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Best proximity point theorems for probabilistic proximal cyclic contraction with applications in nonlinear programming

Abstract

In this paper, we derive a best proximity point theorem for non-self-mappings satisfied proximal cyclic contraction in PM-spaces and this shows the existence of optimal approximate solutions of certain simultaneous fixed point equations in the event that there is no solution. As an application we consider a nonlinear programming problem. Our results extend and improve the recent results of (Sadiq Basha in Nonlinear Anal. 74(17):5844-5850, 2011).

1 Introduction

Best proximity point theorems are those results that provide sufficient conditions for the existence of a best proximity point and algorithms for finding best proximity points. It is interesting to note that best proximity point theorems generalized fixed point theorems in a natural fashion. Indeed, if the mapping under consideration is a self-mapping, a best proximity point becomes a fixed point.

One of the most interesting is the study of the extension of Banach contraction principle to the case of non-self-mappings. In fact, given nonempty closed subsets A and B of a complete PM-space \((X, F,*)\), a contraction non-self-mapping \(T : A \to B\) does not necessarily has a fixed point. Eventually, it is quite natural to find an element x such that \(F_{x,Tx}(t)\) is maximum for a given problem which implies that x and Tx are in close proximity to each other.

Many problems can be formulated as equations of the form \(Tx = x\), where T is a self-mapping in some suitable framework. Fixed point theory finds the existence of a solution to such generic equations and brings out the iterative algorithms to compute a solution to such equations.

However, in the case that T is non-self-mapping, the aforementioned equation does not necessarily have a solution. In such a case, it is worthy to determine an approximate solution x such that the error \(F_{x,Tx}(t)\) is maximum.

2 Preliminaries

Throughout this paper, the space of all probability distribution functions (briefly, d.f.’s) is denoted by \(\Delta^{+}\) = {\(F:{ \mathbf{R}}\cup\{-\infty,+\infty\}\rightarrow[0,1]: F\) is left-continuous and non-decreasing on R, \(F(0)=0\), and \(F(+\infty)=1\)} and the subset \(D^{+} \subseteq\Delta^{+}\) is the set \(D^{+}=\{F\in \Delta^{+}:l^{-}F(+\infty)=1\}\). Here \(l^{-} f(x)\) denotes the left limit of the function f at the point x, \(l^{-} f(x)=\lim_{t\to x^{-}}f(t)\). The space \(\Delta^{+}\) is partially ordered by the usual point-wise ordering of functions, i.e., \(F\leq G\) if and only if \(F(t)\leq G(t)\) for all t in R. The maximal element for \(\Delta^{+}\) in this order is the d.f. given by

$$\varepsilon_{0}(t) =\left \{ \textstyle\begin{array}{l@{\quad}l} 0, & t\leq0, \\ 1, & t>0 . \end{array}\displaystyle \right . $$

Definition 2.1

([1])

A mapping \(*:[0,1]\times[0,1]\rightarrow[0,1]\) is a continuous t-norm if ∗ satisfies the following conditions:

  1. (a)

    ∗ is commutative and associative;

  2. (b)

    ∗ is continuous;

  3. (c)

    \(a*1=a\) for all \(a\in[0,1]\);

  4. (d)

    \(a*b \leq c*d \) whenever \(a\leq c\) and \(b\leq d\), and \(a,b,c,d\in[0,1]\).

Two typical examples of a continuous t-norm are \(a*b =ab\) and \(a*b =\min(a,b)\).

A t-norm ∗ is said to be of Hadžić type if

$$ \forall\epsilon\in(0, 1)\ \exists \delta\in(0, 1)\mbox{:}\quad a >1-\delta \quad \Rightarrow\quad \overbrace{a*a * \cdots * a}^{n}> 1-\epsilon\quad (n\geq1) . $$

The t-norm minimum is a trivial example of a t-norm of Hadžić type, but there exists a t-norm of Hadžić type weaker than minimum (see [2]).

