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Hindawi Publishing Corporation FixedPoint Theory and Applications Volume 2008, Article ID 134148, 17 pages doi:10.1155/2008/134148 ResearchArticleAnExtragradientApproximationMethodforEquilibriumProblemsandFixedPointProblemsofaCountableFamilyofNonexpansive Mappings Rabian Wangkeeree Department of Mathematics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand Correspondence should be addressed to Rabian Wangkeeree, rabianw@nu.ac.th Received 28 February 2008; Accepted 13 July 2008 Recommended by Huang Nanjing We introduce a new iterative scheme for finding the common element of the set of common fixed points ofnonexpansive mappings, the set of solutions ofanequilibrium problem, and the set of solutions of the variational inequality. We show that the sequence converges strongly to a common element of the above three sets under some parameters controlling conditions. Moreover, we apply our result to the problem of finding a common fixed pointofacountablefamilyofnonexpansive mappings, and the problem of finding a zero ofa monotone operator. This main theorem extends a recent result of Yao et al. 2007 and many others. Copyright q 2008 Rabian Wangkeeree. 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. 1. Introduction Let H be a real Hilbert space with inner product ·, · and norm ·,andletC be a closed convex subset of H.LetF be a bifunction of C × C into R, where R is the set of real numbers. The equilibrium problem for φ : C × C → R is to find x ∈ C such that φx, y ≥ 0 ∀y ∈ C. 1.1 The set of solutions of 1.1 is denoted by EPφ. Given a mapping T : C → H,letφx, y Tx,y − x for all x, y ∈ C. Then z ∈ EPφ if and only if Tz,y − z≥0 for all y ∈ C, that is, z is a solution of the variational inequality. Numerous problems in physics, optimization, and economics reduce to find a solution of 1.1. In 1997, Fl ˚ am and Antipin 1 introduced an iterative scheme of finding the best approximation to initial data when EPφ is nonempty and proved a strong convergence theorem. Let A : C → H be a mapping. The classical variational inequality, denoted by VIA, C, is to find x ∗ ∈ C such that Ax ∗ ,v− x ∗ ≥ 0 1.2 2 FixedPoint Theory and Applications for all v ∈ C. The variational inequality has been extensively studied in the literature. See, for example, 2, 3 and the references therein. A mapping Aof C into H is called α-inverse- strongly monotone 4, 5 if there exists a positive real number α such that Au − Av, u − v≥αAu − Av 2 1.3 for all u, v ∈ C. It is obvious that any α-inverse-strongly monotone mapping A is monotone and Lipschitz continuous. A mapping S of C into itself is called nonexpansive if Su − Sv≤u − v 1.4 for all u, v ∈ C. We denote by FS the set of fixed points of S. For finding an element of FS ∩ VIA, C, under the assumption that a set C ⊆ H is nonempty, closed, and convex, a mapping S : C → C is nonexpansiveanda mapping