Existence of Coupled Best Proximity Points of p -Cyclic Contractions

: We generalize the notion of coupled ﬁxed (or best proximity) points for cyclic ordered pairs of maps to p -cyclic ordered pairs of maps. We ﬁnd sufﬁcient conditions for the existence and uniqueness of the coupled ﬁxed (or best proximity) points. We illustrate the results with an example that covers a wide class of maps.


Introduction
Banach's fixed point theorem has proven to be a powerful tool in pure and applied mathematics. Coupled fixed points were initiated in [1] more than 30 year ago. It turns out that the last 10 years there is a great interest on coupled fixed points, both in fundamental results and their applications [2][3][4][5]. We would like to mention a new kind of applications in the theory of equilibrium in duopoly markets [6,7].
A notion that generalizes fixed point results for non-self maps is that of cyclic maps [8] i.e., T : A → B, T : B → A. Since a cyclic map T does not necessarily have a fixed point, one can alter the problem x = Tx to a problem to find an element x which is in some sense closest to Tx. Best proximity points were introduced for cyclic maps in [9] (x is called a best proximity points of T in A if x − Tx = dist(A, B) = inf{ a − b : a ∈ A, b ∈ B}) and they are relevant in this perspective. The notion of best proximity points [9] actually generalizes the notion of cyclic maps from [8], as far as if A ∩ B = ∅, then any best proximity point is a fixed point, too. It turns out that best proximity points are interesting not only as a pure mathematical results, but also as a possibility for a new approach in solving of different types of problems [2][3][4][5][6][7].
We would like to mention just a few very recent results about coupled best proximity points, that can be applied in solving of different types of problems. The authors have investigated a generalization of GKT cyclic Φ-contraction mapping in [10] and a non trivial application for solving of initial value problem is presented. The existence of coupled best proximity point for a class of cyclic (or noncyclic) condensing operators are studied in [11] an the main result applied for finding of an optimal solution for a system of differential equations. A new class of mappings called fuzzy proximally compatible mappings are considered in [12], where coupled best proximity point results are obtained and further applied in finding the fuzzy distance between two subsets of a fuzzy metric space.
Unfortunately all of the mentions above results are for 2-cyclic maps. It is not easy to generalize the results about 2-cyclic maps to p-cyclic maps. The first breakthrough was obtained in [13], where authors succeed to show that for wide classes of maps the distances between the successive sets are equal. The technique from [13] was later widely used [14][15][16][17].
We have tried to unify the techniques from [1,13] to get results for the existence and uniqueness of coupled fixed (or best proximity points) for p-cyclic maps.
The first results related to finding the error estimate for best proximity points is made in [18]. In [19], results for the existence and uniqueness of coupled best proximity points are obtained, as well as an error estimate is obtained. In this article, p-cyclic operators are considered, and the results obtained include as a special case the results obtained in [13,19].

Preliminaries
We will summarize the notions and the results that we will need. If A and B are nonempty subsets of the metric space (X, d), then a distance between the sets A and B will be the number dist(A, be nonempty subsets of X. Just to simplify some of the formulas we will assume the convention that A kp+i = A i for i = 1, 2, . . . , p and k ∈ N. Following [13], if {A i } p i=1 be nonempty subsets of a metric space (X, d), then the map T : The next two lemmas are fundamental to the best proximity points theory.

Lemma 1. ([9]
) Let A be a nonempty closed, convex subset, and B be a nonempty closed subset of a uniformly convex Banach space (X, · ). Let {x n } ∞ n=1 and {z n } ∞ n=1 be two sequences in A and {y n } ∞ n=1 be a sequence in B so that: 1) lim n→∞ x n − y n = dist(A, B); 2) lim n→∞ z n − y n = dist(A, B); then lim n→∞ x n − z n = 0. Lemma 2. ( [9]) Let A be a nonempty closed, convex subset, and B be a nonempty closed subset of a uniformly convex Banach space (X, · ). Let {x n } ∞ n=1 and {z n } ∞ n=1 be sequences in A and {y n } ∞ n=1 be a sequence in B satisfying: (1) lim n→∞ z n − y n = dist(A, B); (2) for every ε > 0 there is a number N 0 ∈ N, such that for any m > n ≥ N 0 , x n − y n ≤ dist(A, B) + ε, then for every ε > 0, there is a number N 1 ∈ N, so that for all m > n > N 1 , holds the inequality The geometric structure of the underlying space X plays a key role. When we consider the Banach space (X, · ) we will always assume that the distance between the elements is generated by the norm · i.e., d(x, y) = x − y . Definition 1. [20] Let (X, · ) be a Banach space. For every ε ∈ (0, 2] we define the modulus of convexity of · by The norm is called uniformly convex if δ X (ε) > 0 for all ε ∈ (0, 2]. The space (X, · ) is then called a uniformly convex space.
For any uniformly convex Banach space X there holds the inequality [9] x + y for any x, y, z ∈ X, such that x − z ≤ R, y − z ≤ R and x − y ≥ r, provided that R, r be real numbers and R > 0, r ∈ [0, 2R]. For any uniformly convex Banach space (X, · ) its modulus of convexity δ X is strictly increasing function and thus its inverse function δ −1 exists. If there are constants C > 0 and q > 0, so that the inequality δ · (ε) ≥ Cε q holds for any ε ∈ (0, 2] we say that the modulus of convexity is of power type q with a constant C.
An extensive study of the Geometry of Banach spaces can be found in [21][22][23].