Definition 2.2

A probabilistic metric space (briefly, PM-space) is a triple \((X,F,*)\), where X is a nonempty set, ∗ is a continuous t-norm, and F is a mapping from \(X\times X\) into \(D^{+}\) such that, if \(F_{x,y}\) denotes the value of F at the pair \((x,y)\), the following conditions hold: for all \(x,y,z\) in X,

  1. (PM1)

    \(F_{x,y}(t)=\varepsilon_{0}(t)\) for all \(t>0\) if and only if \(x=y\);

  2. (PM2)

    \(F_{x,y}(t)=F_{y,x}(t)\);

  3. (PM3)

    \(F_{x,z}( t+s) \geq F_{x,y}(t)*F_{y,z}(s)\) for all \(x,y,z\in X\) and \(t,s\geq0\).

For more details and examples of these spaces see also [3–5].

Definition 2.3

Let \((X,F,*)\) be a PM-space.

  1. (1)

    A sequence \(\{x_{n}\}_{n}\) in X is said to be convergent to x in X if, for every \(\epsilon>0\) and \(\lambda>0\), there exists a positive integer N such that \(F_{x_{n},x}(\epsilon)>1-\lambda\) whenever \(n\geq N\).

  2. (2)

    A sequence \(\{x_{n}\}_{n}\) in X is called Cauchy sequence if, for every \(\epsilon>0\) and \(\lambda>0\), there exists a positive integer N such that \(F_{x_{n},x_{m}}(\epsilon)>1-\lambda\) whenever \(n, m\geq N\).

  3. (3)

    A PM-space \((X,F,*)\) is said to be complete if and only if every Cauchy sequence in X is convergent to a point in X.

Definition 2.4

Let \((X,F,*)\) be a PM-space. For each p in X and \(\lambda>0\), the strong λ-neighborhood of p is the set

$$ N_{p}(\lambda)=\bigl\{ q\in X:F_{p,q}(\lambda)>1-\lambda\bigr\} , $$

and the strong neighborhood system for X is the union \(\bigcup_{p\in V}\mathcal{N}_{p}\) where \(\mathcal{N}_{p}=\{N_{p}(\lambda): \lambda>0\}\).

The strong neighborhood system for X determines a Hausdorff topology for X.

Theorem 2.5

([1])

If \((X,F,*)\) is a PM-space and \(\{p_{n}\}\) and \(\{q_{n}\}\) are sequences such that \(p_{n}\to p\) and \(q_{n}\to q\), then \(\lim_{n\to\infty} F_{p_{n},q_{n}}(t)=F_{p,q}(t)\) for every continuity point t of \(F_{p,q}\).

Lemma 2.6

([2])

Let \((X,F,*)\) be a Menger PM-space with ∗ of Hadžić-type and \(\{x_{n}\}\) be a sequence in X such that, for some \(k\in(0,1)\),

$$ F_{x_{n},x_{n+1}}(kt)\geq F_{x_{n-1},x_{n}}(t)\quad ( n\geq1, t>0). $$

Then \(\{x_{n}\}\) is a Cauchy sequence.

Let A and B be two nonempty subsets of a PM-space and \(t>0\), the following notions and notations are used in the sequel.

  • \(F_{A, B}(t) :=\sup\{F_{x, y}(t) : x\in A, y\in B \}\),

  • \(A_{0} :=\{ x\in A : F_{x, y}(t) = F_{A, B}(t)\mbox{ for some }y\in B \}\),

  • \(B_{0}:=\{ y\in B : F_{x, y}(t) = F_{A, B}(t)\mbox{ for some } x\in A \}\).