A : C → H is α-inverse-strongly monotone, Takahashi and Toyoda 6 introduced the following iterative scheme: x n1 α n x n 1 − α n SP C x n − λ n Ax n 1.5 for every n 0, 1, 2, ,where x 0 x ∈ C, {α n } is a sequence in 0, 1,and{λ n } is a sequence in 0, 2α. They proved that if FS ∩ VIA, C / ∅, then the sequence {x n } generated by 1.5 converges weakly to some z ∈ FS∩VIA, C. Recently, motivated by the idea of Korpelevi ˇ c’s extragradientmethod 7, Nadezhkina and Takahashi 8 introduced an iterative scheme for finding an element of FS ∩ VIA, C and the weak convergence theorem is presented. Moreover, Zeng and Yao 9 proposed some new iterative schemes for finding elements in FS ∩ VIA, C and obtained the weak convergence theorem for such schemes. Very recently, Yao et al. 10 introduced the following iterative scheme for finding an element of FS ∩VIA, C under some mild conditions. Let C be a closed convex subset ofa real Hilbert space H, A : C → H a monotone, L-Lipschitz continuous mapping, and S anonexpansive mapping of C into itself such that FS∩VIA, C / ∅. Suppose that x 1 u ∈ C and {x n }, {y n } are given by y n P C x n − λ n Ax n , x n1 α n u β n x n γ n SP C x n − λ n Ay n ∀n ∈ N, 1.6 where {α n }, {β n }, {γ n }⊆0, 1 and {λ n }⊆0, 1 satisfy some parameters controlling conditions. They proved that the sequence {x n } defined by 1.6 converges strongly to a common element of FS ∩ VIA, C. On the other hand, S. Takahashi and W. Takahashi 11 introduced an iterative scheme by the viscosity approximationmethodfor finding a common element of the set of solution 1.1 and the set of fixed points ofanonexpansive mapping in a real Hilbert space. Let S : C → C be anonexpansive mapping. Starting with arbitrary initial x 1 ∈ C, define sequences {x n } and {u n } recursively by φ u n ,y 1 r n y − u n ,u n − x n ≥ 0 ∀y ∈ C, x n1 α n f x n 1 − α n Su n ∀n ∈ N. 1.7 They proved that under certain appropriate conditions imposed on {α n } and {r n },the sequences {x n } and {u n } converge strongly to z ∈ FS ∩ EPφ, where z P FS∩EPφ fz. Rabian Wangkeeree 3 Moreover, Aoyama et al. 12 introduced an iterative scheme for finding a common fixed pointofacountablefamilyofnonexpansive mappings in Banach spaces and obtained the strong convergence theorem for such scheme. In this paper, motivated by Yao et al. 10, S. Takahashi and W. Takahashi 11 and Aoyama et al. 12, we introduce a new extragradientmethod 4.2 which is mixed the iterative schemes considered in 10–12 for finding a common element of the set of common fixed points ofnonexpansive mappings, the set of solutions ofanequilibrium problem, and the solution set of the classical variational inequality problem fora monotone L-Lipschitz continuous mapping in a real Hilbert space. Then, the strong convergence theorem is proved under some parameters controlling conditions. Further, we apply our result to the problem of finding a common fixed pointofacountablefamilyofnonexpansive mappings, and the problem of finding a zero ofa monotone operator. The results obtained in this paper improve and extend the recent ones announced by Yao et al. results 10 and many others. 