniques like Lyapunov stability. (See, for instance, [33,34,35,36,37].) There are also abundant studies on all such topics in classical metric spaces and Banach spaces, either in the fuzzy formalism or not necessarily under the fuzzy formalism, including a lot of research on contractive and non-expansive mappings, self-mappings and, in particular, cyclic proximal mappings. (See, for instance, [26,27,28,29,38,39,40,41,42,43] and the references therein concerning different iterative schemes and their relations to proximal split feasibility, variational inequalities and fixed point problems. There are also recent studies on the generalizations of several types of contractions in [31] with an introduction of the so-called simulation function.
Recent work in fuzzy metric spaces and probabilistic metric spaces can be found in [22,23,24,25]. Also, the so-called simulation function is introduced and discussed in [31] related to a new special generalized contraction that generalizes the Banach contraction and unifies several previously known types of contractions.
There are certain real-life problems for which fixed points, best proximity points, optimal coincidence points or optimal best proximity coincidence points do not exist, so their approximate counterparts are looked for in order to have an approximate solution of the problem at hand. We recall the following basic concepts:
If is a metric space, are non-empty then:
- (1)
- is a fixed point of if ;
- (2)
- is an approximate fixed point of if ;
- (3)
- is a best proximity point of in if ;
- (4)
- is an approximate best proximity point of in if ;Note that a fixed point of is an approximate fixed point of while the converse is not true, in general. Also, a best proximity point of , which is also a fixed point if and intersect, is an approximate best proximity point of while the converse is not true, in general. If we have two mappings and then:
- (5)
- is an optimal best proximity coincidence point of the pair if ;
- (6)
- is an approximate optimal best proximity coincidence point of the pair if .
Note that optimal best proximity coincidence points are also approximate optimal best proximity coincidence points but the converse is not true, in general. Note also that, if and intersect, then an optimal best proximity coincidence point of the pair is also a coincidence point of . The above concepts can be extended to the “fuzzy” framework formalism when dealing with fuzzy metric spaces. The purpose of this paper is to investigate some relevant properties of two types of fuzzy ordered proximal contractions of cyclic self-mappings integrated in a pair of mappings, where is a non-contractive fuzzy self-mapping and is a cyclic proximal contraction, in the framework of non-Archimedean ordered fuzzy complete metric spaces. In particular, the existence, uniqueness and limit properties for sequences of optimal fuzzy best proximity coincidence points are investigated for such pairs of mappings.
Notation
- is the set of real numbers, , ;
- is the set of integer numbers, , ;
- ;
- is the closure of the -set.
The subsequent equality holds for the t-norm for a fuzzy set on :
Some useful technical definitions to be used are given below:
Definition 1 [1].
A binary operation is said to be a continuous t-norm if:
- (i)
- is continuous, commutative and associative;
- (ii)
- for all ;
- (iii)
- if and .
The formalism of fuzzy sets was proposed by Zadeh [4]. The following formal definition of fuzzy sets on non-Archimedean fuzzy metric spaces will be used throughout this manuscript.
Definition 2 [2,3].
Let be a non-empty set and be a continuous t- norm. A fuzzy set on is said to be a fuzzy metric on the non-Archimedean fuzzy metric space if for any , the following conditions hold:
- (i)
- (ii)
- (iii)
- (iv)
- ; ;
- (v)
- is left-continuous.
If the condition (iv) of Definition 2 is replaced with ; then is a (Archimedean) fuzzy metric space and is non-decreasing on and continuous on [5]. If then ; and is said to be the strong metric on . Each fuzzy metric on generates a Hausdorff topology whose base is the family of open balls of members for , , and a sequence converges to with respect to if and only if ; . Note that, since (iv) implies the above condition, any non-Archimedean fuzzy metric space is a fuzzy metric space.
Definition 3 [13].
Let and be two non-empty subsets of a non-Archimedean fuzzy metric space . Define the sets and as:
Definition 4 [39].
Let be the set of all mappings satisfying the following properties:
- (i)
- , and for and it is continuous in ,
- (ii)
- if and only if .