Definition 2.7

Let \((X,F,*)\) be a PM-space. Given non-self-mappings \(S:A\rightarrow B\) and \(T:B\rightarrow A\), the pair \((S, T)\) is said to form a proximal cyclic contraction if there exists a non-negative number \(\alpha<1\) such that

$$ \left .\textstyle\begin{array}{l} F_{u, Sx}(t) = F_{A, B}(t), \\ F_{v, Ty}(t) = F_{A, B}(t) \end{array}\displaystyle \right \} \quad \Longrightarrow\quad F_{u, v}( t) \geq\min \biggl\{ F_{x, y} \biggl(\frac {t}{\alpha} \biggr),F_{A, B} (t ) \biggr\} $$

for all u, x in A and v, y in B and \(t>0\).

Note that, if S is a self-mapping that is a contraction, then the pair the pair \((S,S)\) forms a proximal cyclic contraction.

Definition 2.8

Let \((X,F,*)\) be a PM-space. A mapping \(S:A\rightarrow B\) is said to be a proximal contraction of the first kind if there exists a non-negative number \(\alpha<1\) such that

$$ \left .\textstyle\begin{array}{l} F_{u_{1}, Sx_{1}}(t) = F_{A, B}(t), \\ F_{u_{2}, Sx_{2}}(t) = F_{A, B}(t) \end{array}\displaystyle \right \}\quad \Longrightarrow\quad F_{u_{1}, u_{2}}(\alpha t) \geq F_{x_{1}, x_{2}}(t) $$

for all \(u_{1}\), \(u_{2}\), \(x_{1}\), \(x_{2}\) in A and \(t>0\).

Definition 2.9

Let \((X,F,*)\) be a PM-space. A mapping \(S:A\rightarrow B\) is said to be a proximal contraction of the second kind if there exists a non-negative number \(\alpha<1\) such that

$$ \left .\textstyle\begin{array}{l} F_{u_{1}, Sx_{1}}(t) = F_{A, B}(t), \\ F_{u_{2}, Sx_{2}}(t) = F_{A, B}(t) \end{array}\displaystyle \right \}\quad \Longrightarrow \quad F_{Su_{1}, Su_{2}}( \alpha t) \geq F_{Sx_{1}, Sx_{2}}(t) $$

for all \(u_{1}\), \(u_{2}\), \(x_{1}\), \(x_{2}\) in A and \(t>0\).

Definition 2.10

Let \((X,F,*)\) be a PM-space. Given a mapping \(S:A\rightarrow B\) and an isometry \(g:A\rightarrow A\), the mapping S is said to preserve isometric distance with respect to g if

$$F_{Sgx_{1}, Sgx_{2}}(t) = F_{Sx_{1}, Sx_{2}}(t) $$

for all \(x_{1}\) and \(x_{2}\) in A. and \(t>0\).

Definition 2.11

Let \((X,F,*)\) be a PM-space. An element x in A is said to be a best proximity point of the mapping \(S:A\rightarrow B\) if it satisfies the condition that

$$F_{x, Sx}(t) =F_{A, B}(t) $$

for all x in A and \(t>0\).

It can be observed that a best proximity reduces to a fixed point if the underlying mapping is a self-mapping.

Definition 2.12

Let \((X,F,*)\) be a PM-space. B is said to be approximatively compact with respect to A if every sequence \(\{y_{n}\}\) of B satisfying the condition that for all \(t>0\), \(F_{x, y_{n}}(t)\rightarrow F_{x, B}(t)\) for some x in A has a convergent subsequence.

It is easy to observe that every set is approximatively compact with respect to itself, and that every compact set is approximatively compact. Moreover, \(A_{0}\) and \(B_{0}\) are non-void if A is compact and B is approximatively compact with respect to A.

3 Proximal contractions

The following main result is a generalized best proximity point theorem for non-self proximal contractions of the first kind. Our results extend and improve some results of [6].

Theorem 3.1

Let A and B be non-void closed subsets of a complete PM-space \((X,F,*)\) with ∗ of Hadžić-type such that \(A_{0}\) and \(B_{0}\) are non-void. Let \(S:A\rightarrow B\), \(T:B\rightarrow A\) and \(g:A\cup B\rightarrow A\cup B\) satisfy the following conditions:

  1. (a)

    S and T are proximal contractions of the first kind.

