Abstract
The main aim of this work is to introduce an implicit general iterative method for approximating a solution of a split variational inclusion problem with a hierarchical optimization problem constraint for a countable family of mappings, which are nonexpansive, in the setting of infinite dimensional Hilbert spaces. Convergence theorem of the sequences generated in our proposed implicit algorithm is obtained under some weak assumptions.
1. Introduction
Let be a real Hilbert space with norm and inner product . Suppose that C is a nonempty convex and set in , and let be the metric (nearest point) projection from space onto set C. We use to denote a mapping on C. Denote by the set of fixed points of T, i.e., . We use the notations ⇀ and → to indicate the weak convergence and the strong convergence, respectively.
Assume that is a nonlinear mapping. The classical monotone variational inequality (VI) is to find such that
We denote by VI the solution set of VI (1). VI (1), which acts as a very powerful and effective research tool, has been applied to study lots of theory problems arising in nonlinear equations, computational mechanics, optimization contact problems in control problems, elasticity, operations research, modern management science, bi-function equilibrium problems in transportation and economics, obstacle, unilateral, moving, etc.; see [1,2,3,4,5,6,7,8,9,10,11,12] and the references therein.
An operator D is said to be a strongly positive operator on , if there is a constant such that
Solution methods for Lipchitz mappings, in particular, nonexpansive mappings, have widely been applied to investigate minimization problems of various convex functions. A mapping is said to be set-valued monotone if for all and imply . Recall that is a maximal operator if the graph Gph is not properly contained in the graph of any other monotone operator. As we all know that M is maximal if and only if for for every , we have .
We now assume that set-valued operator is maximal. We can define a single-valued mapping by
is called the resolvent operator associated with mapping M. It deserves mentioning that it is single-valued and Liptchitz.
Let be another Hilbert space with usual norm () and inner product (). Let A be a bounded linear operator from to . We consider in this paper the following split variational inclusion problem (SVIP): find such that
and
where and are set-valued and maximal monotone. SOLVIP() stands for the solution set of (2) and SOLVIP() stands for the solution set of (3), respectively. The solution set of SVIP (2)–(3) will be used and denoted by . From [13], we know that SVIP (2)–(3) is equivalent to approximating with such that
holds for any given . It is remarkable that if , then
and
Let be a countable family mappings on . We assume that is a real sequence in . For any , we give a mapping by:
If each is nonexpansive, then is Lipschitz. Indeed, it is also nonexpansive and called a W-mapping defined by and . From [14], we know that is a nonexpansive mapping with the relation , for each ; for each and for each positive integer k, the exists; W is defined by
has the nonexpansivity and it satisfies (We call a W-mapping generated by and ). Recently, common fixed-point problems, which finds applications in signal process and medical image restoration, have been studied based on mean-valued or projection methods; see [14,15,16,17,18,19] and references cited therein.
In this present work, we investigate an implicit general iterative method for computing a solution of the SVIP with a hierarchical optimization problem constraint for a countable family of mappings, which will be assumed to have the nonexpansivity, in the framework of real Hilbert spaces. Norm convergence theorems of the sequences generated by our implicit general algorithm are established under some suitable assumptions. Our results extend, unify, develop and improve the corresponding ones in the recent literature.
2. Preliminaries
Now we list some basic notations and facts. will be assumed to be a real Hilbert space and C will be assume to be a closed nonempty convex subset in . A mapping is called a -Lipschitzian mapping if there is a number with , . In particular, if , then F is said to be a nonexpansive operator. If , then F is said to be a contractive operator. A mapping is said to be -strongly monotone if there exists a number such that . In all Hilbert spaces, we known
for all and .
Fixing , we see that there exists a unique nearest point in closed convex set C. We denote it by . . The mapping is called the metric or nearest point projection of onto C. We know that is an nonexpansive operator from space onto set C. In addition, we know that
also enjoys
for all and . It is not too hard to see that (6) is equivalent to the following relation
It is also not hard to find that every nonexpansive operator satisfies the following relation
In particular, one has
Let be a self mapping. It is said to be an averaged operator if it is a combination of the identity operator I and a nonexpansivity operator, that is, where and is an nonexpansive operator. We mention that the class of averaged mappings are of course nonexpansive. Also, mappings, which are firmly nonexpansive are averaged. Indeed, projections on convex nonempty closed sets and resolvent operators of set-valued monotone operators. Some important properties and relations of averaged mappings are gathered in the following lemma; see e.g., [20,21,22,23,24,25] and references cited therein.
Lemma 1.
