Abstract
In this paper, a new iterative process by the hybrid projection method is constructed. Strong convergence of the iterative process to a common element of the set of common fixed points of a finite family of generalized nonexpansive multivalued mappings and the solution set of two equilibrium problems in a Hilbert space is proved. Our results extend some important recent results.
MSC: 47H10, 47H09.
Keywords:
equilibrium problem; hybrid projection method; strong convergence; common fixed point; generalized nonexpansive multivalued mapping1 Introduction
Let C be a nonempty closed convex subset of a Hilbert space H. A subset
is called proximal if for each
there exists an element
such that
We denote by
and
the collection of all nonempty closed bounded subsets and nonempty proximal bounded
subsets of C, respectively. The Hausdorff metric H on
is defined by
Let
be a multivalued mapping. An element
is said to be a fixed point of T, if
. The set of fixed points of T will be denoted by
.
Definition 1.1 A multivalued mapping
is called
(i) nonexpansive if
(ii) quasi-nonexpansive if
and
for all
and all
.
Recently, J. Garcia-Falset, E. Llorens-Fuster and T. Suzuki [1] introduced a new condition on singlevalued mappings, called condition (E), which is weaker than nonexpansiveness.
Definition 1.2 A mapping
is said to satisfy the condition
provided that
We say that T satisfies the condition (E) whenever T satisfies
for some
.
Now we modify this condition for multivalued mappings as follows (see also [2]):
Definition 1.3 A multivalued mapping
is said to satisfy the condition
provided that
It is obvious that every nonexpansive multivalued mapping satisfies the condition
. The theory of multivalued mappings has applications in control theory, convex optimization,
differential equations and economics. Theory of nonexpansive multivalued mappings
is harder than the corresponding theory of nonexpansive single valued mappings. Different
iterative processes have been used to approximate fixed points of multivalued nonexpansive
mappings (see [3-8]). Let Φ be a bifunction from
into
, where
is the set of real numbers. The equilibrium problem for
is to find
such that
The set of solutions is denoted by
. It is well known that this problem is closely related to minimax inequalities (see
[9] and [10]). The equilibrium problem includes fixed point problems, optimization problems and
variational inequality problems as special cases. Some methods have been proposed
to solve the equilibrium problem, see, for example, [11-14].
Recently, many authors have studied the problems of finding a common element of the set of fixed points of nonexpansive single valued mappings and the set of solutions of an equilibrium problem in the framework of Hilbert spaces: see, for instance, [15-29] and the references therein. In this paper, a new iterative process by the hybrid projection method is constructed. Strong convergence of the iterative process to a common element of a set of common fixed points of a finite family of multivalued mappings satisfying the condition (P) and the solution set of two equilibrium problems in a Hilbert space is proved. Our results generalize some results of Tada, Takahashi [15] and many others.
2 Preliminaries
Let us recall the following definitions and results which will be used in the sequel.
Lemma 2.1 ([6])
LetHbe a real Hilbert space. Then for
we have
Let C be a closed convex subset of H. For every point
, there exists a unique nearest point in C, denoted by
such that
is called the metric projection of H onto C. It is well known that
is a nonexpansive mapping.
Lemma 2.2 ([16])
LetCbe a closed convex subset ofH. Given
and a point
. Then
if and only if
Lemma 2.3 ([30])
LetCbe a closed convex subset ofH. Then for all
and
we have
For solving the equilibrium problem, we assume that the bifunction Φ satisfies the following conditions:
(A2) Φ is monotone, i.e.,
for any
,
(A3) Φ is upper-hemicontinuous, i.e., for each
,
(A4)
is convex and lower semicontinuous for each
.
The following lemma was proved in [11].
Lemma 2.4LetCbe a nonempty closed convex subset ofHand let Φ be a bifunction of
into
satisfying (A1)-(A4). Let
and
. Then, there exists
such that
The following lemma was given in [14].
Lemma 2.5Assume that
satisfies (A1)-(A4). For
and
, define a mapping
as follows:
Then, the following hold:
(ii)
is firmly nonexpansive, i.e., for any
,
The following lemma was proved in [31] for nonexpansive multivalued mappings. The statement is true for quasi-nonexpansive multivalued mappings as well. To avoid repetition, we omit the details of the proof.
Lemma 2.6LetCbe a closed convex subset of a real Hilbert spaceH. Let
be a quasi-nonexpansive multivalued mapping such that
for all
. Then
is closed and convex.
Now, following Shahzad and Zegeye [3], we remove the restriction
for all
. Let
be a multivalued mapping and
We use a similar argument as in the proof of Lemma 3.1 in [31] to obtain the following lemma.
Lemma 2.7LetCbe a closed convex subset of a real Hilbert spaceH. Let
be a multivalued mapping such that
is quasi-nonexpansive. Then
is closed and convex.
