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Hindawi Publishing Corporation Fixed Point Theory and Applications Volume 2011, Article ID 620284, 17 pages doi:10.1155/2011/620284 ResearchArticleIterativeMethodsforVariationalInequalitiesovertheIntersectionoftheFixedPointsSetofaNonexpansiveSemigroupinBanach Spaces Issa Mohamadi Department of Mathematics, Islamic Azad University, Sanandaj Branch, Sanandaj 418, Kurdistan, Iran Correspondence should be addressed to Issa Mohamadi, imohamadi@iausdj.ac.ir Received 8 November 2010; Accepted 19 November 2010 Academic Editor: Qamrul Hasan Ansari Copyright q 2011 Issa Mohamadi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This paper presents a framework ofiterativemethodsfor finding specific common fixed pointsofanonexpansive self-mappings semigroupinaBanach space. We prove, with appropriate conditions, the strong convergence to the solution of some variational inequalities. 1. Introduction Let C be a nonempty closed convex subset ofa Hilbert space H,andletF : C → H be a nonlinear map. The classical variational inequality which is denoted by VIF, C is formulated as finding x ∗ ∈ C such that Fx ∗ ,x− x ∗ ≥ 0, 1.1 for all x ∈ C. We recall that F is called η-strongly monotone, if for each x, y ∈ C, we have Fx − Fy,x − y ≥ η x − y 2 , 1.2 fora constant η>0, and also κ-Lipschitzian if for each x, y ∈ C, we have Fx − Fy ≤ κ x − y , 1.3 2 Fixed Point Theory and Applications fora constant κ>0. Existence and uniqueness of solutions are important problems ofthe VIF, C. It is known that if F is a strongly monotone and Lipschitzian mapping on C, then VIF, C has a unique solution. An important problem is how to find a solution of VIF, C.It is known that x ∗ ∈ VI F, C ⇐⇒ x ∗ P C x ∗ − λFx ∗ , 1.4 where λ>0 is an arbitrarily fixed constant and P C is the projection of H onto C.This alternative equivalence has been used to study the existence theory ofthe solution and to develop several iterative type algorithms for solving variational inequalities. But the fixed point formulation in 1.4 involves the projection P C , which may not be easy to compute, due to the complexity ofthe convex set C. So, projection methods and their variant forms can be implemented for solving variational inequalities. In order to reduce the complexity probably caused by the projection P C , Yamada 1 see also 2 introduced a hybrid steepest-descent method for solving VIF, C. His idea is stated now. Assume that C is the fixed point setofanonexpansive mapping T : H → H. Recall that T is nonexpansive if Tx − Ty ≤ x − y , ∀x, y ∈ H. 1.5 Assume that F is η-strongly monotone and κ-Lipschitzian on C. Take a fixed number μ ∈ 0, 2η/κ 2 and a sequence {λ n } in 0, 1 satisfying the following conditions: C1 lim n →∞ λ n 0, C2 ∞ n1 λ n ∞, C3 lim n →∞ λ n − λ n1 /λ 2 n1 0. Starting with an arbitrary initial guess x 0 ∈ H, generate a sequence {x n } by the following algorithm: x n1 : Tx n − λ n1 μF Tx n ,n≥ 0. 