For any given , let the mapping be defined as where , L is the spectral radius of the operator and is the adjoint of A. Then G is a nonexpansive mapping. If , then .
Proof.
Since and are mappings enjoys the firm nonexpansivity, they, of course, are averaged. For , the mapping is averaged. So is a averaged operator and hence a nonexpansive operator.
Next, let us show that if then . Indeed, it is clear that . Conversely, we take and arbitrarily. Then . Hence,
which immediately yields
One has
Using the last two inequalities, we obtain
which immediately leads to
Taking into account , one knows that and . So it follows from (10) that , i.e., . Also, from we get
Hence, . Consequently, . This completes the proof. □
Lemma 2.
[26], Let be a countable family on a real Hilbert space with the restriction . will be assumed to be a sequence in for some . If C is any bounded set in and each is the self nonexpansivity, then
Through the rest of this paper, will be assumed to be in for some .
Lemma 3.
[27], Assume that both and are bounded real sequences in infinite dimensional space either Banach or Hilbert. We support that is a sequence with the restriction that it is bounded away from , that is, . We assume and Hence, .
Lemma 4.
[28], Let C be a closed nonempty convex set in a real Hilbert space , and let be a monotone and hemicontinuous mapping. We the following:
(i) ;
(ii) for all ;
(iii) is singleton, if B is strongly monotone and Lipschitz continuous.
Lemma 5.
[29], All Hilbert spaces satisfies the well known Opial condition: the inequality holds for every and for any sequence with .
Lemma 6.
[30], Assume that S is a nonexpansive self-mapping on a closed convex nonempty set C in . If S is fixed-point free, then is demi-closed at zero, i.e., if is a sequence in C weakly converging to some x in the set and the sequence converges strongly to zero, then , where I stands for the identity operator.
Lemma 7.
[31], Assume that be a real iterative sequence with the conditions where and are real sequences with the restrictionis and , . Then .
3. Main Results
Theorem 1.
Let , where and are two different Hilbert spaces, be a linearly bounded operator. Suppose that and are maximal monotone mappings. Let be a contraction mapping with contractive coefficient and let the linearly bounded operator be strongly positive with coefficient and . Let the mapping be defined as , where , L be the spectral radius of and is the adjoint operator of A. Assume that . For an arbitrary , we define and by
where is defined in (4), and and are real number sequences in . Suppose the parameter sequences satisfy the following three restrictions:
(C1) for some ;
(C2) as and ;
(C3) and .
Then converges to a point in norm and z is a solution to
that is, .
Proof.
First of all, taking into account that as and , we can suppose and for some . Please note that the mapping is defined as , where , is the radius of the operator . By virtue of Lemma 1, we get that G is is nonexpansivity. It is easy to see that there exists an element , which is unique, such that
Define a mapping by
Since each is a nonexpansive mapping, we deduce that, all ,
Also, from , we get for all . Thus, is a contraction operator. This shows that there exists an element , satisfying (12). Indeed, is also unique. So, it can be readily seen that the general implicit iterative scheme (11) can be rewritten as
Next, we divide the rest of our proofs into some steps to prove this theorem.
Step 1. We prove that and are bounded sequence in . By arbitrarily taking an element , we get and . Since each is a nonexpansive operator, it follows that
Note that
Please note that
By considering item and by using (9), we have
Using inequalities (15), (16) and (17), we obtain
From , we get
Substituting (19) for (14), we have
which combining (19) yields that
Thanks to the two restrictions (C1) and (C2), we can suppose that , . Since D is linearly strongly positive bounded, we can easily get that
In view of (13), (20) and (21), one has that
It immediately yields that is a bounded sequence in . Indeed, and (due to (20) and the Lipschitz continuity of and f) are bounded sequences. From this, we fix a bounded subset with the restriction
Step 2. We aim that and as . Indeed, we set
This shows that
Hence,
By using Lemma 1, we know that is Lipchitz. Indeed, it is nonexpansive. Hence, we obtain from (13) that
However, we have that
where C stands for the bounded subset in defined by (22). Simple calculations show that
So it yields from that
Thus, from (25), (26) and (29) we deduce that
Thanks to the three assumptions (C1), (C2), (C3), and Lemma 2,
From Lemma 3, we thus obtain that
This in turn implies that
This together with (26) and (29), implies that
Step 3. We aim to prove and as . Indeed, we set for all . For any , we observe that
where . Substituting (18) for (33), we obtain from (20) that Therefore,
From the assumption that is a firmly nonexpansive mapping, we have
Hence, we obtain
Substituting (35) for (33), one concludes from (20) that
(C1), (C2), (31), and (34) send us to
Also, according to (11) and (19) we have
which immediately leads to
It follows from (19) and (33) that
This implies that
(C1), (C2), and (3.21) send us to
Noticing that ,
and
we deduce from (36) and (37) that
Step 4. We aims to , where z denotes the fixed-point of mapping . Indeed, we first show that consists of one point. As a matter of fact, we note that linear bounded operator D is strongly positive with its coefficient and . Then for any , we have
Hence we knows that monotone operator is strongly and the coefficient satisfies . It is also clear that is Lipschitzian. Therefore, by Lemma 4 (iii) we deduce that is a single-point set. Say , that is, . Also, by Lemma 4 (ii) we have . Since is a bounded sequence in , without loss of generality, we may choose a subsequence of such that
We have proved that sequence is bounded, it is not too hard to see its a subsequence of converges weakly to w. Let suppose that . From (37), we obtain that .
