- Research Article
- Open Access
A Hybrid Projection Algorithm for Finding Solutions of Mixed Equilibrium Problem and Variational Inequality Problem
Fixed Point Theory and Applications volume 2010, Article number: 383740 (2009)
We propose a modified hybrid projection algorithm to approximate a common fixed point of a -strict pseudocontraction and of two sequences of nonexpansive mappings. We prove a strong convergence theorem of the proposed method and we obtain, as a particular case, approximation of solutions of systems of two equilibrium problems.
In this paper, we define an iterative method to approximate a common fixed point of a -strict pseudocontraction and of two sequences of nonexpansive mappings generated by two sequences of firmly nonexpansive mappings and two nonlinear mappings. Let us recall from  that the -strict pseudocontractions in Hilbert spaces were introduced by Browder and Petryshyn in .
is said to be -strict pseudocontractive if there exists such that
The iterative approximation problems for nonexpansive mappings, asymptotically nonexpansive mappings, and asymptotically pseudocontractive mappings were studied extensively by Browder , Goebel and Kirk , Kirk , Liu , Schu , and Xu [8, 9] in the setting of Hilbert spaces or uniformly convex Banach spaces. Although nonexpansive mappings are 0-strict pseudocontractions, iterative methods for -strict pseudocontractions are far less developed than those for nonexpansive mappings. The reason, probably, is that the second term appearing in the previous definition impedes the convergence analysis for iterative algorithms used to find a fixed point of the -strict pseudocontraction . However, -strict pseudocontractions have more powerful applications than nonexpansive mappings do in solving inverse problems. In the recent years the study of iterative methods like Mann's like methods and CQ-methods has been extensively studied by many authors [1, 10–13] and the references therein.
If is a closed and convex subset of a Hilbert space and is a bi-function we call equilibrium problem
and we will indicate the set of solutions with .
If is a nonlinear mapping, we can choose , so an equilibrium point (i.e., a point of the set ) is a solution of variational inequality problem (VIP)
We will indicate with the set of solutions of VIP.
The equilibrium problems, in its various forms, found application in optimization problems, fixed point problems, convex minimization problems; in other words, equilibrium problems are a unified model for problems arising in physics, engineering, economics, and so on (see ).
As in the case of nonexpansive mappings, also in the case of -strict pseudocontraction mappings, in the recent years many papers concern the convergence of iterative methods to a solutions of variational inequality problems or equilibrium problems; see example for, [10, 14–18].
Here we prove a strong convergence theorem of the proposed method and we obtain, as a particular case, approximation of solutions of systems of two equilibrium problems.
Let be a real Hilbert space and let be a nonempty closed convex subset of .We denote by the metric projection of onto . It is well known  that
(see ) Let be a Banach space with weakly sequentially continuous duality mapping , and suppose that converges weakly to , then for any ,
Moreover if is uniformly convex, equality holds in (2.2) if and only if .
Recall that a point is a solution of a VIP if and only if
An operator is said to be -inverse strongly monotone operator if there exists a constant such that
If we say that is firmly nonexpansive. Note that every -inverse strongly monotone operator is also Lipschitz continuous (see ).
(see ). Let be a nonempty closed convex subset of a real Hilbert space and let be a -strict pseudocontractive mapping. Then with is a nonexpansive mapping with .
3. Main Theorem
Let be a closed convex subset of a real Hilbert space . Let
(i) be an -inverse strongly monotone mapping of into ,
(ii) a -inverse strongly monotone mapping of into ,
(iii) and two sequences of firlmy nonexpansive mappings from to .
Let be a -strict pseudocontraction .
Set and let us define the sequence as follows:
(i) with ;
Moreover suppose that
(ii) pointwise converges in to an operator and pointwise converges in to an operator ;
(iii) and .
Then strongly converges to .
We begin to observe that the mappings and are nonexpansive for all since they are compositions of nonexpansive mappings (see [22, page 419]). As a rule, if
Now we divide the proof in more steps.
is closed and convex for each .
Indeed is the intersection of with the half space
for each .
For each we have
So the claim immediately follows by induction.
exists and is asymptotically regular, that is, .
Since , and , by (2.1) choosing and , we have
that is, .
By and , we have
Then exists and is bounded. Moreover
and consequently .
By , it follows
and by boundedness of , it follows that .
, for each .
For , we have
and by Step 4, the assumptions on and , we obtain the claim of Step 5.
Since is firmly nonexpansive, for any , we have
By the assumptions on , Steps 4 and 6, and the boundedness of and the claim follows.
Since is firmly nonexpansive, for each , we have
Then, for each , we have
and by the assumptions on , Step 4 and the boundedness of and it follows that as . By Step 6 we note that also .
and by previous steps, it follows that as .