A point in an abstract non-empty set will be said to be an optimal fuzzy best proximity coincidence point of the pair of mappings , where and , where and are non-empty subsets of , if , where is a non-empty set and is a fuzzy metric. The main paper body consists of other two sections. In such sections, some proximal contractions associated with pair where is a non-contractive self-mapping and is a -cyclic fuzzy ordered proximal contractive self-mapping are formalized and some of their propertied, like convergence of sequences and existence and uniqueness of optimal fuzzy best proximity coincidence points are investigated. The obtained results and their discussion are split into two sections as follows. Section 2 introduces some necessary concepts in the fuzzy framework while some results are obtained and proved concerning the so-called optimal fuzzy best proximity coincidence points in partially ordered non-Archimedean fuzzy metric spaces for cyclic fuzzy order preserving proximal -contractions of type I. Section 3 reformulates the above results for another type of proximal contractions, so-called type II. Both sections contain and discuss some illustrative examples.
2. Results and Discussion on Optimal Fuzzy Best Proximity Coincidence Points in Non-Archimedean Fuzzy Metric Spaces for Cyclic Fuzzy Order Preserving Proximal -Contractions of Type I
This section is devoted to give a framework related to the existence of best proximity coincidence points in partially ordered non- Archimedean fuzzy metric spaces for cyclic fuzzy order preserving proximal -contractions of type I. A set of necessary definitions are given to set and prove the results and a set of “ad hoc” discussed examples is also given.
Definition 5.
Let be a non-empty subset of a non-Archimedean fuzzy metric space . A self-mapping on is said to be:
- (1)
- a fuzzy isometry if for all and ;
- (2)
- fuzzy non-contractive if for any and , we have .
Definition 6.
Let be a preordered set and let be non-empty sets; . A -cyclic mapping is said to be non-decreasing, or order preserving with respect to a preorder relation on , if:
- (a)
- the binary preorder relation on is a partial order relation on each set ; ;
- (b)
- for any in and any if then .
Remark 1.
Note that Definition 6 could be restated under stronger conditions with the binary preorder relation holding on while being a partial order relation on each set ; . Note that ; and . In this context, Definition 6 can be applied to the partially order preserving non-Archimedean fuzzy metric space (i.e., is a partially order preserving set and is a non-Archimedean fuzzy metric space, [38]) to a -cyclic mapping where are non-empty sets; .
The concepts of order preserving, order reversing and monotone mappings have been discussed in [11], where related results have been obtained. An “ad hoc” adaptation of the concept of order preserving for cyclic mappings is proposed in the subsequent definitions:
Definition 7.
A -cyclic mapping is said to be a (strong) -cyclic fuzzy ordered proximal -contraction of type I if for any and any given , the following condition holds:
for all .
If the above conditions hold for any and any given then is said to be a weak -cyclic fuzzy ordered proximal -contraction of type I.
Definition 8.
A -cyclic mapping is said to be a (strong) -cyclic fuzzy ordered proximal -contraction of type II if for some , any and any given , the following condition holds:
where for all .
If the above conditions hold for any and any given then is said to be a weak -cyclic fuzzy ordered proximal-contraction of type II.
Definition 9.
A -cyclic mapping is said to be (strong) -cyclic proximal fuzzy order preserving if for any and any given then and the following condition holds:
If the above conditions hold for any and any given then is said to be a weak -cyclic proximal fuzzy order preserving mapping.
Definition 10 [20].
A point in an abstract non-empty set is said to be an optimal fuzzy best proximity coincidence point of the pair of mappings , where is a self-mapping and is, in general, a non-self mapping, and are non-empty subsets of if .
Remark 2.
- (1)
- Note that Definition 10 is applicable to the case when the mapping is -cyclic (so that ; ) and ; ;
- (2)
- Strong proximal contractions might be simply referred to as proximal contractions when no confusion is expected. Note from Definitions 8–10 that proximal contractions of types I and II are also weak proximal contractions of types I and II, respectively.
A quadruple is called a partially ordered non-Archimedean fuzzy metric space if is a partially ordered set and is a non-Archimedean fuzzy metric space. The following main result of this section holds:
Theorem 1.
