Abstract
In this paper, we introduce some new iterative algorithms for the split common solution problems for equilibrium problems and fixed point problems of nonlinear mappings. Some examples illustrating our results are also given.
MSC:47J25, 47H09, 65K10.
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1 Introduction
Throughout this paper, we assume that H is a real Hilbert space with zero vector θ, whose inner product and norm are denoted by and , respectively. Let K be a nonempty subset of H and T be a mapping from K into itself. The set of fixed points of T is denoted by . The symbols ℕ and ℝ are used to denote the sets of positive integers and real numbers, respectively.
Let C and K be nonempty subsets of real Banach spaces and , respectively. Let be a bounded linear mapping, T a mapping from C into itself with and f a bi-function from into R. The classical equilibrium problem is to find such that
The symbol is used to denote the set of all solutions of the problem (1.1), that is,
The equilibrium problem contains optimization problems, variational inequalities problems, saddle point problems, the Nash equilibrium problems, fixed point problems, complementary problems, bilevel problems, and semi-infinite problems as special cases and have many applications in mathematical program with equilibrium constraint; for detail, one can refer to [1–4] and references therein.
In this paper, we study the following split common solution problem (SCSP) for equilibrium problems and fixed point problems of nonlinear mappings A, T and f:
(SCSP) Find such that and which satisfies , . The solution set of (SCSP) is denoted by
Many authors had proposed some methods to find the solution of the equilibrium problem (1.1). As a generalization of the equilibrium problem (1.1), finding a common solution for some equilibrium problems and fixed point problems of nonlinear operators, it has been considered in the same subset of the same space; see [5–15]. However, some equilibrium problems and fixed point problems of nonlinear mappings always belong to different subsets of spaces in general. So the split common solution is very important for the research on generalized equilibriums problems and fixed point problems.
Example 1.1 Let , and . Let for all and for all . Let be define by for all . Clearly, A is a bounded linear operator, and . So .
Example 1.2 Let with the norm for and with the standard norm . Let and . Let for and for all . Then and A is a bounded and linear operator from into with . Now define a bi-function f as for all . Then f is a bi-function from into ℝ with .
Clearly, , . So .
Remark 1.1 It is worth to mention that the split common solution problem in Example 1.1 lies in two different subsets of the same space and the split common solution problem in Example 1.2 lies in two different subsets of the different space. So, Examples 1.1 and 1.2 also show that the split common solution problem is meaningful.
In this paper, we introduce a weak convergence algorithm and a strong convergence algorithm for the split common solution problem when the nonlinear operator T is a quasi-nonexpansive mapping. Some strong and weak convergence theorems are established. We also give some examples to illustrate our results.
2 Preliminaries
We write to indicate that the sequence weakly converges to x and will symbolize strong convergence as usual.
A Banach space is said to satisfy Opial’s condition, if for each sequence in X which converges weakly to a point , we have
It is well known that any Hilbert space satisfies Opial’s condition.
Let K be a nonempty subset of real Hilbert spaces H. Recall that a mapping is said to be nonexpansive if for all and quasi-nonexpansive if and for all , .
Example 2.1 Let with the inner product defined by for all and the standard norm . Let and for all . Obviously, . It is easy to see that
and
Hence, T is a continuous quasi-nonexpansive mapping but not nonexpansive.
Definition 2.1 (see [16])
Let K be a nonempty closed convex subset of a real Hilbert space H and T a mapping from K into K. The mapping T is said to be demiclosed if, for any sequence which weakly converges to y, and if the sequence strongly converges to z, then .
Remark 2.1 In Definition 2.1, the particular case of demiclosedness at zero is frequently used in some iterative convergence algorithms, which is the particular case when , the zero vector of H; for more detail, one can refer to [16].
The following concept of zero-demiclosedness was introduced in [17].
Definition 2.2 (see [17])
Let K be a nonempty, closed, and convex subset of a real Hilbert space and T a mapping from K into K. The mapping T is called zero-demiclosed if in K satisfying and implies .
The following result was essentially proved in [17], but we give the proof for the sake of completeness.
Proposition 2.1 Let K be a nonempty, closed, and convex subset of a real Hilbert space with zero vector θ and T a mapping from K into K. Then the following statements hold.
