Best Proximity Point Theorems for Some New Cyclic Mappings
Chi-Ming Chen1and Chao-Hung Chen2
Academic Editor: Pablo GonzΓ‘lez-Vera
Received26 Feb 2012
Accepted16 Jun 2012
Published10 Jul 2012
Abstract
By using the stronger Meir-Keeler mapping, we introduce the concepts of the sMK-G-cyclic mappings, sMK-K-cyclic mappings, and sMK-C-cyclic mappings, and then we prove some best proximity point theorems for these various types of contractions. Our results generalize or improve many recent best proximity point theorems in the literature (e.g., Elderd and Veeramani, 2006; Sadiq Basha et al., 2011).
1. Introduction and Preliminaries
Let and be nonempty subsets of a metric space . Consider a mapping , is called a cyclic map if and . is called a best proximity point of in if is satisfied, where . In 2005, Eldred et al. [1] proved the existence of a best proximity point for relatively nonexpansive mappings using the notion of proximal normal structure. In 2006, Eldred and Veeramani [2] proved the following existence theorem.
Theorem 1.1 (see Theorem 3.10 in [2]). Let and be nonempty closed convex subsets of a uniformly convex Banach space. Suppose is a cyclic contraction, that is, and , and there exists such that
Then there exists a unique best proximity point in . Further, for each , converges to the best proximity point.
Later, best proximity point theorems for various types of contractions have been obtained in [3β7]. Particularly, in [8], the authors prove some best proximity point theorems for -cyclic mappings and -cyclic mappings in the frameworks of metric spaces and uniformly convex Banach spaces, thereby furnishing an optimal approximate solution to the equations of the form , where is a non-self--cyclic mapping or a non-self--cyclic mapping.
Definition 1.2 (see [8]). A pair of mappings and is said to form a -cyclic mapping between and if there exists a nonnegative real number such that
for and .
Definition 1.3 1.3 (see [8]). A pair of mappings and is said to form a -cyclic mapping between and if there exists a nonnegative real number such that
for and .
In this paper, we also recall the notion of Meir-Keeler mapping (see [9]). A function is said to be a Meir-Keeler mapping if, for each , there exists such that, for with , we have . Generalization of the above function has been a heavily investigated branch of research. In this study, we introduce the below notion of the stronger Meir-Keeler function .
Definition 1.4. We call a stronger Meir-Keeler mapping if the mapping satisfies the following condition:
The following provides two example of a stronger Meir-Keeler mapping.
Example 1.5. Let be defined by
Then is a stronger Meir-Keeler mapping which is not a Meir-Keeler function.
Example 1.6. Let be defined by
Then is a stronger Meir-Keeler mapping.
In this paper, by using the stronger Meir-Keeler mapping, we introduce the concepts of the sMK--cyclic mappings, sMK--cyclic mappings and sMK--cyclic mappings, and then we prove some best proximity point theorems for these various types of contractions. Our results generalize or improve many recent best proximity point theorems in the literature (e.g., [2, 8]).
2. sMK-G-Cyclic Mappings
In this section, we prove the best proximity point theorems for the sMK--cyclic non-self mappings.
Definition 2.1. Let be a metric space, and let and be nonempty subsets of . A pair of mappings and is said to form an sMK--cyclic mapping between and if there is a stronger Meir-Keeler function in such that for and ,
where .
Lemma 2.2. Let and be nonempty subsets of a metric space . Suppose that the mappings and form an sMK--cyclic mapping between and . Then there exists a sequence in such that
Proof. Let be given and let and for each . Taking into account (2.1) and the definition of the stronger Meir-Keeler function , we have that for each
where
Taking into account (2.3) and (2.4), we have that for each
and so we conclude that
and, for each ,
where
Taking into account (2.7) and (2.8), we have that for each
and so we conclude that
Generally, by (2.6) and (2.10), we have that for each
Thus the sequence is decreasing and bounded below and hence it is convergent. Let . Then there exists and such that for all with
Taking into account (2.12) and the definition of stronger Meir-Keeler function , corresponding to use, there exists such that
Thus, we can deduce that for each with
and so
Since , we get
that is, .
Lemma 2.3. Let and be nonempty closed subsets of a metric space . Suppose that the mappings and form an sMK--cyclic mapping between and . For a fixed point , let and . Then the sequence is bounded.
Proof. It follows from Lemma 2.2 that is convergent and hence it is bounded. Since and form an sMK--cyclic mapping between and , there is a stronger Meir-Keeler function in such that
where
Taking into account (2.17) and (2.18), we get
Therefore, the sequence is bounded. Similarly, it can be shown that is also bounded. So we complete the proof.
Theorem 2.4. Let and be nonempty closed subsets of a metric space. Let the mappings and form an sMK--cyclic mapping between and . For a fixed point , let and . Suppose that the sequence has a subsequence converging to some element in . Then, is a best proximity point of .