Let be a complete partially ordered non-Archimedean fuzzy metric space and let be non-empty sets; with being a partial order defined on . Let a -cyclic mapping be continuous and weak -cyclic fuzzy order preserving (with respect to ) proximal -contraction of type I and let be surjective, fuzzy non-contractive and inverse monotone mapping such that, for any , and are comparable with respect to only if are comparable. Suppose also that each pair of elements of has a lower bound and an upper bound and that for any , is non-empty, and ; . If for each given for each , there exists some element in such that:
then there exists a unique element for each that is an optimal fuzzy best proximity coincidence point of the pair in such that ; , and then:
Furthermore, each of the subsequences for each for , with , being defined by any given first element so that the proximal constraint:
holds for any given , , is a Cauchy sequence that is convergent to the optimal fuzzy best proximity coincidence point (the closure of ) of the pair in provided that the two subsequent conditions hold:
- (1)
- , with , for , and , with ; , ;
- (2)
- the chosen arbitrary is such that the initial points and that the sets of positive integers for and have positive upper-bounding integers ; , with and .
Proof.
Denote the restricted mappings and ; of the functions and , respectively, by and ; . Let arbitrary in for the given and some for any given arbitrary be such that and . Since and , exists such that . Since is weak -cyclic proximal fuzzy order preserving and then and, since is surjective and then it follows that. Assume that this is not the case and proceed by contradiction. Since and are comparable, which holds, by hypothesis, only if and are comparable, then since is assumed false. However, then , which contradicts . Then, and, as a result, . Proceeding in the same way, we can build a sequence with for , where , such that ; ; . Then, take such that since is a weak -cyclic proximal fuzzy order preserving, and . As a result, ; . Again, for such a , there is some such that and for . Then, the elements of from to are ordered, with the order preserved with respect to the preorder relation and and for . By keeping , we proceed in the same way by running from to and prove that the finite subsequence of from to is also totally ordered with respect to since for ; for the given . Now, the same reasoning is used for and for and to conclude that the elements of from to are ordered with respect to the relation . Proceeding recursively for each and each integer , it is proved that, for for ; and for ; and that the sequence is totally ordered with respect to . Define the strictly ordered set of positive integers ; , with and ; , . Since is a weak -cyclic proximal fuzzy order preserving (with respect to ) proximal -contraction of type I and is fuzzy non-contractive, one has for since is in the set :
:
. Note that if and are in then and are in , for , if and in since, by hypothesis, , with , for and , with ; . As a result, there is a subsequence of non-negative integer numbers that depends on the initial , such that and are in for all and each .
Also, for the subsequence for ; and any given , and are strictly increasing sequences with for each given, so that as for , and convergent to a limit in for each and since is continuous and non-decreasing and Equations (4) and (5) hold with:
For each . Assume that there is such that for some . Then, the subsequent contradiction follows:
for each . Thus, for all and all . It is now proven that the subsequences are Cauchy sequences in for each given . Suppose that there is a sequence that is not Cauchy for some . Then, there exists and such that for all , there are such that ; for some . Assume that is the least integer exceeding and satisfying the above inequality so that:
Then, one obtains for all :
and, since for all is a continuous -norm and , one gets by taking the limits in Equation (10) as the following contradiction:
As a result, is a Cauchy sequence for all . Since is complete, there exists such that ; since as and ; , . Since is continuous, this also implies that:
so that is the common best proximity point of the pair in for each . It is now proven that is unique for each . This is equivalent to proving that, for any fixed element , the subsequence of converges to the same ; . Since is a weak -cyclic fuzzy order preserving proximal -contraction of type I and is fuzzy non-contractive, one gets the subsequent contradiction under the assumption that for some such that, if and and are comparable, the convergent subsequences , , such that the sequences of nonnegative integers and with as ; , defined by:
satisfy the set of inequalities:
so that ; . Now, assume that the corresponding elements of the sequences and , with distinct initial values and , are not all pair-wise comparable. By the hypothesis of the mapping being a fuzzy order preserving proximal -contraction of type I and the hypothesis of the mapping being inverse monotone, both sequences are lower-bounded and upper-bounded by sequences and , with the corresponding subsequences and , respectively, in any of the sets , which are constructed from:
provided that ; and have order comparison properties of the form and ; , since the sequences and ; , are totally ordered, and also both lower-bounded and upper-bounded by the pair-wise comparable sequences and , respectively, since they are convergent. Then, ; .
It is now proved that ; . Since , then:
where is a Cauchy sequence of initial value that is convergent to some , while another subsequence in of a sequence with initial consecutive values , converges to . However, since is unique and for all , then:
since is a unique limit of Cauchy sequences in then ; . So the unique limit of all Cauchy subsequences in is ; . ☐
Remark 3.