-
(a)
T is zero-demiclosed if and only if is demiclosed at θ;
-
(b)
If T is a nonexpansive mappings and there is a bounded sequence such that as , then T is zero-demiclosed.
Proof Obviously, the conclusion (a) holds. To see (b), since is bounded, there is a subsequence and such that . One can claim . Indeed, if , it follows from the Opial’s condition that
which is a contradiction. So and hence T is zero-demiclosed. □
Example 2.2 Let H, C, and T be the same as in Example 2.1. Let be a sequence in C. If and , then . Indeed, since T is continuous, we have and . Hence, T is zero-demiclosed.
Example 2.3 Let with the inner product defined by for all and the standard norm . Let . Let T be a mapping from C into C defined by
Then T is a discontinuous quasi-nonexpansive mapping but not zero-demiclosed.
Proof Obviously, , and T is a quasi-nonexpansive operator. On the other hand, let for all , then it is not hard to prove that , and . So T is not zero-demiclosed. □
Let and be two Hilbert spaces. Let and be two bounded linear operators. B is called the adjoint operator (or adjoint) of A, if for all , , B satisfies . It is known that the adjoint operator of a bounded linear operator on a Hilbert space always exists and is bounded linear and unique. Moreover, it is not hard to show that if B is an adjoint operator of A, then .
Example 2.4 Let with the norm for and with the norm for . Let and denote the inner product of and , respectively, where , , , . Let for . Then A is a bounded linear operator from into with . For , let . Then B is a bounded linear operator from into with . Moreover, for any and , , so B is an adjoint operator of A.
Let K be a closed and convex subset of a real Hilbert space H. For each point , there exists a unique nearest point in K, denoted by , such that , . The mapping is called the metric projection from H onto K. It is well known that has the following characterizations:
-
(i)
for every .
-
(ii)
for , and , , .
-
(iii)
for all and .
The following lemmas are crucial in our proofs.
Lemma 2.1 (see [1])
Let K be a nonempty, closed, and convex subset of H and F be a bi-function of into R satisfying the following conditions.
(A1) for all ;
(A2) F is monotone, that is, for all ;
(A3) for each , ;
(A4) for each , is convex and lower semicontinuous.
Let and . Then there exists such that , for all .
Lemma 2.2 (see [3])
Let K be a nonempty, closed, and convex subset of H and let F be a bi-function of into R satisfying (A 1)-(A 4). For , define a mapping as follows:
for all . Then the following hold:
-
(i)
is single-valued and for any and is closed and convex;
-
(ii)
is firmly nonexpansive, that is, for any , .
Lemma 2.3 (see, e.g., [9])
Let H be a real Hilbert space. Then the following hold.
-
(a)
and for all ;
-
(b)
for all and .
The following result is simple, but it is very useful in this paper; see also [18].
Lemma 2.4 Let the mapping be defined as (2.1). Then for and ,
In particular, for any and , that is is nonexpansive for any .
Proof For and , by (i) of Lemma 2.2, and for some . By the definition of , we have
and
So, combining (2.2), (2.3), and (A2), we get
or
or
or
or
which implies
and hence
In particular, the last inequality show that for any , is nonexpansive. The proof is completed. □
3 Main results
In this section, we first introduce a weak convergence iterative algorithms for the split common solution problem.
Theorem 3.1 Let and be two real Hilbert spaces and and be two nonempty closed convex sets. Let be zero-demiclosed quasi-nonexpansive mappings and be bi-functions with . Let be a bounded linear operator with its adjoint B.
Given and . Let and be sequences generated by
where with , is a constant, is a projection operator from into C and satisfies for . Then and .
Proof Let . Then . For each , by Lemmas 2.2 and 2.3, we have
So,
By (b) of Lemma 2.3 and (3.2), for each , we get
Note that for any ,
so it follows from (3.1), (3.3), and (3.4) that
Since , , by (3.5), we obtain
and
The inequality (3.6) implies that exists. Further, from (3.6) and (3.7), we get
and
From (3.1) and (3.10), we have
Since exists, is bounded and hence has a weakly convergence subsequence . Assume that for some . Then , and by (3.10) and (3.11).