Next, let us pay our focus to . Supposing on the contrary that, , i.e., , we see from Lemma 5 that
On the other hand, we have
By using Lemma 3 and (38), we obtain that , which together with (40), yields This reaches a contraction, and hence we have . Please is a nonexpansive mapping. Since and (due to (38)), by Lemma 6, we get that . From Lemma 1, we get that . Therefore, . Since z is a fixed point of mapping and , we have
Step 5. We aim to and as . Indeed, by (3.10) and (3.11) we have
This immediately implies that
By using Lemma 7, we infer that as . This completes the proof. □
4. Conclusions
In this paper, we studied an implicit general iterative method for approximating a solution of a split variational inclusion problem with a hierarchical optimization problem constraint for a countable family of mappings, which are nonexpansive, in the setting of infinite dimensional Hilbert spaces. Convergence theorem of the sequences generated in our proposed implicit algorithm is obtained without compact assumptions.
Author Contributions
These authors contributed equally to this work.
Funding
This research was funded by the Natural Science Foundation of Shandong Province of China (ZR2017LA001) and Youth Foundation of Linyi University (LYDX2016BS023).
Acknowledgments
The authors are grateful to the editor and the referees for useful suggestions which improved the contents of this paper.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Bao, T.Q.; Tammer, C. Subdifferentials and SNC property of scalarization functionals with uniform level sets and applications. J. Nonlinear Var. Anal. 2018, 2, 355–378. [Google Scholar]
- Cho, S.Y. Generalized mixed equilibrium and fixed point problems in a Banach space. J. Nonlinear Sci. Appl. 2016, 9, 1083–1092. [Google Scholar] [CrossRef]
- Cho, S.Y.; Li, W.; Kang, S.M. Convergence analysis of an iterative algorithm for monotone operators. J. Inequal. Appl. 2013, 2013, 199. [Google Scholar] [CrossRef]
- Byrne, C. A unified treatment of some iterative algorithms in signal processing and image reconstruction. Inverse Probl. 2004, 20, 103–120. [Google Scholar] [CrossRef]
- Qin, X.; Yao, J.C. Weak convergence of a Mann-like algorithm for nonexpansive and accretive operators. J. Inequal. Appl. 2016, 2016, 232. [Google Scholar] [CrossRef][Green Version]
- Kazmi, K.R.; Rizvi, S.H. An iterative method for split variational inclusion problem and fixed point problem for a nonexpansive mapping. Optim. Lett. 2014, 8, 1113–1124. [Google Scholar] [CrossRef]
- Qin, X.; Yao, J.C. Projection splitting algorithms for nonself operators. J. Nonlinear Convex Anal. 2017, 18, 925–935. [Google Scholar]
- Ceng, L.C.; Guu, S.M.; Yao, J.C. Hybrid viscosity CQ method for finding a common solution of a variational inequality, a general system of variational inequalities, and a fixed point problem. Fixed Point Theory Appl. 2013, 2013, 25. [Google Scholar] [CrossRef]
- Lions, J.L.; Stampacchia, G. Variational ineqalities. Commun. Pure Appl. Math. 1967, 20, 493–519. [Google Scholar] [CrossRef]
- Glowinski, R.; Tallec, P.L. Augmented Lagrangian and Operator Splitting Methods in Nonlinear Mechanics; SIAM Studies in Applied Mathematics: Philadelphia, PA, USA, 1989. [Google Scholar]
- Zhao, X.; Ng, K.F.; Li, C.; Yao, J.C. Linear regularity and linear convergence of projection-based methods for solving convex feasibility problems. Appl. Math. Optim. 2018, 78, 613–641. [Google Scholar] [CrossRef]
- Qin, X.; Cho, S.Y.; Wang, L. Strong convergence of an iterative algorithm involving nonlinear mappings of nonexpansive and accretive type. Optimization 2018, 67, 1377–1388. [Google Scholar] [CrossRef]