Note that for all
,
. We remark that there exist some examples of multivalued mappings for which
is nonexpansive (see [3] for details), so that the assumption on T is not artificial.
3 The main result
Theorem 3.1LetCbe a nonempty closed convex subset of a real Hilbert spaceH,
and
be two bifunctions of
into
satisfying (A1)-(A4). Let
, (
), be a finite family of quasi-nonexpansive multivalued mappings, each satisfying the condition (P). Assume further that
and
, (
), for each
. For
, let
and
be sequences generated by the following algorithm:
where
,
for
. Assume that
,
,
and
,
satisfy the following conditions:
Then, the sequences
and
converge strongly to
.
Proof First, we show that
for all
. Fix
. We set
Hence we have
and
. By Lemma 2.5, we have
and
which implies that
Since
is quasi-nonexpansive, for
, we have
and also
Therefore
, which implies that
We observe that
is closed and convex (see [32]). Now we show that
exists. By Lemma 2.6 we have
is closed and convex. Put
. From
and
we have
Also from
and
for all
, we get that
It follows that the sequence
is bounded and nondecreasing. Hence the limit
exists. We show that
. For
we have
. Now by applying Lemma 2.3 we have
Since
exists, it follows that
is a Cauchy sequence, and hence there exists
such that
. Putting
, in the above inequality we have
so that
. This implies that
. Take
. By Lemma 2.1, for each
, we have
and also
So we have that
which implies that
Hence
and hence
and hence
Now we use (2) and (3) to obtain
It follows from (1) and the last inequality that
So we have
and
which implies that
which implies that
. Let us show that
. From
and
, we have
as
. Since
we obtain
From (A2), we have
and hence
Since
For
and
, let
. Since
, and C is convex we have
and hence
. So, from (A1) and (A4), we have
which gives
. From (A3) we have
,
and hence
. Similarly, we have
. Now we show that
. Since
, by Lemma 2.2 we have
Now by Lemma 2.2 we obtain that
. □
By substituting
by
and using a similar argument as in Theorem 3.1, we obtain the following result.
Theorem 3.2LetCbe a nonempty closed convex subset of a real Hilbert spaceH,
and
be two bifunctions of
into
satisfying (A1)-(A4). Let
, (
), be a finite family of multivalued mappings such that each
is quasi-nonexpansive and satisfies the condition (P). Assume further that
. For
, let
and
be sequences generated by the following algorithm:
where
,
for
. Assume that
,
,
and
,
satisfy the following conditions:
Then, the sequences
and
converge strongly to
.
As a result, for single valued mappings we obtain the following theorem.
Theorem 3.3LetCbe a nonempty closed convex subset of a real Hilbert spaceHand
and
be two bifunctions of
into
satisfying (A1)-(A4). Let
(
), be a finite family of quasi-nonexpansive mappings, each satisfying the condition (P). Assume further that
. For
, let
and
be sequences generated by the following algorithm:
Assume that
,
,
and
,
satisfy the following conditions:
Then, the sequences
and
converge strongly to
.
Theorem 3.4LetCbe a nonempty closed convex subset of a real Hilbert spaceH. Let
(
), be a finite family of multivalued mappings such that
is quasi-nonexpansive and satisfies the condition (P). Assume further that
. For
, let
be the sequence generated by the following algorithm:
where
,
for
. Assume that
(
), Then, the sequence
converges strongly to
.
Proof Putting
for all
and
in Theorem 3.2, we have
and hence
. Now, the desired conclusion follows directly from Theorem 3.2. □
Now, we supply an example to illustrate the main result of this paper.
Example 3.5 We consider the nonempty closed convex subset
of the Hilbert space
. Define two mappings
and
on C as follows:
We note that
and
are quasi-nonexpansive mappings satisfying the condition (P), (for details, see [2]). Also we define two bifunctions
and
as follows:
It is easy to see that
and
satisfy the conditions (A1)-(A4). If we put
and
, then
and
(for details, see [26]). Put
for
and
. For any arbitrary
we have
By continuing this process we obtain
and hence
Now, we have the following algorithm:
We observe that for an arbitrary
,
is convergent to zero. We note that
.
Remark 3.6 Since every nonexpansive mapping is quasi-nonexpansive and satisfies the condition (P), our results hold for nonexpansive mappings.
Remark 3.7 Our results generalize the results of Tada and Takahashi [15], of a nonexpansive single valued mapping to a finite family of generalized nonexpansive multivalued mappings.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
All the authors contributed equally to the writing of the present article. And they also read and approved the final manuscript.
Acknowledgements
Research of the first author was supported in part by a grant from Imam Khomeini International University, under the grant number 751164-91.
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