Theorem 1 guarantees the existence of Cauchy sequences that are constructed from the proximal constraints and their convergence to unique optimal fuzzy best proximity coincidence points of the pair in , which are located at ; provided that the proximal constraints run at least for two consecutive iterations at each before each iteration to the next adjacent subset (see conditions 1–2). In the subsequent result, the constraints for running at least two consecutive proximal iterations at each ; are removed. Only a proximal iteration at is needed for some given at particular cycles of the -cyclic map . This operation guarantees the convergence of the corresponding subsequences in ; to unique optimal fuzzy best proximity coincidence points of the pair at each set ; .
Corollary 1.
Assume that the hypothesis of Theorem 1 holds except that, for any given initial point , the sequences are built so that:
- (1)
- for any if for any and some fixed (i.e., the proximal subsequence from each subset of to each next adjacent subset is only computed eventually at the subset , while at the remaining subsets only the cyclic self-mapping is involved);
- (2)
- the proximal constraint Equation (3), subject to its subsequent constraints, is replaced at the subset of by the subsequent one:for some given and some subsequence , for with for some satisfying with , for some set of bounded positive integers ; for the given and some sequence of positive integers being strictly increasing with (i.e., the proximal subsequence at the subset is not necessary computed at each -th cycle on the whole cyclic disposal of the subsets for all since can exceed the value for some values .
Then, there exists a unique element for each , which is an optimal fuzzy best proximity coincidence point of the pair in , such that ; , and then ; . Furthermore, each of the subsequences for being defined by any given first element , so that the proximal constraint ; , is a Cauchy sequence which is convergent to the optimal fuzzy best proximity coincidence point of the pair in .
Sketch of Proof.
Note that the proximal constraint (16) may be rewritten as:
by defining . Thus, we can define a strictly increasing sequence of nonnegative integers satisfying:
such that the nonnegative integers for all and , , with such that . Then, the subsequence and satisfies the proximal condition (16). Then, according to Theorem 1, such a subsequence is Cauchy and convergent to a unique , which is a unique optimal fuzzy best proximity coincidence points of the pair in . Since this sequence is convergent, all subsequences ; and is the unique limit point and also the unique optimal fuzzy best proximity coincidence point of the pair in . ☐
Theorem 1 and Corollary 1 also hold if is a -cyclic fuzzy order preserving (strong) proximal -contraction of type I such that the convergence of the constructed subsequences in each for converge asymptotically to be proximal subsequences converging to a unique optimal fuzzy best proximity coincidence point of in each so that as . In particular, Equation (1) is replaced with Equation (17) below. A related result is as follows:
Corollary 2.
Theorem 1 and Corollary 1 also hold “mutatis–mutandis” if is a continuous -cyclic fuzzy order preserving (with respect to defined on ) proximal -contraction of type I provided that for each given for each and some existing element in :
Sketch of Proof.
Now take some arbitrary in and any arbitrary given and some for any given arbitrary such that (17) holds (note that equality in Equation (17) holds if and only if ). Since is a -cyclic fuzzy order preserving proximal -contraction of type I and is fuzzy non-contractive, one has for any built subsequence of the whole iteration, since is in the set , and following Equations (4), (5) and (17):
if , and:
if . One can conclude from the steps of the proof of Theorem 1 and from the sketch of the proof of Corollary 1 that as so that the subsequence converges to a best proximity point in , which is a unique optimal fuzzy best proximity coincidence point of in . ☐
Example 1.
Let be defined by , where and . Note that . Consider the complete ordered fuzzy metric space under ; , and , where for any , and “ ” is a coordinate-wise ordering for all for defined by:
- (a)
- if and only if ; and
- (b)
- for any , i.e., if , for .
The proximal subsets are , .
Define the continuous—cyclic mapping and for some given real constant . Note that and ; . If then and .
Define as and for any given and some given real . Note that , and that is surjective and inverse monotone.