Proof. Suppose that a subsequence converges to in . It follows from Lemma 2.2 that converges to . Since and form an sMK--cyclic mapping between and and taking into account (2.13), we have that for each with
where
Following from (2.20) and (2.21), we obtain that
that is, we have that
letting . Then we conclude that
Therefore, , that is, is a best proximity point of .
3. sMK-K-Cyclic Mappings
In this section, we prove the best proximity point theorems for the sMK--cyclic non-self mappings.
Definition 3.1. Let be a metric space, and let and be nonempty subsets of . A pair of mappings and is said to form an sMK--cyclic mapping between and if there is a stronger Meir-Keeler function in such that, for and ,
where .
Lemma 3.2. Let and be nonempty subsets of a metric space . Suppose that the mappings and form an sMK--cyclic mapping between and . Then there exists a sequence in such that
Proof. Let be given and let and for each . Taking into account (3.1) and the definition of the stronger Meir-Keeler function , we have that
where
Taking into account (3.3) and (3.4), we have that
Similarly, we can conclude that
Generally, by (3.5) and (3.6), we have that for each
Thus the sequence is decreasing and bounded below and hence it is convergent. Let . Then there exists and such that for all with
Taking into account (3.8) and the definition of stronger Meir-Keeler function , corresponding to use, there exists such that
Thus, we can deduce that for each with
that is,
since . Therefore we get that for each with
Since , we get
that is, .
Lemma 3.3. Let and be nonempty closed subsets of a metric space . Suppose that the mappings and form an sMK--cyclic mapping between and . For a fixed point , let and . Then the sequence is bounded.
Proof. It follows from Lemma 3.2 that is convergent and hence it is bounded. Since and form an sMK--cyclic mapping between and , there is a stronger Meir-Keeler function in such that, for and ,
where . So we get that
Therefore, the sequence is bounded. Similarly, it can be shown that is also bounded. So we complete the proof.
Theorem 3.4. Let and be nonempty closed subsets of a metric space. Let the mappings and form an sMK--cyclic mapping between and . For a fixed point , let and . Suppose that the sequence has a subsequence converging to some element in . Then, is a best proximity point of .
Proof. Suppose that a subsequence converges to in . It follows from Lemma 2.2 that converges to . Since and form an sMK--cyclic mapping between and and taking into account (3.9), we have that for each with
where
Following from (3.16) and (3.17), we obtain that for each with
Letting . Then we conclude that , that is, is a best proximity point of .
4. sMK-C-Cyclic Mappings
In this section, we prove the best proximity point theorems for the sMK--cyclic non-self mappings.
Definition 4.1. Let be a metric space, and let and be nonempty subsets of . A pair of mappings and is said to form an sMK--cyclic mapping between and if there is a stronger Meir-Keeler function in such that, for and ,
where .
Lemma 4.2. Let and be nonempty subsets of a metric space . Suppose that the mappings and form an sMK--cyclic mapping between and . Then there exists a sequence in such that
Proof. Let be given and let and for each . Taking into account (4.1) and the definition of the stronger Meir-Keeler function , we have that
where
Taking into account (4.3) and (4.4), we conclude that
Similarly, we can conclude that
Generally, by (4.5) and (4.6), we have that for each
Thus the sequence is decreasing and bounded below and hence it is convergent. Let . Then there exists and such that for all with
Taking into account (4.5) and the definition of stronger Meir-Keeler function , corresponding to use, there exists such that
Thus, we can deduce that for each with
that is,
since . Therefore we get that for each with
Since , we obtain that .
Lemma 4.3. Let and be nonempty closed subsets of a metric space . Suppose that the mappings and form an sMK--cyclic mapping between and . For a fixed point , let and . Then the sequence is bounded.
Proof. It follows from Lemma 4.2 that is convergent and hence it is bounded. Since and form an sMK--cyclic mapping between and , there is a stronger Meir-Keeler function in such that for and ,
where
So we get that
Therefore, the sequence is bounded. Similarly, it can be shown that is also bounded. So we complete the proof.
Theorem 4.4. Let and be nonempty closed subsets of a metric space. Let the mappings and form an sMK--cyclic mapping between and . For a fixed point , let and . Suppose that the sequence has a subsequence converging to some element in . Then, is a best proximity point of .
Proof. Suppose that a subsequence converges to in . It follows from Lemma 2.2 that converges to . Since and form an sMK--cyclic mapping between and and taking into account (4.9), we have that, for each with ,
where
Following from (4.16) and (4.17), we obtain that
that is, we have that
Letting . Then we conclude that
Therefore, , that is, is a best proximity point of .
Acknowledgment
The authors would like to thank the referee(s) for many useful comments and suggestions for the improvement of the paper.
References
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