2. Preliminaries Let H be a real Hilbert space with norm · and inner product ·, · and let C be a closed convex subset of H. For every point x ∈ H, there exists a unique nearest point in C, denoted by P C x, such that x − P C x ≤x − y∀y ∈ C. 2.1 P C is called the metric projection of H onto C. It is well known that P C is anonexpansive mapping of H onto C and satisfies x − y, P C x − P C y ≥ P C x − P C y 2 2.2 for every x, y ∈ H. Moreover, P C x is characterized by the following properties: P C x ∈ C and x − P C x, y − P C x ≤ 0, 2.3 x − y 2 ≥ x − P C x 2 y − P C x 2 2.4 for all x ∈ H, y ∈ C. For more details, see 13. It is easy to see that the following is true: u ∈ VIA, C ⇐⇒ u P C u − λAu,λ>0. 2.5 A set-valued mapping T : H → 2 H is called monotone if for all x, y ∈ H, f ∈ Tx, and g ∈ Ty imply x − y, f − g≥0. A monotone mapping T : H → 2 H is maximal if the graph of GT of T is not properly contained in the graph of any other monotone mapping. It is known that a monotone mapping T is maximal if and only if for x, f ∈ H × H, x − y, f − g≥0 for every y, g ∈ GT implies f ∈ Tx.LetB be a monotone map of C into H, L-Lipschitz continuous mapping and let N C v be the normal cone to C at v ∈ C,thatis,N C v {w ∈ H : u − v, w≥0 for all u ∈ C}. Define Tv ⎧ ⎨ ⎩ Bv N C v, v ∈ C; ∅,v / ∈ C. 2.6 Then T is the maximal monotone and 0 ∈ Tv if and only if v ∈ VIC, B;see14. 4 FixedPoint Theory and Applications The following lemmas will be useful for proving the convergence result of this paper. Lemma 2.1 see 15. Let E, ·, · be an inner product space. Then for all x, y, z ∈ E and α, β, γ ∈ 0, 1 with α β γ 1,one has αx βy γz 2 αx 2 βy 2 γz 2 − αβx − y 2 − αγx − z 2 − βγy − z 2 . 2.7 Lemma 2.2 see 16. Let {x n } and {z n } be bounded sequences in a Banach space E and let {β n } be a sequence in 0, 1 with 0 < lim inf n→∞ β n ≤ lim sup n→∞ β n < 1. Suppose x n1 1 − β n z n β n x n for all integers n ≥ 1 and lim sup n→∞ z n1 − z n −x n1 − x n ≤ 0. Then, lim n→∞ z n − x n 0. Lemma 2.3 see 17. Assume {a n } is a sequence of nonnegative real numbers such that a n1 ≤ 1 − α n a n δ n ,n≥ 1, 2.8 where {α n } is a sequence in 0, 1 and {δ n } is a sequence in R suchthat i ∞ n1 α n ∞ and ii lim sup n→∞ δ n /α n ≤ 0 or ∞ n1 |δ n | < ∞. Then lim n→∞ a n 0. Lemma 2.4 see 12, Lemma 3.2. Let C be a nonempty closed subset ofa Banach space and let {S n } be a sequence of mappings of C into itself. Suppose that ∞ n1 sup{S n1 z− S n z : z ∈ C} < ∞. Then, for each y ∈ C, {S n y} converges strongly to some pointof C. Moreover, let S be a mapping of C into itself defined by Sy lim n→∞ S n y ∀y ∈ C. 2.9 Then lim n→∞ sup{Sz − S n z : z ∈ C} 0. For solving the equilibrium problem fora bifunction φ : C × C → R, let us assume that φ satisfies the following conditions: A1 φx, x0 for all x ∈ C; A2 φ is monotone, that is, φx, yφy, x ≤ 0 for all x, y ∈ C; A3 for each x, y, z ∈ C, lim t→0 φtz 1 − tx, y ≤ φx, y; A4 for each x ∈ C, y → φx, y is convex and lower semicontinuous. The following lemma appears implicitly in 18. Lemma 2.5 see 18. Let C be a nonempty closed convex subset of H and let φ be a bifunction of C × C into R satisfying (A1)–(A4). Let r>0 and x ∈ H. Then, there exists z ∈ C such that φz, y 1 r y − z, z − x≥0 ∀y ∈ C. 2.10 The following lemma was also given in 1. Rabian Wangkeeree 5 Lemma 2.6 see 1. Assume that φ : C × C → R satisfies (A1)–(A4). For r>0 and x ∈ H, define a mapping T r : H → C as follows: T r x z ∈ C : φz, y 1 r y − z, z − x≥0 ∀y ∈ C 2.11 for all z ∈ H. Then, the following hold: i T r is single-valued; ii T r is firmly nonexpansive, that is, for any x, y ∈ H, T r x − T r y 2 ≤T r x − T r y, x − y; iii FT r EPφ; iv EPφ is closed and convex. 3. Main results In this section, we prove a strong convergence theorem. Theorem 3.1. Let C be a closed convex subset ofa real Hilbert space H.Letφ be a bifunction from C× C to R satisfying (A1)–(A4), A : C → H a monotone L-Lipschitz continuous mapping and let {S n } be a sequence ofnonexpansive mappings of C into itself such that ∩ ∞ n1 FS n ∩ VIA, C ∩ EPφ / ∅. Let the sequences {x n }, {u n }, and {y n } be generated by x 1 x ∈ C chosen arbitrarily, φ u n ,y 1 r n y − u n ,u n − x n ≥ 0 ∀y ∈ C, y n P C u n − λ n Au n , x n1 α n f x n β n x n γ n S n P C u n − λ n Ay n ∀n ≥ 1, 3.1 where {α n }, {β n }, {γ n }⊆0, 1, {λ n }⊆0, 1, and {r n }⊆0, ∞ satisfy the following conditions: C1 α n β n γ n 1, C2 lim n→∞ α n 0, ∞ n1 α n ∞, C3 0 < lim inf n→∞ β n ≤ lim sup n→∞ β n < 1, C4 lim n→∞ λ n 0, C5 lim inf n→∞ r n > 0, ∞ n1 |r n1 − r n | < ∞. Suppose that ∞ n1 sup{S n1 z − S n z : z ∈ B} < ∞ for any bounded subset B of C.Let S be a mapping of C into itself defined by Sy lim n→∞ S n y for all y ∈ C and suppose that FS∩ ∞ n1 FS n . Then the sequences {x n }, {u n }, and {y n } converge strongly to the same point q ∈∩ ∞ n1 FS n ∩ VIA, C ∩ EPφ,whereq P ∩ ∞ n1 FS n ∩VIA,C∩EPφ fq. Proof. Let Q P ∩ ∞ n1 FS n ∩VIA,C∩EPφ . Since f is a contraction with α ∈ 0, 1,weobtain Qfx − Qfy ≤ fx − fy ≤ αx − y∀x, y ∈ C. 3.2 Therefore, Qf is a contraction of C into itself, which implies that there exists a unique element q ∈ C such that q Qfq. Then we divide the proof into several steps. 6 FixedPoint Theory and Applications Step 1 {x n } is bounded. Indeed, put t n P C u n − λ n Ay n for all n ≥ 1. Let x ∗ ∈∩ ∞ n1 FS n ∩ VIA, C ∩ EPφ.From2.5 we have x ∗ P C x ∗ − λ n Ax ∗ . Also it follows from 2.4 that t n − x ∗ 2 ≤ u n − λ n Ay n − x ∗ 2 − u n − λ n Ay n − t n 2 u n − x ∗ 2 − 2λ n Ay n ,u n − x ∗ λ 2 n Ay n 2 − u n − t n 2 2λ n Ay n ,u n − t n − λ 2 n Ay n 2 u n − x ∗ 2 2λ n Ay n ,x ∗ − t n − u n − t n 2 u n − x ∗ 2 − u n − t n 2 2λ n Ay n − Ax ∗ ,x ∗ − y n 2λ n Ax ∗ ,x ∗ − y n 2λ n Ay n ,y n − t n . 