Auxiliary Results
The iterated sequence {(x n , y n )} ∞ n=0 (defined in ( [1] in the statement of Theorem 1 for coupled fixed points and in [24] in the statement of Lemma 3.8 for coupled best proximity points) will play a crucial role in the proofs of the results, as far as the ordered pair (x, y) of coupled fixed (or best proximity) points is obtained as its limit.
When we consider a sequence {(x n , y n )} ∞ n=0 we will always assume that it is the iterated sequence defined in Definition 2. Sometimes we will consider a subsequence {(x n k , y n k )} ∞ k=1 of {(x n , y n )} ∞ n=0 . The notion of a coupled best proximity point for cyclic maps was defined in [24] and the notion of best proximity point for p-cyclic maps was introduced in [13]. We will combine both definitions to define a coupled best proximity point for a p-cyclic maps. Definition 3. Let A i , i = 1, 2, . . . , p be nonempty subsets of a metric space (X, d) and T : Following [13] we will define a p-cyclic contractive condition for T : i=1 be nonempty subsets of a metric space (X, d). The map T is called p-cyclic contraction, if it satisfies the following condition: There exists α, β ≥ 0, α + β ∈ (0, 1), such that the inequality be nonempty subsets of a metric space (X, d) and T be a p-cyclic contraction map. Then dist(A i , A i+1 ) = dist(A i+1 , A i+2 ) for i = 1, 2, . . . , p.

Proof. Let us put
Let us suppose the contrary, that there are two indexes k, j ∈ {1, 2, . . . , p}, such that max i∈{1,2,...,p} Without loss of generality we may assume, that k = p. There exists s ∈ (0, 1], such that Let (x 0 , y 0 ) ∈ A p , then x pn+m , y pn+m ∈ A m , x pn , y pn ∈ A p , x pn+1 , y pn+1 ∈ A 1 and from (2) we get and Let us, for what follows, to use the notation γ = α + β. From (4) and (5) we can write the chain of inequalities and thus we get There exists N ∈ N, so that for any n ≥ N there holds the inequality where j and s are the index and the constant from (3), respectively. Therefore using the assumption that which is a contradiction and consequently the assumption that there exists j so that d j < max{d i : i = 1, 2, . . . , p} could not holds.
We have just proven in Lemma 3 that for maps, which satisfy Definition 4, there holds dist(A 1 , and thus we can denote in the rest of the article the distance between the consecutive sets by An easier to apply inequality, which is a consequence from (2) is the inequality be nonempty closed subsets of a metric space (X, d) and T be a pcyclic contraction. Then for every (x 0 , Consequently after taking a limit in (9) when n → ∞ we get lim n→∞ (d(x pn , x pn−1 ) + d(y pn , y pn−1 )) = 2d. From the inequalities d ≤ d(x pn , x pn−1 ) and d ≤ d(y pn , y pn−1 ) it follows that lim n→∞ d(x pn , x pn−1 ) = lim n→∞ d(y pn , y pn−1 ) = d.
The proofs of the other two (actually four, because of ±) limits can be done in a similar fashion.
Proof. By Lemma 4 we have that lim n→∞ x pn − x pn+1 = lim n→∞ x pn+p − x pn+1 = d. According to Lemma 3 it follows that lim n→∞ x pn − x pn+p = 0.
be nonempty closed subsets of a metric space (X, d) and T be a p-cyclic contraction.