  2. (b)

    \(S(A_{0}) \subseteq B_{0}\) and \(T(B_{0}) \subseteq A_{0}\).

  3. (c)

    The pair \((S, T)\) forms a proximal cyclic contraction.

  4. (d)

    g is an isometry.

  5. (e)

    \(A_{0} \subseteq g(A_{0})\) and \(B_{0} \subseteq g(B_{0})\).

Then there exist a unique element x in A and a unique element y in B satisfying the conditions that

$$\begin{aligned}& F_{gx, Sx}(t) = F_{A, B}(t), \\& F_{gy, Ty}(t) = F_{A, B}(t), \\& F_{x, y}(t) = F_{A, B}(t). \end{aligned}$$

Further, for any fixed element \(x_{0}\) in \(A_{0}\), the sequence \(\{x_{n}\}\), defined by

$$F_{gx_{n+1}, Sx_{n}}(t) = F_{A, B}(t), $$

converges to the element x. For any fixed element \(y_{0}\) in \(B_{0}\), the sequence \(\{y_{n}\}\), defined by

$$F_{gy_{n+1}, Ty_{n}}(t) = F_{A, B}(t), $$

converges to the element y.

On the other hand, a sequence \(\{u_{n}\}\) of elements in A converges to x if there is a sequence \(\{\epsilon_{n}\}\) of positive numbers for which

$$\lim_{n\rightarrow\infty} \prod_{i=0}^{n}(1- \epsilon_{i} )=1 $$

in which

$$\prod_{i=0}^{n} a_{i}=a_{0}* \cdots * a_{n} $$

for \(a_{i}\in(0,1]\) and

$$F_{u_{n+1}, z_{n+1}}(t) \geq 1-\epsilon_{n}, $$

where \(z_{n+1}\in A\) satisfies the condition that

$$F_{z_{n+1}, Su_{n}}(t) = F_{A, B}(t) $$

for \(t>0\).

Proof

Let \(x_{0}\) be an element in \(A_{0}\). In view of the facts that \(S(A_{0})\) is contained in \(B_{0}\) and that \(A_{0}\) is contained in \(g(A_{0})\), it is ascertained that there is an element \(x_{1}\) in \(A_{0}\) such that

$$F_{gx_{1}, Sx_{0}}(t) = F_{A, B}(t) $$

for \(t>0\). Again, since \(S(A_{0})\) is contained in \(B_{0}\), and \(A_{0}\) is contained in \(g(A_{0})\), there exists an element \(x_{2}\) in \(A_{0}\) such that

$$F_{gx_{2}, Sx_{1}}(t) = F_{A, B}(t) $$

for \(t>0\). One can proceed further in a similar fashion to find \(x_{n}\) in \(A_{0}\). Having chosen \(x_{n}\), one can determine an element \(x_{n+1}\) in \(A_{0}\) such that

$$F_{gx_{n+1}, Sx_{n}}(t) = F_{A, B}(t), $$

because of the facts that \(S(A_{0})\) is contained in \(B_{0}\) and that \(A_{0}\) is contained in \(g(A_{0})\). In light of the facts that g is an isometry and that S is a proximal contraction of the first kind,

$$F_{x_{n}, x_{n+1}}(\alpha t) = F_{gx_{n}, gx_{n+1}}(\alpha t) \geq F_{x_{n-1}, x_{n}}(t) $$

for \(t>0\). Therefore, by Lemma 2.6, \(\{x_{n}\}\) is a Cauchy sequence and hence converges to some element x in A. Similarly, in view of the facts that \(T(B_{0})\) is contained in \(A_{0}\) and that \(B_{0}\) is contained in \(g(B_{0})\), it is guaranteed that there is a sequence \(\{y_{n}\}\) of elements in \(B_{0}\) such that