Now, we build a sequence by taking an initial point for some real for some given fixed real . Now, for some given real . Take . Next, take some such that and (i.e.,), for some given real . In general, , , , , with , so that for and:
Note that if and then and is strictly decreasing and . Thus, for all , one has , which converges to as , , and:
, , the last inequality being strict if , with while if and only if . Note that the sequence is strictly increasing for all and as , so that , , , and:
Note that this example extends the validity of Corollary 1—via Corollary 2—to the construction of sequences in the whole (instead of on just the proximal subset ), which converge to the unique proximal point limit to .
Example 2.
If, in Example 1, we take the initial points either in the proximal set or in the proximal set , i.e., , then, according to Corollary 1, and since and for .
Example 3.
Note that, in Example 1, we have taken the initial conditions in and the proximal sequences to are always constructed within and converge to the unique best proximity point of the proximal set to so that the best proximity point in is focused as a limit point via the cyclic mapping since . In Example 2, the points of the proximal built sequences are taken directly on both proximal sets. Now, we can construct converging proximal sequences with elements in both and that converge to the unique optimal fuzzy best proximity coincidence points of the pair in both corresponding proximal sets. Take a point . We now proceed by constructing a sequence with two consecutive elements in , then the next one is in and again two consecutive proximal elements to in and so on so that the cyclic mapping is also relevant to alternate elements with two or more elements of the sequences of interest in both subsets in the cyclic disposal. Thus, for instance, the sequence:
consists of two subsequences that converge to the best proximity points and for any given , which are the unique optimal fuzzy best proximity coincidence points of .
3. Results and Discussion of Optimal Fuzzy Best Proximity Coincidence Points in Partially Ordered Non-Archimedean Fuzzy Metric Spaces for Cyclic Fuzzy Order Proximal -Contractions of Type II
This section is devoted to a framework related to the existence of best proximity coincidence points in partially ordered non-Archimedean fuzzy metric spaces for cyclic fuzzy order preserving proximal -contractions of type II. Three definitions are given; we then state and prove the results and two examples are also given.
The following definitions are used in the main results of this section:
Definition 11 [8].
A sequence of positive real numbers is said to be -increasing if there exists such that for all .
Definition 12 [7,8].
A fuzzy metric space is said to have the property if for any -increasing sequence and any given real constant , there exists such that for all and all .
An alternative definition under weaker conditions follows:
Definition 13.
A fuzzy metric space is said to have the property if for any -increasing sequence and any given real constant , there exist some and some such that:
The following result relates the properties and if ; .
Lemma 1.
Let be a fuzzy metric space endowed with the product -norm such that its associate fuzzy metric fulfils ; . Then, the fuzzy metric space , endowed with a -norm has the properties and for any -norm .
Proof.
If for any -increasing sequence , one has:
and for any given real constant , there exists such that for any and since is a non-decreasing function on . Also, for any given real constants and , and some integer , where is in , one gets for the fuzzy metric space :
and ; so that possesses the property . Since; then ; . Thus, since has the property then for any -increasing sequence and any given real constant , there exists such that for all integer ; . As a result, has the property since:
If the metric space is , with being the triangular -norm, then one gets for any arbitrary that .
Since the triangular -norm exceeds any other -norm, all of which are strictly larger than the drastic -norm , one gets from the above results for any given and with , and some integer , where is in , that:
and has the property for any -norm . Also, for all integer ; , ; for any -norm so that has also the property .
Lemma 1 concludes that property is less restrictive than property and holds under a standard property in probabilistic spaces ; . The subsequent result is close to Theorem 1 for the case when is a weak -cyclic fuzzy order preserving proximal -contraction of type II. The main result of this section follows below:
Theorem 2.
Let be a complete partially ordered non-Archimedean fuzzy metric space satisfying the property and let be non-empty sets; with being a partial order defined on . Let a -cyclic mapping be continuous and weak -cyclic fuzzy order preserving (with respect to ) proximal -contraction of type II and let be surjective, fuzzy non-contractive and inverse monotone mapping such that, for any , and are comparable with respect to only if are comparable. Suppose also that each pair of elements of has a lower bound and an upper bound, and that for any , is non-empty, and ; . If for each given for each , there exist some element in such that:
Then, there exists a unique element for each , which is an optimal fuzzy best proximity coincidence point of the pair in such that ; , and then ; . Furthermore, each of the subsequences for each being defined by any given first element so that the proximal constraint:
holds for any given , , is a Cauchy sequence which is convergent to the optimal fuzzy best proximity coincidence point of the pair in provided that the two subsequent conditions hold:
- (1)
- , with , for , and , with ; , ;
- (2)
- the chosen arbitrary is such that the initial point and that the sets of positive integers for and have positive upper-bounding integers ; , with and .