For an arbitrary chosen
be nonempty closed subsets of a metric space (X, d) and T be a pcyclic contraction. If there exists a coupled best proximity point (z, v) of T in A i × A i , then (T n (z, v), T n (v, z)) is a coupled best proximity point of T in A i+n × A i+n . If (z, v) is a limit of the sequence {(x pn , y pn )} ∞ n=0 , then the ordered pair (z, v) is a p-periodic point of T, i.e., z = T pn (z, v) and v = T pn (v, z) for n ∈ N and any sequence {(ξ pn , η pn )} ∞ n=0 converges to (z, v).
Proof. Let (z, v) be any ordered pair, which is a coupled best proximity points of T in A i × A i . From the inequality it follows that (T(z, v), T(v, z)) is an ordered pair, which is a coupled best proximity points of T in A i+1 × A i+1 . From By induction we can prove that (T n (z, v), T n (v, z)) is a coupled best proximity points of T in A i+n × A i+n .
Therefore we have Let there exists (ξ, η) ∈ A i × A i , which is a coupled best proximity points of T in A i × A i , i.e., ξ − T(ξ, η) = η − T(η, ξ) = d, that is different from (z, v) and obtained as a limit of a sequence {(ξ pn , η pn )} ∞ n=0 . Using the continuity of the norm function, the equality T(z, v) = T p+1 (z, v), T(v, z) = T p+1 (v, z) we get the inequality and by the assumption γ ∈ (0, 1) we get the inequality
From (11) we get that there holds true Therefore {x n } ∞ n=1 is a Cauchy sequence in ∪ p i=1 A i . From the assumption that A i are closed subsets of the complete metric space (X, d) it follows that {x n } ∞ n=1 is convergent to some point z ∈ ∪ p i=1 A i . The sequence {x n } ∞ n=1 is an iterated sequence defined by the pcyclic map T and thus it has infinite number of terms that belong to each A i , i = 1, 2, . . . , p. Consequently z ∈ ∩ p i=1 A i . By literary the same arguments we get that lim n→∞ y n = v ∈ ∩ p i=1 A i . We will show that (z, v) is a coupled fixed point of T. Indeed from We will proof that (z, v) is a unique coupled fixed point by assuming the contrary. Let (x, y) be a coupled fixed point of T, different from (z, v). If x ∈ A i , then by the definition of a coupled fixed point it follows that y ∈ A i , too. From the assumption that T is a p-cyclic map it follows that (x, y) = (T(x, y), T(y, x)) ∈ A i+1 × A i+1 and therefore and the assumption that γ ∈ (0, 1) it follows that d(x, z) = d(y, v) = 0, i.e., the coupled fixed point (z, v) of T is unique.
After taking a limit in (12) we get Consequently there holds the a priori estimate y 0 )).

From the chain of inequalities
After taking a limit, when p → ∞, in the above inequality, we get 1 , y n )).
From the inequality we get the estimate the rate of convergence.
We will use the notations P n,m = x n − x m + y n − y m and W n,m = x n − x m + y n − y m − 2d, where {x n } ∞ n=0 and {y n } ∞ n=0 be the sequences from Definition 2, when the text field is too short.
We have proven in Lemma 3, that for any p-cyclic contraction the distances between the consecutive sets are equal. Therefore in the next theorem we will denote be nonempty, closed and convex subsets of a uniformly convex Banach space (X, · ). Let T : If d > 0 and (X, · ) be with a modulus of convexity of power type q with a constant C, then there hold the a priori error estimate and the a posteriori error estimate max{ x pn − z i , y pn − v i } ≤ P pn,pn−1 q W pn,pn−1 Cd where γ = α + β, α and β be the constants form Definition 4.