$$F_{gy_{n+1}, Ty_{n}}(t) = F_{A, B}(t) $$

for \(t>0\). Because g is an isometry and T is a proximal contraction of the first kind, it follows that

$$F_{y_{n}, y_{n+1}}(\alpha t) =F_{gy_{n}, gy_{n+1}}(\alpha t) \geq F_{y_{n-1}, y_{n}}(t) $$

for \(t>0\). Therefore, by Lemma 2.6, \(\{y_{n}\}\) is a Cauchy sequence and hence converges to some element y in B. Since the pair \((S, T)\) forms a proximal cyclic contraction and g is an isometry, it follows that

$$F_{x_{n+1}, y_{n+1}}(t) = F_{gx_{n+1}, gy_{n+1}}(t) \geq\min \biggl\{ F_{x_{n}, y_{n}} \biggl(\frac{t}{\alpha} \biggr),F_{A, B} (t ) \biggr\} $$

for \(t>0\).

Letting \(n\rightarrow\infty\), since \(F_{x, y}(t)\leq F_{x, y}(t/\alpha)\) we have,

$$F_{x, y}(t) = F_{A, B}(t) $$

for \(t>0\). Thus, it can be concluded that x is a member of \(A_{0}\) and that y is a member of \(B_{0}\). Since \(S(A_{0})\) is contained in \(B_{0}\), and \(T(B_{0})\) is contained in \(A_{0}\), there exist an element u in A and an element v in B such that

$$\begin{aligned}& F_{u, Sx}(t) = F_{A, B}(t), \\& F_{v, Ty}(t) = F_{A, B}(t) \end{aligned}$$

for \(t>0\). Because S is a proximal contraction of the first kind,

$$F_{u, gx_{n+1}}(\alpha t) \geq F_{x, x_{n}}(t) $$

for \(t>0\). Letting \(n\rightarrow\infty\), we have the result that \(u=gx\). Thus, it follows that

$$F_{gx, Sx}(t) = F_{A, B}(t) $$

for \(t>0\). Similarly, it can be shown that \(v=gy\) and hence

$$F_{gy, Ty}(t) = F_{A, B}(t) $$

for \(t>0\). To prove the uniqueness, let us suppose that there exist elements \(x^{*}\) in A and \(y^{*}\) in B such that

$$\begin{aligned}& F_{gx^{*}, Sx^{*}}(t) = F_{A, B}(t), \\& F_{gy^{*}, Ty^{*}}(t) = F_{A, B}(t) \end{aligned}$$

for \(t>0\). Since g is an isometry, and the non-self-mappings S and T are proximal contractions of the first kind, it follows that

$$\begin{aligned}& F_{x, x^{*}}(\alpha t) = F_{gx, gx^{*}}(\alpha t) \geq F_{x, x^{*}}(t), \\& F_{y, y^{*}}(\alpha t) = F_{gy, gy^{*}}(\alpha t) \geq F_{y, y^{*}}(t) \end{aligned}$$

for \(t>0\). Therefore, x and \(x^{*}\) are identical, and y and \(y^{*}\) are identical.

On the other hand, let \(\{u_{n}\}_{n=0}^{\infty}\) in which \(u_{0}=x_{0}\) be a sequence of elements in A and \(\{\epsilon_{n}\}\) a sequence \((0,1)\) such that