1.6 Yamada 1 proved that the sequence {x n } converges strongly to a unique solution of VIF, C. Xu and Kim 3 further considered and studied the hybrid steepest-descent algorithm 1.6. Their major contribution is that the strong convergence of 1.6 holds with condition C3 being replaced by the following condition: C3 lim n →∞ λ n − λ n1 /λ n1 0. It is clear that condition C3 is strictly weaker than condition C3, coupled with conditions C1 and C2. Moreover, C3 includes the important and natural choice {1/n} for {λ n } whereas C3 does not. For more related results, see 4, 5. Let X be aBanach space we recall that anonexpansivesemigroup is a family {Tt : t>0} of self-mappings of X satisfies the following conditions: i T0x x for x ∈ X, ii Tt sx TtTsx for t, s > 0andx ∈ X, Fixed Point Theory and Applications 3 iii lim t → 0 Ttx x for x ∈ X, iv for each t>0,Tt is nonexpansive. that is, T t x − T t y ≤ x − y , ∀x, y ∈ X. 1.7 The problem is to find some fixed point in C t>0 FixTt. For this, so many algorithms have been developed and under some restrictions partial answers have been obtained 6–11. Assume that F : X → X is a strongly monotone and Lipschitzian mapping and {Tt : t>0} is anonexpansivesemigroupof self-mappings on X. For an appropriate μ and starting from an arbitrary initial point x 0 ∈ X, we devise the following implicit, explicit, and modified iterations: x n : λ n x n 1 − λ n T t n x n − λ n μFx n , 1.8 x n1 : λ n x n 1 − λ n T t n x n − λ n μFx n , 1.9 x n1 : λ n y n 1 − λ n T t n x n , y n : 1 − μ n x n μ n T t n − F x n , 1.10 for n ≥ 1. With some appropriate assumptions, we prove the strong convergence of 1.8, 1.9,and1.10 to the unique solution ofthevariational inequality Fx ∗ ,Jx − x ∗ ≥0inC, where J is the single-valued normalized duality mapping from X into 2 X ∗ . Our main purpose is to improve some ofthe conditions and results inthe mentioned papers, especially those of Song and Xu 11. 2. Preliminaries Let S : {x ∈ X : x 1} be the unit sphere oftheBanach space X. The space X is said to have Gateaux differentiable norm or X is said to be smooth, if the limit lim t → 0 x ty − x t , 2.1 exists for each x, y ∈ S,andX is said to have a uniformly Gateaux differentiable norm if for each y ∈ S, the limit 2.1 converges uniformly for x ∈ S. Further, X is said to be uniformly smooth if the limit 2.1 exists uniformly for x, y ∈ S × S. We denote J the normalized duality mapping from X to 2 X ∗ defined by J x f ∗ : x, f ∗ x 2 f ∗ 2 , ∀x ∈ X. 2.2 where ·, · denotes the generalized duality pairing. It is well known if X is smooth then any duality mapping on X is single valued, and if X has a uniformly Gateaux differentiable norm, then the duality mapping is norm to weak ∗ uniformly continuous on bounded sets. 4 Fixed Point Theory and Applications Recall that aBanach space X is said to be strictly convex if x y 1andx / y implies x y/2 < 1. Ina strictly convex Banach space X, we have that if λx 1 − λy 1 for λ ∈ 0, 1 and x, y ∈ X, then x y. Now, we recall the concept of uniformly asymptotically regular semigroup. A continuous operator semigroup {Tt : t>0} on X is said to be uniformly asymptotically regular on X if for all h>0 and any bounded subset D of X, we have lim t →∞ sup x∈D T h T t x − T t x 0. 