•
If d = 0, then there hold the error estimates of Theorem 1.
If p = 2, we get as a particular case the results from [19].
Proof. If dist(A i , A i+1 ) = 0 for some i, then by Lemma 3 it follows that dist(A i , A i+1 ) = 0 for all i. Then the contractive condition induced on T is equivalent to (10). Thus by Theorem 1, T has a unique coupled fixed point and the error estimates from Theorem 1 holds. Let us assume that d > 0. Let (x 0 , y 0 ) ∈ A i × A i . Then x np ∈ A i and x np+1 ∈ A i+1 for all n. By Lemma 4, lim n→∞ x np − x np+1 = d. If, for any arbitrary chosen ε > 0, there exists an n 0 ∈ N, such that for all m > n > n 0 the inequality to hold by the inequalities x pm − x pn+1 ≥ d and y pm − y pm+1 ≥ d it follows the inequality max{ x pm − x pn+1 , y pm − y pn+1 } ≤ d + ε holds for all m > n > n 0 . Then by Lemma 1, for any ε 1 > 0, there exists n 1 ∈ N, such that for m > n > n 1 the inequality max{ x mp − x np , y mp − y np } ≤ ε 1 holds, i.e., {x np } ∞ n=1 and {y np } ∞ n=1 are Cauchy sequences and thus converges to some (z, v) ∈ A i × A i . By Lemma 6 (z, v) will be a best proximity point of T in A i × A i .
Let us assume contrary of (13). Then, there exists an ε 0 > 0 such that, for every k ∈ N, there exists m k > n k ≥ k such that, Let m k be the smallest integer greater than n k , to satisfy the above inequality. Now By Lemma 4 we have lim k→∞ x pm k − x pm k +p = 0 and lim k→∞ y pm k − y pm k +p = 0. Therefore, using the choice of m k to be the smallest natural, so that to holds the inequality (14), we get i.e., lim k→∞ x pm k − x pn k +1 + lim k→∞ y pm k − y pn k +1 = 2d + ε 0 . From the inequality x pm k − x pm k +p + x pm k +p − x pn k +p+1 + x pn k +p+1 − x pn k +1 + y pm k − y pm k +p + y pm k +p − y pn k +p+1 + y pn k +p+1 − y pn k +1 .
From Lemma 7 it follows that (x, y), which is a limit of the iterated sequences is unique, for an arbitrary chosen initial guess, (T n (x, y), T n (y, x)) is a coupled best proximity point of T in A i+n × A i+n , (x, y) is a p-periodic point of T.
It has remained to prove that x = y. It holds Consequently x − T(y, x) = y − T(x, y) = d. From y − T(y, x) = x − T(x, y) = d and the uniform convexity of X it follows that x = y.
From (8) there holds the inequality Thus we get There hold the inequalities and After a substitution in (1) with x = x pn , y = x pn+p , z = x pn+1 , R = d + γ l ( x pn+1−l − x pn−l + y pn+1−l − y pn−l − 2d) and r = x pn+p − x pn and using the convexity of the set A we get the chain of inequalities where we have denoted W = d + γ l ( x pn+1−l − x pn−l + y pn+1−l − y pn−l − 2d). From (15) we obtain the inequality From the uniform convexity of X is follows that δ · is strictly increasing and therefore there exists its inverse function δ −1 · , which is strictly increasing too. From (16) we get By the inequality δ · (t) ≥ Ct q it follows that δ −1 · (t) ≤ t C 1/q .
From (17) and the inequalities we obtain There exists a unique pair (z, v) ∈ A i × A i , such that z − T(z, v) = d and z is a limit of the sequence {x pn } ∞ n=1 for any (x, y) ∈ A i × A i . After a substitution with l = pn and k = 0 in (18) we get the inequality ∞ ∑ n=1 x pn − x pn+p + y pn − y pn+p ≤ P 0,1 (x, y) q W 0,1 (x, y) Cd and consequently the series ∑ ∞ n=1 (x pn − x pn+p ) is absolutely convergent. Thus for any m ∈ N there holds z = x pm − ∑ ∞ n=m x pn − x pn+p and therefore we get the inequality The proof for v − y pm can be done in a similar fashion. After a substitution with l = 1 + 2i in (18) we obtain From (19) we get that there holds the inequality and after letting m → ∞ in (20) we obtain the inequality x pn − z ≤ P pn−1,pn (x, y) q W pn−1,pn (x, y) Cd The proof for y pn − v can be done in a similar fashion.
If we try to solve (21) with the use of some Computer Algebraic System, for example Maple, the software could not find the exact solution even for not too complicated functions (p = 2, ϕ(x) = x 1/2 , ψ(x) = x). If we try to solve it numerically, Maple finds that x = y = 1, but could not find that this is a solution for every λ, µ ∈ (0, 1) and presents two approximations of λ and µ.

Discussion
It is interesting whether same conclusions can be made for existence of coupled fixed (or best proximity) points p-cyclic Meir-Keeler maps [16], Reich Maps p-cyclic maps [25].
We were not able to prove a uniqueness of the coupled best proximity points, as like as [13,16]. We were able to prove just uniqueness of the best proximity points, if obtained by the sequence of successive iterations, which is not the case of 2-cyclic maps. It will be interesting if this gap can be filled.