$$\lim_{n\rightarrow\infty} \prod_{i=0}^{n}(1- \epsilon_{i} )=1 $$

and

$$F_{u_{n+1}, z_{n+1}}(t) \geq1-\epsilon_{n}, $$

where \(z_{n+1}\in A\) satisfies the condition that

$$F_{z_{n+1}, Su_{n}}(t) = F_{A, B}(t) $$

for \(t>0\). Since S is a proximal contraction of the first kind,

$$F_{x_{n+1}, z_{n+1}}(\alpha t) \geq F_{x_{n}, u_{n}}(t). $$

Given \(\delta\in(0,1)\), for all \(n\geq N\) we have

$$\begin{aligned} F_{x_{n+1}, u_{n+1}}( t+\delta) \geq& F_{x_{n+1}, z_{n+1}}( t) *F_{z_{n+1}, u_{n+1}}( \delta) \\ \geq& F_{x_{n}, u_{n}} \biggl(\frac{t}{\alpha} \biggr) *(1- \epsilon_{n}) \\ \geq& F_{x_{n}, u_{n}} \biggl(\frac{t}{\alpha^{2}} \biggr)*(1- \epsilon _{n-1}) *(1- \epsilon_{n}) \\ \ge&\cdots\ge F_{x_{0}, u_{0}} \biggl(\frac{t}{\alpha^{n+1}} \biggr)*\prod _{i=0}^{n}(1- \epsilon_{i}) \end{aligned}$$

for \(t>0\). Since \(\delta\in(0,1)\) was arbitrary, we have

$$ F_{x_{n+1}, u_{n+1}}( t)\ge\prod_{i=0}^{n}(1- \epsilon_{i}) $$

for \(t>0\). Now,

$$\begin{aligned} F_{u_{n+1}, x}(2t) \ge& F_{u_{n+1}, x_{n+1}}(t)*F_{x_{n+1}, x}(t) \\ \ge&\prod_{i=0}^{n}(1- \epsilon_{i}) *F_{x_{n+1}, x}(t) \end{aligned}$$

for \(t>0\). Then

$$\lim_{n\rightarrow\infty}F_{u_{n+1}, x}(2t) \to1 $$

for \(t>0\), and it can be concluded that \(\{u_{n}\}\) converges to x. This completes the proof of the theorem. □

The following example illustrates the preceding generalized best proximity point theorem.

Example 3.2

Consider the complete PM-space \(({\mathbf{R}},F,\mathrm{min})\) where

$$F_{x,y}(t)=\frac{t}{t+|x-y|}, $$

when \(t>0\) and

$$F_{x,y}(t)=0, $$

when \(t\le0\) for x, y in R.

Let \(A = [-1,0]\) and \(B = [0,1]\).

Let \(S:A\rightarrow B\), \(T:B\rightarrow A\), and \(g:A\cup B\rightarrow A\cup B\) be defined as

$$\begin{aligned}& S(x) = \frac{-x}{2}, \\& T(y) = \frac{-y}{2}, \\& g(x) = -x. \end{aligned}$$

Then it is easy to see that

$$F_{A, B}(t)=1, $$

\(A_{0} = \{0\}\) and \(B_{0} = \{0\}\). The mapping g is an isometry and the non-self-mappings S and T are proximal contractions of the first kind, and the pair \((S, T)\) forms a proximal cyclic contraction. The other hypotheses of Theorem 3.1 are also satisfied. Further, it is easy to observe that the element 0 in A and B satisfy the conditions in the conclusion of the preceding result.

If g is assumed to be the identity mapping, then Theorem 3.1 yields the following best proximity point result.

Corollary 3.3

Let A and B be non-void closed subsets of a complete PM-space \((X,F,*)\) with ∗ of Hadžić-type such that \(A_{0}\) and \(B_{0}\) are non-void. Let \(S:A\rightarrow B\) and \(T:B\rightarrow A\) satisfy the following conditions:

  1. (a)

    S and T are proximal contractions of the first kind.

  2. (b)

    \(S(A_{0}) \subseteq B_{0}\) and \(T(B_{0}) \subseteq A_{0}\).

  3. (c)

    The pair \((S, T)\) forms a proximal cyclic contraction.

Then there exist a unique element x in A and a unique element y in B satisfying the conditions that

$$\begin{aligned}& F_{x, Sx}(t) = F_{A, B}(t) , \\& F_{y, Ty}(t) = F_{A, B}(t) , \\& F_{x, y}(t) = F_{A, B}(t) \end{aligned}$$

for \(t>0\).