Proof.
Denote the restricted mappings and ; of the functions and , respectively, by and; . Let arbitrary in and some for any given arbitrary be such that and . Since and , one gets that exists such that . Since is a weak -cyclic fuzzy order preserving proximal mapping and then and, since is surjective and then it follows that . Assume that this is not the case and proceed by contradiction. Since and are comparable which holds, by hypothesis, only if and are comparable then since is assumed false. However, contradicts . Then, and, as a result, . Proceeding in the same way, we can build a sequence with for , where, such that ; ; . Then, take such that since is a weak -cyclic fuzzy order preserving proximal mapping, and . As a result,; . Again, for such a , there is some such that and for . Then, the elements of from to are ordered, with order preserving, with respect to the preorder relation and and for . By keeping , we proceed in the same way by running from to and prove that the finite subsequence of from to is also ordered with respect to since for ; for the given . Now, the same reasoning is used for and for and to conclude that the elements of from to are ordered with respect to the relation . Proceeding recursively for each and each integer , it is proved that, for for ; and for ; and that the sequence is ordered with respect to . Define the strictly ordered set of positive integers; , with and ; , . Since is a weak -cyclic fuzzy order preserving (with respect to ) proximal -contraction of type II and is fuzzy non-contractive, one has for and some real constant , since belongs to the set :
if , , and:
if ; . Thus, one gets for any given , some , and all that:
from the property with ; being a -increasing sequence for such that implies that for all and all (note that as ). Any other -increasing sequence can be accommodated to satisfy . Thus, by the non-Archimedean property. Then, satisfies the property since Equation (24) holds for the -increasing sequence and it is extendable to any other -increasing sequence. Thus, one has from Equation (22) that:
for a subsequence being defined, provided that arbitrary points for some given arbitrary and such that ( being the set where the iteration switches from to ), . Thus, is Cauchy and convergent to some since is complete. For the given initial, we can always find two points , which are initial adjacent points of a subsequence for any arbitrary . It is found that is Cauchy and convergent to some . The set of limit best proximity points ; is unique since all the above subsequences are also totally ordered with lower-bounding and an upper-bounding ordered sequences (see Theorem 1 for similar reasoning), which converge to a unique best proximity point of a set to its adjacent set for each . Then, for any constructed sequence , we have convergent subsequences to the same limit within each subset , which is a unique best proximity point so that:
so that ; . It is now proven that each is an optimal fuzzy best proximity coincidence points of the pair in for each . One gets from the properties of the -norms, Equation (26), and the continuity of :
and:
However, we can interchange the locations of and in Equations (27) and (28) for obtaining corresponding sets of inequalities to conclude that:
Thus, is a unique best proximity point to in of and it is also an optimal fuzzy best proximity coincidence point of the pair in .
In the same way as Corollary 1 and under a close proof (see also Remark 3), we can get the subsequent Corollary to Theorem 2:
Corollary 3.
Assume that the hypothesis of Theorem 2 holds except that, for any given initial point , the sequences are built so that:
- (1)
- for any if for any and some fixed (i.e., the proximal subsequence from each subset of to each next adjacent subset is only computed eventually at the subset , while at the remaining subsets only the cyclic self-mapping is involved);
- (2)
- the proximal constraint Equation (3), subject to its subsequent constraints, is replaced at the subset of by the subsequent one:for some given and some subsequence , for with for some satisfying with , for some set of bounded positive integers ; for the given and some sequence of positive integers being strictly increasing with (i.e., the proximal subsequence at the subset is not necessary computed at each -th cycle on the whole cyclic disposal of the subsets for all since can exceed the value for some values ).
Then, there exists a unique element for each , which is an optimal fuzzy best proximity coincidence point of the pair in , such that ; , and then ; . Furthermore, each of the subsequences for being defined by any given first element , so that the proximal constraint ; , is a Cauchy sequence that is convergent to the optimal fuzzy best proximity coincidence point of the pair in . ☐
Results similar to those of Theorem 2 and Corollary 3 can be obtained by replacing the continuity assumption on by the condition that is fuzzy approximatively compact with respect to ; , that is, each sequence such that for some has a convergent subsequence.