The set of weak cluster points of is contained in .
We will use three times the Opial's Lemma 2.1.
Let be a weak cluster point of and let be a subsequence of such that .
We prove that . We suppose for absurd that . By Opial's Lemma 2.1 and as , we obtain
which is a contradiction.
Since it is enough to prove that . Now if we note that
This leads to a contraddiction again. By the hypotheses and Step 7 the claim follows. By the same idea and using Step 6, we prove that .
Since and , we have
Let be a subsequence of such that . By Step 8, . Thus
Therefore we have
Since has the Kadec-Klee property, then as .
Moreover, by and by the uniqueness of the projection , it follows that .
Thence every subsequence converges to as and consequently , as .
Let us observe that one can choose and as sequences of -inverse strongly monotone operators and -inverse strongly monotone operators provided for all .
The hypotheses and in the main Theorem 3.1 seem very strong but, in the sequel, we furnish two cases in which (ii) and (iii) are satisfied.
Let us remember that the metric projection on a convex closed set is a firmly nonexpansive mapping (see ) so we claim that have the following proposition.
If is such that and an -inverse strongly monotone, then realizes conditions (ii) and (iii) with .
To prove (ii) we note that for each ,
Moreover, (iii) follows directly by (2.2).
Now we consider the mixed equilibrium problem
In the sequel we will indicate with the set of solution of our mixed equilibrium problem. If we denote with .
We notice that for and the problem is the well-known equilibrium problem [23–25]. If and is an -inverse strongly monotone operator we have the equilibrium problems studied firstly in  and then in [18, 22, 27]. If and we refound the mixed equilibrium problem studied in [16, 28, 29].
A bi-function is monotone if for all .
A function is upper hemicontinuous if
Next lemma examines the case in which .
Let be a convex closed subset of a Hilbert space .
Let be a bi-function such that
(f1) for all ;
(f2) is monotone and upper hemicontinuous in the first variable;
(f3) is lower semicontinuous and convex in the second variable.
Let be a bi-function such that
(h1) for all ;
(h2) is monotone and weakly upper semicontinuous in the first variable;
(h3) is convex in the second variable.
Moreover let us suppose that
()for fixed and , there exists a bounded set and such that for all , ,
for and let be a mapping defined by
called resolvent of and .
(2) is a single value;
(3) is firmly nonexpansive;
(4) and it is closed and convex.
Let . For any define
We will prove that, by KKM's lemma, is nonempty.
First of all we claim that is a KKM's map. In fact if there exists such that (with ) does not appartiene to for any then
By the convexity of and and the monotonicity of , we obtain that
that is absurd.
Now we prove that . We recall that, by the weak lower semicontinuity of , the relation
holds. Let and let be a sequence in such that .
We want to prove that
Since is lower semicontinuous and convex in the second variable and is weakly upper semicontinuous in the first variable, then
Now we observe that is weakly compact for at least a point . In fact by hypothesis (H) there exist a bounded and , such that for all it results . Then , that is, it is bounded. It follows that is weakly compact. Then by KKM's lemma is nonempty. However if then
As in [24, Lemma 3], since is upper hemicontinuous and convex in the first variable and monotone, we obtain that (3.36) is equivalent to claim that is such that
that is, . This prove (1). To prove (2) and (3) we consider and . They satisfy the relations
By the monotonicity of and , summing up both the terms,
so we conclude
that means simultaneously that if and is firmly nonexpansive.
To prove (4), it is enough to follow (iii) and (iv) in [25, Lemma 2.12].
We note that if , our lemma reduces to [25, Lemma 2.12]. The coercivity condition (H) is fulfilled.
Moreover our lemma is more general than [16, Lemma 2.2]. In fact
(i)our hypotheses on are weaker ( weak upper semicontinuous implies upper hemicontinuous);
(ii)if satisfies the condition in Lemma 2.2, choosing one has that is concave and upper semicontinuous in the first variable and convex and lower semicontinous in the second variable;
(iii)the coercivity condition (H) by the equivalence of (3.36) and (3.37) is the same.
Let us suppose that (f1)–(f3), (h1)–(h3) and (H) hold. Let , . Then
By Lemma 3.5, defining and , we know that
Hence, summing up this two inequalities and using the monotonicity of and ,
We derive from (3.44) that
and thus the claim holds.
Let us suppose that and are two bi-functions satisfying the hypotheses of Lemma 3.5. Let be the resolvent of and . Let be an -inverse strongly monotone operator. Let us suppose that is such that . Then realize (ii) and (iii) in Theorem 3.1.
Let be in a bounded closed convex subset of . To prove (i) it is enough to observe that by Lemma 3.7
When , by boundedness of the terms that do not depend on , we obtain (ii).