2.3 Thenonexpansivesemigroup {σ t x1/t t 0 Tsxds : t>0} is an example of uniformly asymptotically regular operator semigroup 11. Let μ be a continuous linear functional on l ∞ satisfying μ 1 μ1. Then, we know that μ is a mean on N if and only if inf { a n : n ∈ N } ≤ μ a ≤ sup { a n : n ∈ N } , 2.4 for every a a 1 ,a 2 , ∈ l ∞ . Sometimes, we use μ n a n instead of μa. A mean μ on N is called aBanach limit if μ n a n μ n a n1 . We know that if μ is aBanach limit, then lim inf n →∞ a n ≤ μ a ≤ lim sup n →∞ a n , 2.5 for every a a 1 ,a 2 , ∈ l ∞ .Thus,ifa n → c as n →∞, then we have μ n a n μ a c. 2.6 A discussion on these and related concepts can be found in 12. We make use ofthe following well-known results throughout the paper. Lemma 2.1 see 12, Lemma 4.5.4. Let D be a nonempty closed convex subset ofaBanach space X with a uniformly Gateaux differentiable norm, and let {y n } be a bounded sequence in X.Ifz 0 ∈ D, then μ n y n − z 0 2 min y∈D μ n y n − y 2 , 2.7 if and only if μ n y − z 0 ,J y n − z 0 ≤ 0, 2.8 for all y ∈ D. Lemma 2.2 see 13. Let {s n }, {c n }⊂R , {a n }⊂0, 1, and let {b n }⊂R be sequences such that s n1 ≤ 1 − a n s n b n c n , 2.9 Fixed Point Theory and Applications 5 for all n ≥ 0. Assume also that n≥0 |c n | < ∞. Then, the following results hold: i if b n ≤ βa n (where β ≥ 0), then {s n } is bounded, ii if we have n≥0 a n ∞, lim sup n →∞ b n a n ≤ 0, 2.10 then lim n →∞ s n 0. Lemma 2.3. Let X be a real normed linear space, and let J be the normalized duality mapping on X. Then, for any x, y ∈ X, and j ∈ J, the following inequality holds: x y 2 ≤ x 2 2 y, j x y . 2.11 In order to reduce any possible complexity in writing, we set C t>0 FixTt foranonexpansivesemigroup {Tt : t>0} and D x n x ∈ X : g x inf y∈X g y , 2.12 where gxμ n x n − x 2 , for all x ∈ X,and{x n } is a bounded sequence in X. 3. Implicit Iterative Method Recall that if J is the single-valued normalized duality mapping from aBanach space X into 2 X ∗ , a nonlinear operator F : X → X is called η-strongly monotone if for every x, y ∈ X,the following inequality holds: Fx − Fy,J x − y ≥ η x − y 2 , 3.1 fora constant η>0. The following lemma will be be used to show the convergence of 1.8 and 1.9. Lemma 3.1. Let X be aBanach space, and let J be the single-valued normalized duality mapping from X into 2 X ∗ . Assume also that F : X → X is η-strongly monotone and κ-Lipschitzian on X. Then, ψ x I x − μF x 3.2 is a contraction on X for every μ ∈ 0,η/κ 2 . 6 Fixed Point Theory and Applications Proof. By using Lemma 2.3, we have ψx − ψy 2 ≤ I − μF x − I − μF y 2 x − y μ Fy − Fx 2 ≤ x − y 2 2 μ Fy − Fx ,J x − y μ Fy − Fx ≤ x − y 2 2μ Fy − Fx,J x − y 2μ 2 Fy − Fx,J Fy − Fx ≤ x − y 2 − 2μ Fx − Fy,J x − y 2μ 2 Fy − Fx J Fy − Fx ≤ x − y 2 − 2μη x − y 2 2μ 2 Fy − Fx 2 ≤ x − y 2 − 2μη x − y 2 2μ 2 κ 2 x − y 2 ≤ 1 − 2μη 2μ 2 κ 2 x − y 2 , 3.3 Thus, we obtain ψx − ψy ≤ 1 − 2μ η − μκ 2 x − y , 3.4 and for μ ∈ 0,η/κ 2 , we have 1 − 2μη − μκ 2 ∈ 0, 1.Thatis,ψ is a contraction, and the proof is complete. Inthe following theorem, which is the main result in this section, we establish the strong convergence ofthe sequence defined by 1.8. Theorem 3.2. Let X be a real Banach space with a uniformly Gateaux differentiable norm, and let {Tt : t>0} be anonexpansivesemigroup from X into itself. Let also {x n } defined by 1.8 satisfies the following condition: C ∩ D x n / ∅. 