3.3 Since A is monotone and x ∗ is a solution of the variational inequality problem VIA, C,we have Ay n − Ax ∗ ,x ∗ − y n ≤ 0, Ax ∗ ,x ∗ − y n ≤ 0. 3.4 This together with 3.3 implies that t n − x ∗ 2 ≤ u n − x ∗ 2 − u n − t n 2 2λ n Ay n ,y n − t n u n − x ∗ 2 − u n − y n y n − t n 2 2λ n Ay n ,y n − t n u n − x ∗ 2 − u n − y n 2 − 2 u n − y n ,y n − t n − y n − t n 2 2λ n Ay n ,y n − t n u n − x ∗ 2 − u n − y n 2 − y n − t n 2 2 u n − λ n Ay n − y n ,t n − y n . 3.5 From 2.3, we have u n − λ n Au n − y n ,t n − y n ≤ 0, 3.6 so that u n − λ n Ay n − y n ,t n − y n u n − λ n Au n − y n ,t n − y n λ n Au n − λ n Ay n ,t n − y n ≤ λ n Au n − λ n Ay n ,t n − y n ≤ λ n Au n − Ay n t n − y n ≤ λ n L u n − y n t n − y n . 3.7 Hence it follows from 3.5 and 3.7 that t n − x ∗ 2 ≤ u n − x ∗ 2 − u n − y n 2 − y n − t n 2 2λ n L u n − y n t n − y n ≤ u n − x ∗ 2 − u n − y n 2 − y n − t n 2 λ n L u n − y n 2 y n − t n 2 u n − x ∗ 2 λ n L − 1 u n − y n 2 λ n L − 1 y n − t n 2 . 3.8 Rabian Wangkeeree 7 Since λ n → 0asn →∞, there exists a positive integer N 0 such that λ n L − 1 ≤−1/3, when n ≥ N 0 . Hence it follows from 3.8 that t n − x ∗ ≤ u n − x ∗ . 3.9 Observe that u n − x ∗ T r n x n − T r n x ∗ ≤ x n − x ∗ , 3.10 and hence t n − x ∗ ≤ x n − x ∗ . 3.11 Thus, we can calculate x n1 − x ∗ α n f x n β n x n γ n S n t n − x ∗ ≤ α n f x n − x ∗ β n x n − x ∗ γ n t n − x ∗ ≤ α n f x n − f x ∗ α n f x ∗ − x ∗ β n x n − x ∗ γ n x n − x ∗ ≤ 1 − α n 1 − α x n − x ∗ α n f x ∗ − x ∗ 1 − α n 1 − α x n − x ∗ α n 1 − α f x ∗ − x ∗ 1 − α . 3.12 It follows from induction that x n − x ∗ ≤ max x 1 − x ∗ , f x ∗ − x ∗ 1 − α ,n≥ N 0 . 3.13 Therefore, {x n } is bounded. Hence, so are {t n }, {S n t n }, {Au n }, {Ay n },and{fx n }. Step 2 lim n→∞ x n1 − x n 0. Indeed, we observe that for any x, y ∈ C, I − λ n A x − I − λ n A y 2 x − y − λ n Ax − Ay 2 x − y 2 − 2λ n x − y, Ax − Ay λ 2 n Ax − Ay 2 ≤x − y 2 λ 2 n L 2 x − y 2 1 λ 2 n L 2 x − y 2 , 3.14 which implies that I − λ n A x − I − λ n A y ≤ 1 λ n L x − y. 3.15 Thus t n1 − t n ≤ P C u n1 − λ n1 Ay n1 − P C u n − λ n Ay n ≤ u n1 − λ n1 Ay n1 − u n − λ n Ay n u n1 − λ n1 Au n1 − u n − λ n1 Au n λ n1 Au n1 − Ay n1 − Au n λ n Ay n ≤ u n1 − λ n1 Au n1 − u n − λ n1 Au n λ n1 Au n1 Ay n1 Au n λ n Ay n ≤ 1 λ n1 L u n1 − u n λ n1 Au n1 Ay n1 Au n λ n Ay n . 3.16 8 FixedPoint Theory and Applications On the other hand, from u n T r n x n and u n1 T r n1 x n1 , we note that φ u n ,y 1 r n y − u n ,u n − x n ≥ 0 ∀y ∈ C , 3.17 φ u n1 ,y 1 r n1 y − u n1 ,u n1 − x n1 ≥ 0 ∀y ∈ C. 3.18 Putting y u n1 in 3.17 and y u n in 3.18, we have φ u n ,u n1 1 r n u n1 − u n ,u n − x n ≥ 0, φ u n1 ,u n 1 r n1 u n − u n1 ,u n1 − x n1 ≥ 0. 3.19 So, from A2, we have u n1 − u n , u n − x n r n − u n1 − x n1 r n1 ≥ 0 3.20 and hence u n1 − u n ,u n − u n1 u n1 − x n − r n r n1 u n1 − x n1 ≥ 0. 