To prove (iii) let the pointwise limit of . It is necessary to prove only that . Let . We want to prove that . Let . Thus, by definition of , is the unique point such that
By monotonicity of and this implies
Passing to the limit on , by (f3) and (h2) we obtain
Let now with . Then by the convexity of and
Passing we obtain by (f1) and (h1)
That is, . At this point we observe that from the definitions of and , one has .
By Propositions 3.3 and 3.8 we can exhibit iterative methods to approximate fixed points of the -strict pseudo contraction that are also
(1)solution of a system of two variational inequalities VI(C,A) and VI(C,B) ();
(2)solution of a system of two mixed equilibrium problems ( and );
(3)solution of a mixed equilibrium problem and a variational inequality ( and ).
However when the properties of the mapping and are well known, one can prove convergence theorems like Theorem 3.1 without use of Opial's lemma.
In next theorem our purpose is to prove a strong convergence theorem to approximate a fixed point of that is also a solution of a mixed equilibrium problem and a solution of a variational inequality . One can note that we relax the hypotheses on the convergence of the sequences and .
Let be a closed convex subset of a real Hilbert space , let be two bi-functions satisfying (f1)–(f3),(h1)–(h3), and (H). Let be a -strict pseudocontraction.
Let be an -inverse strongly monotone mapping of into and let be a -inverse strongly monotone mapping of into .
Let us suppose that .
Set , one defines the sequence as follows:
(i) with ;
Then strongly converges to .
First of all we observe that by Lemma 3.5 we have that . We can follow the proof of Theorem 3.1 from Steps 1–7. We prove only the following.
The set of weak cluster points of is contained in .
Let be a cluster point of ; we begin to prove that . We know that
and by (f2)
Let be a subsequence of weakly convergent to , then by Step 7 as . Let . Then by (3.56)
Since is Lipschitz continuous and as , we have as .
By condition , for fixed, the function is lower semicontinuos and convex, and thus weakly lower semicontinuous .
Since , as and by the assumption on we obtain . Then we obtain by (h2)
Using (f1), (f3), (h1), (h3) we obtain
by (f2) and (h2), as , we obtain .
Now we prove that .
We define the maximal monotone operator
where is the normal cone to at , that is,
Since , by the definition of we have
But , then
By (3.63), (3.65), and by the -inverse monotonicity of , we obtain
By as (immediately consequence of Steps 6 and 7), it follows that as . Then
moreover, since is a maximal operator, , that is, .
Finally, to prove that we follow Step 8 as in Theorem 3.1.
Since also Step 9 can be followed as in Theorem 3.1, we obtain the claim.
Acedo GL, Xu H-K: Iterative methods for strict pseudo-contractions in Hilbert spaces. Nonlinear Analysis: Theory, Methods & Applications 2007,67(7):2258–2271. 10.1016/j.na.2006.08.036
Browder FE, Petryshyn WV: Construction of fixed points of nonlinear mappings in Hilbert space. Journal of Mathematical Analysis and Applications 1967, 20: 197–228. 10.1016/0022-247X(67)90085-6
Browder FE: Nonexpansive nonlinear operators in a Banach space. Proceedings of the National Academy of Sciences of the United States of America 1965, 54: 1041–1044. 10.1073/pnas.54.4.1041
Goebel K, Kirk WA: A fixed point theorem for asymptotically nonexpansive mappings. Proceedings of the American Mathematical Society 1972, 35: 171–174. 10.1090/S0002-9939-1972-0298500-3
Kirk WA: A fixed point theorem for mappings which do not increase distances. The American Mathematical Monthly 1965, 72: 1004–1006. 10.2307/2313345
Liu Q: Convergence theorems of the sequence of iterates for asymptotically demicontractive and hemicontractive mappings. Nonlinear Analysis: Theory, Methods & Applications 1996,26(11):1835–1842. 10.1016/0362-546X(94)00351-H
Schu J: Iterative construction of fixed points of asymptotically nonexpansive mappings. Journal of Mathematical Analysis and Applications 1991,158(2):407–413. 10.1016/0022-247X(91)90245-U
Xu HK: Inequalities in Banach spaces with applications. Nonlinear Analysis: Theory, Methods & Applications 1991,16(12):1127–1138. 10.1016/0362-546X(91)90200-K
Xu HK: Existence and convergence for fixed points of mappings of asymptotically nonexpansive type. Nonlinear Analysis: Theory, Methods & Applications 1991,16(12):1139–1146. 10.1016/0362-546X(91)90201-B