We argue . Since T is a zero-demiclosed mapping, by (3.9) and , we obtain . Applying Lemma 2.2, for any . We claim . If , since as from (3.10) and applying Opial’s condition, we have
which lead to a contradiction. So , and hence we show .
Now, we prove converges weakly to . Otherwise, if there exists other subsequence of which is denoted by such that with . Then, by Opial’s condition,
This is a contradiction. Hence, converges weakly to an element .
Finally, we prove converges weakly to . Since , we have as . Thus, by (3.10), we obtain as . The proof is completed. □
Corollary 3.1 Let and be two real Hilbert spaces. Let be a zero-demiclosed quasi-nonexpansive mapping with and be a bi-function with . Let be a bounded linear operator with its adjoint B. Given . Let and be sequences generated by
where and with . Suppose and the control coefficient sequence satisfies for . Then the sequence converges weakly to an element and weakly to .
Next, we introduce a strong convergence algorithm for the split common solution problem.
Theorem 3.2 Let and be two nonempty, closed, and convex sets, zero-demiclosed quasi-nonexpansive mappings and a bi-function with . Let be a bounded linear operator with the adjoint B. Given , and . Let and be sequences generated by
where with , is a projection operator from into C and is a constant, satisfies for , then and .
Proof First, we claim for . In fact, let . Following the same argument as in Theorem 3.1, we have
and
By (3.13), (3.14), and (3.15), we get
Notice , . It follows from (3.16) that
and hence for all . Hence, and for all .
Now, we prove is a closed convex set for each . It is not hard to verify that is closed for each , so it suffices to verify that is convex for each . Indeed, let . For any , since
we have . Similarly, we also have , which implies . Hence, we show that is a convex set for each .
Notice that and , then for with . It follows that exists. Hence is bounded, which yields that and are bounded. For any with , from and the character (iii) of the projection operator P, we have
Since exists, by (3.17), we have , which implies that is a Cauchy sequence.
Let . One claim . Firstly, by , from (3.13) we have
and
Setting , from (3.16) again, we have
So
and
Let . Since as , Lemma 2.4 and equation (3.21) imply that
So , which say that . On the other hand, since by (3.19) and , we have . Notice that T is zero-demiclosed quasi-nonexpansive mappings, by (3.20), , namely, . So . From (3.21), we also have converges strongly to . The proof is completed. □
Corollary 3.2 Let and be two real Hilbert spaces. Let be a zero-demiclosed quasi-nonexpansive mappings with and be a bi-function with . Let be a bounded linear operator with the adjoint B. Given , , and . Let and be sequences generated by
where with , and is a constant. Suppose that and the control coefficient sequence satisfies for , then the sequence converges strongly to an element and converges strongly to .
Example 3.1 Let with the inner product defined by for all and the standard norm . Let and for all . From Examples 2.1 and 2.2, we know that T is an zero-demiclosed quasi-nonexpansive mapping with .
Let and for all , then f satisfies the condition (A1)-(A4) and . Let for all , then A is a bounded linear operator with B (the adjoint of A) =A and .
Obviously, , so . Let , and be sequences generated by
where, and for all , is a projection operator from into C. Then the sequence converges strongly to and converges strongly to .
Proof
-
(i)
Firstly, for given for , we prove that for any , there exists a unique sequence in K such that
(3.24)
Because (3.24) is equivalent with
while (3.25) is true if and only if for all . So the conclusion is true.
-
(ii)
Secondly, it is not hard to compute for all . Hence,
-
(iii)
By (i) and (ii), for , we can rewrite the algorithm (3.23) as follows:
(3.26)
and
As in Example 2.1, we easily obtain . Hence, from (3.26) and (3.27), we get
which shows . Since , , we obtain .
□
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Acknowledgements
The authors would like to express their sincere thanks to the anonymous referee for their valuable comments and useful suggestions in improving the paper. The first author was supported by the Natural Science Foundation of Yunnan Province (2010ZC152). The second author was supported partially by Grant no. NSC 100-2115-M-017-001 of the National Science Council of the Republic of China.
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He, Z., Du, WS. Nonlinear algorithms approach to split common solution problems. Fixed Point Theory Appl 2012, 130 (2012). https://doi.org/10.1186/1687-1812-2012-130
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DOI: https://doi.org/10.1186/1687-1812-2012-130