Theorem 3.4

Let A and B be non-void closed subsets of a complete PM-space \((X,F,*)\) with ∗ of Hadžić-type such that \(A_{0}\) and \(B_{0}\) are non-void. Let \(S:A\rightarrow B\) and \(g:A\rightarrow A\) satisfy the following conditions:

  1. (a)

    S is a proximal contraction of the first and second kind.

  2. (b)

    \(S(A_{0})\) is contained in \(B_{0}\).

  3. (c)

    g is an isometry.

  4. (d)

    S preserves isometric distance with respect to g.

  5. (e)

    \(A_{0}\) is contained in \(g(A_{0})\).

Then there exists a unique element x in A such that

$$F_{gx, Sx}(t) = F_{A, B}(t) $$

for \(t>0\). Further, for any fixed element \(x_{0}\) in \(A_{0}\), the sequence \(\{x_{n}\}\), defined by

$$F_{gx_{n+1}, Sx_{n}}(t) = F_{A, B}(t), $$

converges to the element x for \(t>0\).

On the other hand, a sequence \(\{u_{n}\}\) of elements in A converges to x if there is a sequence \(\{\epsilon_{n}\}\) of positive numbers for which

$$\lim_{n\rightarrow\infty} \prod_{i=0}^{n}(1- \epsilon_{i} )=1 $$

and

$$F_{u_{n+1}, z_{n+1}}(t) \geq 1-\epsilon_{n}, $$

where \(z_{n+1}\in A\) satisfies the condition that

$$F_{z_{n+1}, Su_{n}}(t) = F_{A, B}(t) $$

for \(t>0\).

Proof

Proceeding as in Theorem 3.1, it is possible to find a sequence \(\{x_{n}\}\) of elements in \(A_{0}\) such that

$$F_{gx_{n+1}, Sx_{n}}(t) = F_{A, B}(t) $$

for \(t>0\) and for all non-negative integral values of n, because of the facts that \(S(A_{0})\) is contained in \(B_{0}\) and that \(A_{0}\) is contained in \(g(A_{0})\). Due to the facts that S is a proximal contraction of the first kind and g is an isometry,

$$F_{x_{n}, x_{n+1}}( \alpha t) = F_{gx_{n}, gx_{n+1}}( \alpha t) \geq F_{x_{n-1}, x_{n}}(t) $$

for \(t>0\). Therefore, by Lemma 2.6, \(\{x_{n}\}\) is a Cauchy sequence and hence converges to some element x in A. Because of the facts that S is a proximal contraction of the second kind and preserves the isometric distance with respect to g,

$$F_{Sx_{n}, Sx_{n+1}}(\alpha t) = F_{Sgx_{n}, Sgx_{n+1}}(\alpha t) \geq F_{Sx_{n-1}, Sx_{n}}(t) $$

for \(t>0\). Therefore, by Lemma 2.6, \(\{Sx_{n}\}\) is a Cauchy sequence and hence converges to some element y in B. Thus, it can be concluded that

$$F_{gx, y}(t) = \lim_{n\rightarrow\infty}F_{gx_{n+1}, Sx_{n}}(t) = F_{A, B}(t). $$