Corollary 4.
Theorem 2 holds “mutatis-mutandis” if is fuzzy and approximatively compact with respect to ; even if is not everywhere continuous.
Proof.
The hypothesis of Theorem 2 still holds except that is not necessarily everywhere continuous while is fuzzy and approximately compact with respect to ; . Then, the first part of the proof of Theorem 2 is still applicable while one concludes from Equation (28) that , as so that there is a convergent subsequence for some for each since:
leads to:
and ; . Assume that this is not true, i.e., for some , so that:
Taking limits in both sides of the above inequality as , and since and , yields the contradiction , so that ; . Then, ; . ☐
Corollary 5.
Corollary 3 holds “mutatis-mutandis” if is fuzzy and approximately compact with respect to ; even if is not everywhere continuous.
Theorem 2 and Corollaries 3–5 can be directly extended to a pair where the -cyclic mapping is a continuous -cyclic fuzzy order preserving proximal -contraction of type II, the partial order being defined with respect to , which is now defined on the whole union of subsets of the cyclic disposal . This means that the constructed sequences possessing Cauchy subsequences within each subset converge to the best proximity points. Such points are simultaneously unique optimal fuzzy coincidence points of the pair that can be constructed on the whole subset but converge to the corresponding proximal subsets.
Remark 4.
Note from Definition 7 and from Definition 8 that if is a strong (respectively, weak) -cyclic fuzzy order preserving proximal -contraction of type II for some and is non-decreasing on then is also a strong (respectively, weak) -cyclic fuzzy order preserving proximal -contraction of type I. This becomes obvious from ; , , and, respectively, from ; , .
Example 4.
Assume that is a -cyclic fuzzy order preserving proximal -contraction with ; (respectively, ), , for some real where is a metric, then, , (respectively, ), with the above inequality being strict if and only if . Thus, for any if and only if for all . Then, is also a strong (respectively, weak) -cyclic fuzzy order preserving proximal -contraction of type I (see also Remark 4).
Example 5.
Consider the mappings and defined as in Examples 1–3. From Definition 8, Equations (22) and (23) in the proof of Theorem 2 and Example 4 with , it follows that for any sequence for constructed as in the proof of Theorem 2. Thus, it follows that the subsequences (or, respectively, in for for the weak proximal contraction case) for each converge to unique best proximity points, which are also the unique optimal fuzzy best proximity coincidence points of the pair of at each ; .
Remark 5.
Consider the mappings and under the conditions of Theorem 3. From Equations (22) and (23) in the proof of Theorem 2 and Example 4 with , it follows that , even if the constraint in Definition 8 holds for all and only for some , for any sequence constructed as in the proof of Theorem 2. Thus, it follows that the subsequences of fulfilling (or, respectively, in for the weak proximal contraction case); , converge to unique best proximity points at each , which are also the unique optimal fuzzy best proximity coincidence points of the pair at each ; . Thus, Theorem 2 can be weakened by “ad hoc weakening” the implied part of the inequalities in Definition 8 so as to be fulfilled only for some (and not for all) .
4. Conclusions
This paper has dealt with some properties of interest in two types of fuzzy ordered proximal contractions of cyclic self-mappings , which is integrated in a pair of mappings that construct the relevant proximal sequences of interest. In particular, is supposed to be a non-contractive fuzzy self-mapping in a non-Archimedean ordered fuzzy complete metric space , endowed with a partial order and a triangular norm , while is a -cyclic proximal contraction. The fuzzy set on is a fuzzy metric on the non-Archimedean fuzzy metric space . Two types of such contractions (so-called type I and of type II) are considered. The main results obtained rely on the existence, uniqueness and limit properties for sequences to existing optimal fuzzy best proximity coincidence points for such pairs of mappings.
Acknowledgments
The first author is grateful to the Spanish Government and European Fund of Regional Development FEDER for Grant Nos. DPI2012-30651 and DPI2015-64766-R. The authors are also grateful to the referees for their useful suggestions.
Author Contributions
All authors contributed equally to the writing of this paper. All authors read and approved the final manuscript.
Conflicts of Interest
The authors declare that they have no competing interests.
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