3.21 Without loss of generality, let us assume that there exists a real number c such that r n >c>0 for all n ∈ N. Then, we have u n1 − u n 2 ≤ u n1 − u n ,x n1 − x n 1 − r n r n1 u n1 − x n1 ≤ u n1 − u n x n1 − x n 1 − r n r n1 u n1 − x n1 3.22 and hence u n1 − u n ≤ x n1 − x n 1 r n1 r n1 − r n u n1 − x n1 ≤ x n1 − x n 1 c r n1 − r n M, 3.23 where M sup{u n − x n : n ∈ N}. It follows from 3.16 and the last inequality that t n1 − t n ≤ 1 λ n1 L x n1 − x n 1 λ n1 L 1 c r n1 − r n M λ n1 Au n1 Ay n1 Au n λ n Ay n . 3.24 Rabian Wangkeeree 9 Setting z n α n fx n γ n S n t n /1 − β n ,weobtainx n1 1− β n z n β n x n for all n ∈ N.Thus, we have z n1 − z n α n1 f x n1 γ n1 S n1 t n1 1 − β n1 − α n f x n γ n S n t n 1 − β n α n1 1 − β n1 f x n1 γ n1 1 − β n1 S n1 t n1 − S n t n − α n 1 − β n f x n − 1 − α n 1 − β n S n t n 1 − α n1 1 − β n1 S n t n ≤ α n1 1 − β n1 f x n1 − S n t n α n 1 − β n S n t n − f x n γ n1 1 − β n1 S n1 t n1 − S n t n . 3.25 It follows from 3.24 that S n1 t n1 − S n t n ≤ S n1 t n1 − S n1 t n S n1 t n − S n t n ≤ t n1 − t n S n1 t n − S n t n ≤ 1 λ n1 L x n1 − x n 1 λ n1 L 1 c r n1 − r n M λ n1 Au n1 Ay n1 Au n λ n Ay n S n1 t n − S n t n . 3.26 Combining 3.25 and 3.26, we have z n1 −z n − x n1 −x n ≤ α n1 1 − β n1 f x n1 − S n t n α n 1 − β n S n t n − f x n γ n1 1 − β n1 1λ n1 L x n1 −x n γ n1 1 − β n1 1λ n1 L 1 c |r n1 −r n |M γ n1 1 − β n1 λ n1 Au n1 Ay n1 Au n γ n1 1 − β n1 λ n Ay n γ n1 1 − β n1 S n1 t n − S n t n − x n1 − x n ≤ α n1 1 − β n1 f x n1 − S n t n α n 1 − β n S n t n − f x n γ n1 1 − β n1 λ n1 Lx n1 − x n γ n1 1 − β n1 1 λ n1 L 1 c |r n1 − r n |M γ n1 1 − β n1 λ n1 Au n1 Ay n1 Au n γ n1 1 − β n1 λ n Ay n γ n1 1 − β n1 sup S n1 t − S n t : t ∈ t n . 3.27 10 FixedPoint Theory and Applications This together with C1–C5 and lim n→∞ sup{S n1 t − S n t : t ∈{t n }} 0 implies that lim sup n→∞ z n1 − z n − x n1 − x n ≤ 0. 3.28 Hence, by Lemma 2.2,weobtainz n − x n →0asn →∞. It then follows that lim n→∞ x n1 − x n lim n→∞ 1 − β n z n − x n 0. 3.29 By 3.23 and 3.24, we also have lim n→∞ t n1 − t n lim n→∞ u n1 − u n 0. 3.30 Step 3 lim n→∞ St n − t n 0. Indeed, pick any x ∗ ∈∩ ∞ n1 FS n ∩ VIA, C ∩ EPφ,toobtain u n − x ∗ 2 T r n x n − T r n x ∗ 2 ≤ T r n x n − T r n x ∗ ,x n − x ∗ u n − x ∗ ,x n − x ∗ 1 2 u n − x ∗ 2 x n − x ∗ 2 − x n − u n 2 . 3.31 Therefore, u n − x ∗ 2 ≤x n − x ∗ 2 −x n − u n 2 .FromLemma 2.1 and 3.9, we obtain, when n ≥ N 0 ,that x n1 − x ∗ 2 α n f x n β n x n γ n S n t n − x ∗ 2 ≤ α n f x n − x ∗ 2 β n x n − x ∗ 2 γ n S n t n − x ∗ 2 ≤ α n f x n − x ∗ 2 β n x n − x ∗ 2 γ n t n − x ∗ 2 ≤ α n f x n − x ∗ 2 β n x n − x ∗ 2 γ n u n − x ∗ 2 ≤ α n f x n − x ∗ 2 β n x n − x ∗ 2 γ n x n − x ∗ 2 − x n − u n 2 ≤ α n f x n − x ∗ 2 1 − α n x n − x ∗ 2 − γ n x n − u n 2 3.32 and hence γ n x n − u n 2 ≤ α n f x n − x ∗ 2 x n − x ∗ 2 − x n1 − x ∗ 2 ≤ α n f x n − x ∗ 2 x n − x n1 x n − x ∗ x n1 − x ∗ . 3.33 It now follows from the last inequality, C1, C2, C3 and 3.29,that lim n→∞ x n − u n 0. 