3.5 Assume that F : X → X is η-strongly monotone and κ-Lipschitzian. Assume also that {t n } is a sequence of positive numbers that lim n →∞ t n ∞ and {λ n }⊂0, 1.Ifμ ∈ 0,η/κ 2 ,then{x n } converges strongly to some fixed point x ∗ ∈ C, which is the unique solution in C to thevariational inequality VI ∗ F, C, that is Fx ∗ ,J x − x ∗ ≥ 0, ∀x ∈ C. 3.6 Fixed Point Theory and Applications 7 Proof. We divide the proof into several steps. Step 1. We first prove the uniqueness ofthe solution to VI ∗ F, C; for this, we suppose x ∗ ,y ∗ ∈ C are two solutions of VI ∗ F, C. Thus, we have Fx ∗ ,J x ∗ − y ∗ ≤ 0, Fy ∗ ,J y ∗ − x ∗ ≤ 0. 3.7 By adding up the last two inequalities, we obtain η x ∗ − y ∗ 2 ≤ Fx ∗ − Fy ∗ ,J x ∗ − y ∗ ≤ 0, 3.8 and so, x ∗ y ∗ . Step 2. We claim that {x n } is bounded. In fact, taking a fixed x ∗ ∈ C, we have x n − x ∗ λ n x n 1 − λ n T t n x n − λ n μFx n − x ∗ ≤ λ n x n − μFx n − x ∗ 1 − λ n T t n x n − x ∗ ≤ λ n I − μF x n − I − μF x ∗ λ n I − μF x ∗ − x ∗ 1 − λ n x n − x ∗ ≤ λ n 1 − 2μ η − μκ 2 x n − x ∗ 1 − λ n x n − x ∗ λ n μ Fx ∗ ≤ 1 − λ n 1 − 1 − 2μ η − μκ 2 x n − x ∗ λ n μ Fx ∗ . 3.9 Taking γ 1 − 1 − 2μη − μκ 2 and by using induction, we obtain x n − x ∗ ≤ max x 0 − x ∗ , μ γ Fx ∗ , 3.10 therefore, {x n − x ∗ } is bounded and so is {x n }. Step 3. The sequence {x n } is sequentially compact. To prove this, we assume that theset Dx n contains some x ∗ such that Ttx ∗ x ∗ for an arbitrary t>0. So, by using Lemma 2.1 , we can obtain μ n x − x ∗ ,J x n − x ∗ ≤ 0, ∀x ∈ X. 3.11 On the other hand, for any q ∈ C, we have x n − q 2 λ n x n − q 1 − λ n T t n x n − q − μλ n Fx n ,J x n − q ≤ λ n I − μF x n − I − μF q x n − q λ n −μF q ,J x n − q 1 − λ n T t n x n − T t n q, J x n − q ≤ 1 − λ n γ x n − q 2 λ n −μF q ,J x n − q . 3.12 8 Fixed Point Theory and Applications Thus, x n − q 2 ≤ 1 γ I − μF q − q, J x n − q . 3.13 Also, we have x n − q 2 ≤ λ n I − μF x n − q, J x n − q 1 − λ n T t n x n − q, J x n − q ≤ λ n I − μF x n − q, J x n − q 1 − λ n x n − q 2 . 3.14 It follows that x n − q 2 ≤ I − μF x n − q, J x n − q . 3.15 Combining 3.11 and 3.13 together, we get μ n x n − x ∗ 2 ≤ μ n γ I − μF x ∗ − x ∗ ,J x n − x ∗ ≤ 0. 3.16 This yields μ n x n − x ∗ 0. Hence, there exists a subsequence of {x n } such as {x n k } that converges strongly to x ∗ ;thatis,{x n } is sequentially compact. Step 4. We claim that x ∗ is the solution of VI ∗ F, C. Since {x n } is bounded, for any fixed point x ∈ C, there exist a constant L>0 such that x n − x≤L. Therefore, we obtain x n − x 2 λ n I − μF x n − I − μF x ∗ ,J x n − x λ n −μFx ∗ ,J x n − x 1 − λ n T t n x n − T t n x, J x n − x λ n x ∗ − x, J x n − x ≤ 2 − γ λ n L x n − x ∗ λ n −μFx ∗ ,J x n − x x n − x 2 . 3.17 Hence, Fx ∗ ,J x n − x ≤ L 2 − γ μ x n − x ∗ . 3.18 Note that the duality mapping J is single valued X is smooth, and norm topology to weak ∗ uniformly continuous on bounded sets ofBanach space X with uniformly Gateaux differentiable norm. Therefore, Fx ∗ ,J x n k − x −→ Fx ∗ ,J x ∗ − x , 3.19 and by taking limit as n k →∞in two sides of 3.18,weobtain Fx ∗ ,J x ∗ − x ≤ 0, ∀x ∈ C. 3.20 Cosequently, x ∗ ∈ C istheuniquesolutionofVI ∗ F, C. Fixed Point Theory and Applications 9 Step 5. x n → x ∗ in norm. Indeed, we show that each cluster point ofthe sequence {x n } is equal to x ∗ . Assume that y ∗ is another strong limit point of {x n } in C. Thanks to 3.15,we have the following two inequalities: x ∗ − y ∗ 2 ≤ I − μF x ∗ − y ∗ ,J x ∗ − y ∗ , y ∗ − x ∗ 2 ≤ I − μF y ∗ − x ∗ ,J y ∗ − x ∗ . 