Ceng L-C, Al-Homidan S, Ansari QH, Yao J-C: An iterative scheme for equilibrium problems and fixed point problems of strict pseudo-contraction mappings. Journal of Computational and Applied Mathematics 2009,223(2):967–974. 10.1016/j.cam.2008.03.032
Marino G, Xu H-K: Weak and strong convergence theorems for strict pseudo-contractions in Hilbert spaces. Journal of Mathematical Analysis and Applications 2007,329(1):336–346. 10.1016/j.jmaa.2006.06.055
Marino G, Colao V, Qin X, Kang SM: Strong convergence of the modified Mann iterative method for strict pseudo-contractions. Computers and Mathematics with Applications 2009,57(3):455–465. 10.1016/j.camwa.2008.10.073
Zhou H: Convergence theorems of fixed points for -strict pseudo-contractions in Hilbert spaces. Nonlinear Analysis: Theory, Methods & Applications 2008,69(2):456–462. 10.1016/j.na.2007.05.032
Colao V, Marino G, Xu H-K: An iterative method for finding common solutions of equilibrium and fixed point problems. Journal of Mathematical Analysis and Applications 2008,344(1):340–352. 10.1016/j.jmaa.2008.02.041
Moudafi A: Viscosity approximation methods for fixed-points problems. Journal of Mathematical Analysis and Applications 2000,241(1):46–55. 10.1006/jmaa.1999.6615
Peng JW: Iterative algorithms for mixed equilibrium problems, strictly pseudocontractions and monotone mappings. Journal of Optimization Theory and Applications. In press
Peng JW, Liou YC, Yao JC: An iterative algorithm combining viscosity method with parallel method for a generalized equilibrium problem and strict pseudocontractions. Fixed Point Theory and Applications 2009, Article ID 794178 2009:-21.
Cho YJ, Qin X, Kang JI: Convergence theorems based on hybrid methods for generalized equilibrium problems and fixed point problems. Nonlinear Analysis: Theory, Methods & Applications 2009,71(9):4203–4214. 10.1016/j.na.2009.02.106
Browder FE: Convergence of approximants to fixed points of nonexpansive non-linear mappings in Banach spaces. Archive for Rational Mechanics and Analysis 1967, 24: 82–90.
Opial Z: Weak convergence of the sequence of successive approximations for nonexpansive mappings. Bulletin of the American Mathematical Society 1967, 73: 591–597. 10.1090/S0002-9904-1967-11761-0
Takahashi W, Toyoda M: Weak convergence theorems for nonexpansive mappings and monotone mappings. Journal of Optimization Theory and Applications 2003,118(2):417–428. 10.1023/A:1025407607560
Takahashi S, Takahashi W: Strong convergence theorem for a generalized equilibrium problem and a nonexpansive mapping in a Hilbert space. Nonlinear Analysis: Theory, Methods & Applications 2008,69(3):1025–1033. 10.1016/j.na.2008.02.042
Bianchi M, Schaible S: Generalized monotone bifunctions and equilibrium problems. Journal of Optimization Theory and Applications 1996,90(1):31–43. 10.1007/BF02192244
Blum E, Oettli W: From optimization and variational inequalities to equilibrium problems. The Mathematics Student 1994,63(1–4):123–145.
Combettes PL, Hirstoaga SA: Equilibrium programming in Hilbert spaces. Journal of Nonlinear and Convex Analysis 2005,6(1):117–136.
Moudafi A: Weak convergence theorems for nonexpansive mappings and equilibrium problems. Journal of Nonlinear and Convex Analysis 2008,9(1):37–43.
Wang S, Zhou H, Song J: Viscosity approximation methods for equilibrium problems and fixed point problems of nonexpansive mappings and inverse-strongly monotone mappings. Methods and Applications of Analysis 2007,14(4):405–419.
Ceng L-C, Yao J-C: A hybrid iterative scheme for mixed equilibrium problems and fixed point problems. Journal of Computational and Applied Mathematics 2008,214(1):186–201. 10.1016/j.cam.2007.02.022
Chadli O, Chbani Z, Riahi H: Equilibrium problems with generalized monotone bifunctions and applications to variational inequalities. Journal of Optimization Theory and Applications 2000,105(2):299–323. 10.1023/A:1004657817758
Brezis H: Analyse Fonctionnelle, Collection Mathématiques Appliquées pour la Maîtrise. Masson, Paris, France; 1983:xiv+234.
About this article
Cite this article
Cianciaruso, F., Marino, G., Muglia, L. et al. A Hybrid Projection Algorithm for Finding Solutions of Mixed Equilibrium Problem and Variational Inequality Problem. Fixed Point Theory Appl 2010, 383740 (2009). https://doi.org/10.1155/2010/383740
- Equilibrium Problem
- Nonexpansive Mapping
- Monotone Operator
- Lower Semicontinuous
- Variational Inequality Problem