3.34 Noting that y n − x n P C u n − λ n Au n − x n ≤ u n − x n λ n Au n −→ 0asn −→ ∞ , y n − t n P C u n − λ n Au n − P C u n − λ n Ay n ≤ λ n Au n − Ay n −→ 0asn −→ ∞ . 3.35 [...]... 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Journal of Optimization Theory and Applications, vol 124, no 3, pp 725–738, 2005 4 F E Browder and W V Petryshyn, “Construction of fixed points of nonlinear mappings in Hilbert space,” Journal of Mathematical Analysis and Applications, vol 20, no 2, pp 197–228, 1967 5 F Liu and M Z Nashed, “Regularization of nonlinear ill-posed variational inequalities and convergence rates,” Set-Valued Analysis, vol 6,... valuable suggestions and comments, and pointing out a major error in the original version of this paper This research was partially supported by the Commission on Higher Education References 1 S D Fl˚ m andA S Antipin, Equilibrium programming using proximal-like algorithms,” a Mathematical Programming, vol 78, no 1, pp 29–41, 1997 2 J.-C Yao and O Chadli, “Pseudomonotone complementarity problems and. .. and variational inequalities,” in Handbook of Generalized Convexity and Generalized Monotonicity, N Hadjisavvas, S Komlosi, and S ´ Schaible, Eds., vol 76 of Nonconvex Optimization and Its Applications, pp 501–558, Springer, New York, NY, USA, 2005 3 L C Zeng, S Schaible, and J C Yao, “Iterative algorithm for generalized set-valued strongly nonlinear mixed variational-like inequalities,” Journal of Optimization... ∞ for any bounded subset B of C n by using convex combination ofa general sequence {Tk } ofnonexpansive mappings with a common fixed point Corollary 3.2 Let C be a closed convex subset ofa real Hilbert space H Let φ be a bifunction from C × C to R satisfying (A1 )– (A4 ), A : C → H a monotone, L-Lipschitz continuous mapping and let 14 FixedPoint Theory and Applications k {βn } be afamilyof nonnegative... the graph of any other monotone operator Let I denote the identity operator on H and let S : H → 2H be a maximal monotone operator Then we can define, for each r > 0, anonexpansive single-valued I rS −1 It is called the resolvent or the proximal mapping of mapping Jr : H → H by Jr I − Jr /r We know that Ar x ∈ SJr x S We also define the Yosida approximation Ar by Ar and Ar x ≤ inf{ y : y ∈ Sx} for all . K. Aoyama, Y. Kimura, W. Takahashi, and M. Toyoda, Approximation of common fixed points of a countable family of nonexpansive mappings in a Banach space,” Nonlinear Analysis: Theory, Methods &. for Equilibrium Problems and Fixed Point Problems of a Countable Family of Nonexpansive Mappings Rabian Wangkeeree Department of Mathematics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand Correspondence. point problems and variational inequality problems, ” Journal of Inequalities and Applications, vol. 2007, Article ID 38752, 12 pages, 2007. 11 S. Takahashi and W. Takahashi, “Viscosity approximation