Eventually, gx is an element of \(A_{0}\). Because of the fact that \(A_{0}\) is contained in \(g(A_{0})\), \(gx = gz\) for some member z in \(A_{0}\). Owing to the fact that g is an isometry, \(F_{x, z}(t) = F_{gx, gz}(t) = 1\). Consequently, the elements x and z must be identical, and hence x becomes an element of \(A_{0}\). Because \(S(A_{0})\) is contained \(B_{0}\),

$$F_{u, Sx}(t) = F_{A, B}(t) $$

for \(t>0\), for some element u in A. On account of the fact that the mapping S is a proximal contraction of the first kind,

$$F_{u, gx_{n+1}}( \alpha t) \geq F_{x, x_{n}}(t) $$

for \(t>0\). As a result, the sequence \(\{g(x_{n})\}\) must converge to u. However, because of the continuity of g, the sequence \(\{g(x_{n})\}\) converges to gx as well. Therefore, u and gx must be identical. Thus, we have the result that

$$F_{gx, Sx}(t) = F_{z, Sx}(t) = F_{A, B}(t) $$

for \(t>0\). The uniqueness and the remaining part of the proof follow as in Theorem 3.1. This completes the proof of the theorem. □

The preceding generalized best proximity point theorem is illustrated by the following example.

Example 3.5

Consider the complete PM-space \(({\mathbf{R}},F,\mathrm{min})\) where

$$F_{x,y}(t)=\frac{t}{t+|x-y|}, $$

when \(t>0\), and

$$F_{x,y}(t)=0, $$

when \(t\le0\) for \(x,y\in{\mathbf{R}}\).

Let \(A = [-1, 1]\) and \(B = [-3, -2] \cup[2, 3]\). Then \(F_{A,B}(t)=\frac{t}{t+1}\), \(A_{0} = \{-1, 1\}\), and \(B_{0} = \{-2, 2\} \). Let \(S:A\rightarrow B\) be defined as

$$Sx = \left \{ \textstyle\begin{array}{l@{\quad}l} 2 & \mbox{if }x \mbox{ is rational}, \\ 3 & \mbox{otherwise}. \end{array}\displaystyle \right . $$

Then S is a proximal contraction of the first and second kind, and \(S(A_{0}) \subseteq B_{0}\).

Further, let \(g:A\rightarrow A\) be defined as \(gx=-x\). Then g is an isometry, S preserves the isometric distance with respect to g, and \(A_{0}\subseteq g(A_{0})\). It can also be observed that \(F_{g(-1), S(-1)}(t) = F_{A,B}(t)\) for \(t>0\).

If g is assumed to be the identity mapping, then Theorem 3.4 yields the following best proximity point theorem.

Corollary 3.6

Let A and B be non-void closed subsets of a complete PM-space \((X,F,*)\) with ∗ of Hadžić-type such that \(A_{0}\) and \(B_{0}\) are non-void. Let \(S:A\rightarrow B\) satisfy the following conditions:

  1. (a)

    S is a proximal contraction of the first and second kind.

  2. (b)

    \(S(A_{0})\) is contained in \(B_{0}\).

Then there exists a unique element x in A such that

$$F_{x, Sx}(t) = F_{A, B}(t). $$

Further, for any fixed element \(x_{0}\) in \(A_{0}\), the sequence \(\{x_{n}\}\), defined by

$$F_{x_{n+1}, Sx_{n}}(t) = F_{A, B}(t), $$

converges to the best proximity point x of S.

4 Application

A solution to the nonlinear programming problem

$$\max_{x\in A}F_{x,Tx}(t) $$

is fundamentally an ideal optimal approximate solution to the equation \(Tx = x\) which is shifting to have a solution when T is supposed to be a non-self-mapping.

Considering the fact that \(F_{x,Tx}(t)\) is at least \(F_{A,B}(t)\) for all x in A, a solution x to the aforementioned nonlinear programming problem becomes an approximate solution with the lowest possible error to the corresponding equation \(Tx = x\) if it satisfies the condition that \(F_{x,Tx}(t)=F_{A,B}(t)\) for \(t>0\).

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The author is thankful to the three anonymous referees for giving valuable comments and suggestions, which helped to improve the final version of this paper.

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Saadati, R. Best proximity point theorems for probabilistic proximal cyclic contraction with applications in nonlinear programming. Fixed Point Theory Appl 2015, 79 (2015). https://doi.org/10.1186/s13663-015-0330-5

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