- Ceng, L.C.; Wong, N.C.; Yao, J.C. Hybrid extragradient methods for finding minimum-norm solutions of split feasibility problems. J. Nonlinear Convex Anal. 2015, 16, 1965–1983. [Google Scholar]
- Shimoji, K.; Takahashi, W. Strong convergence to common fixed points of infinite nonexpansive mappings and applications. Taiwan. J. Math. 2001, 5, 387–404. [Google Scholar] [CrossRef]
- Takahashi, W.; Wen, C.F.; Yao, J.C. Split common fixed point problems and hierarchical variational inequality problems in Hilbert spaces. J. Nonlinear Convex Anal. 2017, 18, 777–797. [Google Scholar]
- Alsulami, S.M.; Latif, A.; Takahashi, W. The split common fixed point problem and strong convergence theorems by hybrid methods for new demimetric mappings in Hilbert spaces. Appl. Anal. Optim. 2018, 2, 11–26. [Google Scholar]
- Chang, S.S.; Wen, C.F.; Yao, J.C. Generalized viscosity implicit rules for solving quasi-inclusion problems of accretive operators in Banach spaces. Optimization 2017, 66, 1105–1117. [Google Scholar] [CrossRef]
- Cho, S.Y.; Dehaish, B.A.B.; Qin, X. Weak convergence of a splitting algorithm in Hilbert spaces. J. Comput. Anal. Appl. 2017, 7, 427–438. [Google Scholar]
- Takahashi, W.; Wen, C.F.; Yao, J.C. An implicit algorithm for the split common fixed point problem in Hilbert spaces and applications. Appl. Anal. Optim. 2017, 1, 423–439. [Google Scholar]
- Fang, N. Some results on split variational inclusion and fixed point problems in Hilbert spaces. Commun. Optim. Theory 2017, 2017, 5. [Google Scholar]
- Ceng, L.C.; Wong, M.M.; Yao, J.C. A hybrid extragradient-like approximation method with regularization for solving split feasibility and fixed point problems. J. Nonlinear Convex Anal. 2013, 14, 163–182. [Google Scholar]
- Qin, X.; Cho, S.Y. Convergence analysis of a monotone projection algorithm in reflexive Banach spaces. Acta Math. Sci. 2017, 37, 488–502. [Google Scholar] [CrossRef]
- Dehaish, B.A.B. A regularization projection algorithm for various problems with nonlinear mappings in Hilbert spaces. J. Inequal. Appl. 2015, 2015, 51. [Google Scholar] [CrossRef]
- Hao, Y. Viscosity methods for nonexpansive and monotone mappings in Hilbert spaces. J. Nonlinear Funct. Anal. 2018, 2018, 40. [Google Scholar]
- Qin, X.; Wang, L. A regularization method for treating zero points of the sum of two monotone operators. Fixed Point Theory Appl. 2014, 2014, 75. [Google Scholar] [CrossRef]
- Chang, S.S.; Lee, H.W.J.; Chan, C.K. A new method for solving equilibrium problem fixed point problem and variational inequality problem with application to optimization. Nonlinear Anal. 2009, 70, 3307–3319. [Google Scholar] [CrossRef]
- Suzuki, T. Strong convergence of Krasnoselskii and Mann’s type sequences for one-parameter nonexpansive semigroups without Bochner integrals. J. Math. Anal. Appl. 2005, 305, 227–239. [Google Scholar] [CrossRef]
- Iiduka, H. Iterative algorithm for solving triple-hierarchical constrained optimization problem. J. Optim. Theory Appl. 2011, 148, 580–592. [Google Scholar] [CrossRef]
- Opial, Z. Weak convergence of successive approximations for nonexpansive mappings. Bull. Am. Math. Soc. 1967, 73, 591–597. [Google Scholar] [CrossRef]
- Goebel, K.; Kirk, W.A. Topics on Metric Fixed-Point Theory. In Cambridge Studies in Advanced Mathematics; Cambridge University Press: Cambridge, UK, 1990; Volume 28. [Google Scholar]
- Xue, Z.; Zhou, H.; Cho, Y.J. Iterative solutions of nonlinear equations for m-accretive operators in Banach spaces. J. Nonlinear Convex Anal. 2000, 1, 313–320. [Google Scholar]
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