3.21 Therefore, 2 x ∗ − y ∗ 2 ≤ I − μF x ∗ − I − μF y ∗ x ∗ − y ∗ ,J x ∗ − y ∗ ≤ 2 − γ x ∗ − y ∗ 2 . 3.22 It yields that x ∗ − y ∗ 2 0, which proves the uniqness of x ∗ .Thus,{x n } itself converges strongly to x ∗ . This completes the proof. 4. Explicit Iterative Method In this section, we will present our result ofthe strong convergence of 1.9, but first, we need to prove, with different approach, the following lemma. Lemma 4.1. Let X, {Tt : t>0},F,{λ n }, {t n },μ, and {x n } be as those in Theorem 3.2.Ifx ∗ lim n →∞ x n , and there exists a bounded sequence {y n } such that lim n →∞ T t y n − y n 0, ∀t>0. 4.1 Then, lim sup n →∞ Fx ∗ ,J x ∗ − y n ≤ 0. 4.2 Proof. By the uniqueness of x ∗ and with no loss of generality, we can choose λ n such that λ n −→ 0, T t y n − y n λ n −→ 0, 4.3 as n →∞.Letx ∗ λ n be the fixed point ofthe contraction ϕ ∗ λ n x λ n x 1 − λ n T t n x − λ n μFx, x ∈ X. 4.4 10 Fixed Point Theory and Applications Then, x ∗ λ n − y n λ n I − μF x ∗ λ n − y n 1 − λ n T t n x ∗ λ n − y n . 4.5 Now, by using Lemma 2.3, we have x ∗ λ n − y n 2 1 − λ n 2 T t n x ∗ λ n − y n 2 2λ n I − μF x ∗ λ n − y n ,J x ∗ λ n − y n ≤ 1 − λ n 2 T t n x ∗ λ n − T t n y n T t n y n − y n 2 2λ n x ∗ λ n − y n 2 2λ n −μFx ∗ λ n ,J x ∗ λ n − y n ≤ 1 λ n 2 x ∗ λ n − y n 2 T t n y n − y n 2 x ∗ λ n − y n T t n y n − y n 2λ n −μFx ∗ λ n ,J x ∗ λ n − y n . 4.6 Therefore, μFx ∗ λ n ,J x ∗ λ n − y n ≤ λ n 2 x ∗ λ n − y n 2 T t n y n − y n 2λ n 2 x ∗ λ n − y n T t n y n − y n . 4.7 Because {y n }, {Tt n y n } and {x ∗ λ n } are bounded, from 4.3 and 4.7, we conclude that lim sup n →∞ μFx ∗ λ n ,J x ∗ λ n − y n ≤ 0. 4.8 Moreover, we have μFx ∗ λ n ,J x ∗ λ n − y n x ∗ − I − μF x ∗ λ n ,J x ∗ − y n x ∗ − I − μF x ∗ λ n ,J x ∗ λ n − y n −J x ∗ − y n x ∗ λ n − x ∗ ,J x ∗ λ n − y n . 4.9 By Theorem 3.2, x ∗ λ n → x ∗ ,asn →∞. So, using the boundedness of {y n },weget x ∗ λ n − x ∗ ,J x ∗ λ n − y n −→ 0,n−→ ∞ . 4.10 On the other hand, noticing that the sequence {x ∗ λ n − y n } is bounded and the duality mapping J is single-valued and norm to weak ∗ uniformly continuous on bounded subsets of X, we conclude that x ∗ − I − μF x ∗ λ n ,J x ∗ λ n − y n − J x ∗ − y n −→ 0,n−→ ∞ . 4.11 [...]... 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Taking an λn γ, bn 2μλn Fx∗ , J x∗ −xn 1 , and cn 0 and using Lemma 4.1 together with Lemma 2.2 lead to limn → ∞ xn 1 − x∗ 2 0, that is, xn → x∗ in norm This completes the proof Corollary 4.3 Let X be a real reflexive strictly convex Banach space with a uniformly Gateaux differentiable norm Let also {T t : t > 0} be anonexpansivesemigroup from X into itself such that C t>0 Fix T t / ∅ Assume that . Inequalities over the Intersection of the Fixed Points Set of a Nonexpansive Semigroup in Banach Spaces Issa Mohamadi Department of Mathematics, Islamic Azad University, Sanandaj Branch, Sanandaj 418,. Yokohama Publishers, Yokohama, Japan, 2002. 13 P E. Maing ´ e, “Approximation methods for common fixed points of nonexpansive mappings in Hilbert spaces,” Journal of Mathematical Analysis and Applications,. Hindawi Publishing Corporation Fixed Point Theory and Applications Volume 2011, Article ID 620284, 17 pages doi:10.1155/2011/620284 Research Article Iterative Methods for Variational Inequalities over