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Iterative methods for mixed equilibrium problems and strictly pseudocontractive mappings

Abstract

In this paper, we introduce new implicit and explicit iterative schemes for finding a common element of the set of solutions of the mixed equilibrium problem and the set of fixed points of a k-strictly pseudocontractive non-self mapping in Hilbert spaces. We establish results of the strong convergence of the sequences generated by the proposed schemes to a common point of two sets, which is a solution of a certain variational inequality. Our results extend and improve the corresponding results given by many authors recently in this area.

MSC:47H05, 47H06, 47H09, 47H10, 47J25, 47J05, 49M05.

1 Introduction

Let H be a real Hilbert space with inner product , and induced norm . Let C be a nonempty closed convex subset of H and S:CC be a self-mapping on C. We denote by F(S) the set of fixed points of S, that is, F(S):={xC:Sx=x}.

Let Θ be a bifunction of C×C into and φ:CR be a function, where is the set of real numbers. Then we consider the following mixed equilibrium problem (for short, MEP): finding xC such that

Θ(x,y)+φ(y)φ(x)0,yC,
(1.1)

which was studied by Ceng and Yao [1] (see also [2]). The set of solutions of the MEP (1.1) is denoted by MEP(Θ,φ). We see that x being a solution of the problem (1.1) implies that xdomφ={φ(x)<}.

If φ=0, then the MEP (1.1) becomes the following equilibrium problem (for short, EP): finding xC such that

Θ(x,y)0,yC.
(1.2)

The set of solutions of the EP (1.2) is denoted by EP(Θ).

The MEP (1.1) is very general in the sense that it includes, as special cases, fixed point problems, optimization problems, variational inequality problems, minmax problems, Nash equilibrium problems in noncooperative games and others; see, e.g., [1, 35].

The class of pseudocontractive mappings is one of the most important classes of mappings among nonlinear mappings. Recently, many authors have devoted their studies to the problems of finding fixed points for pseudocontractive mappings; see, for example, [69] and the references therein. We recall that a mapping S:CH is said to be k-strictly pseudocontractive if there exists a constant k[0,1) such that

S x S y 2 x y 2 +k ( I S ) x ( I S ) y 2 ,x,yC.

Note that the class of k-strictly pseudocontractive mappings includes the class of nonexpansive mappings as a subclass. That is, S is nonexpansive (i.e., SxSyxy, x,yC) if and only if S is 0-strictly pseudocontractive. The mapping S is also said to be pseudocontractive if k=1, and S is said to be strongly pseudocontractive if there exists a constant λ(0,1) such that SλI is pseudocontractive. Clearly, the class of k-strictly pseudocontractive mappings falls into the one between classes of nonexpansive mappings and pseudocontractive mappings. Also, we remark that the class of strongly pseudocontractive mappings is independent of the class of k-strictly pseudocontractive mappings (see [10, 11]).

Recently, in order to study the EP (1.2) coupled with the fixed point problem, many authors have introduced some iterative schemes for finding a common element of the set of solutions of the EP (1.2) and the set of fixed points of a countable family of nonexpansive mappings or strictly pseudocontractive mappings; see [1214] and the references therein.

On the other hand, in 2001 Yamada [15] introduced the hybrid iterative method for the nonexpansive mapping to solve a variational inequality related to a Lipschitzian and strongly monotone operator. Since then, by using the ideas of Marino and Xu [16], Tien [17, 18] and Ceng et al. [19] provided the general iterative schemes for finding a fixed point of the nonexpansive mapping, which is a solution of a certain variational inequality related to a Lipschitzian and strongly monotone operator. Cho et al. [7] and Jung [8, 20] gave the general iterative schemes for finding a fixed point of the k-strictly pseudocontractive mapping, which is a solution of a certain variational inequality.

Inspired and motivated by the above mentioned recent works, in this paper, we introduce new implicit and explicit iterative schemes for finding a common element of the set of the solutions of the MEP (1.1) and the set of fixed points of a k-strictly pseudocontractive mapping. Then we establish results of the strong convergence of the sequences generated by the proposed schemes to a common point of two sets, which is a solution of a certain variational inequality. Our results extend and improve the recent well-known results in this area.

2 Preliminaries and lemmas

Let H be a real Hilbert space, and let C be a nonempty closed convex subset of H. In the following, we write x n x to indicate that the sequence { x n } converges weakly to x. x n x implies that { x n } converges strongly to x.

Recall that the mapping V:HH is said to be l-Lipschitzian if

VxVylxy,x,yH,

and that the nonlinear operator F:HH is said to be ρ-Lipschitzian and η-strongly monotone, where ρ>0 and η>0 are constants, if

FxFyρxy

and

FxFy,xyη x y 2 ,x,yH.

In a real Hilbert space H, we have

x y 2 = x 2 + y 2 2x,y,
(2.1)

for all x,yH and λR. For every point xH, there exists a unique nearest point in C, denoted by P C x, such that

x P C xxy

for all yC. P C is called the metric projection of H onto C. It is well known that P C is nonexpansive and P C is characterized by the property

u= P C xxu,uy0,xH,yC.
(2.2)

It is also well known that H satisfies the Opial condition; that is, for any sequence { x n } with x n x, the inequality

lim inf n x n x< lim inf n x n y

holds for every yH with yx.

For solving the equilibrium problem for a bifunction Θ:C×CR, let us assume that Θ and φ satisfy the following conditions:

(A1) Θ(x,x)=0 for all xC;

(A2) Θ is monotone, that is, Θ(x,y)+Θ(y,x)0 for all x,yC;

(A3) for each x,y,zC,

lim t 0 Θ ( t z + ( 1 t ) x , y ) Θ(x,y);

(A4) for each xC, yΘ(x,y) is convex and lower semicontinuous;

(A5) for each yC, xΘ(x,y) is weakly upper semicontinuous;

(B1) for each xH and r>0, there exist a bounded subset D x C and y x C such that for any zC D x ,

Θ(z, y x )+φ( y x )φ(z)+ 1 r y x z,zx<0;

(B2) C is a bounded set.

The following lemmas were given in [3, 21].

Lemma 2.1 [3]

Let C be a nonempty closed convex subset of H and Θ be a bifunction of C×C into satisfying (A1)-(A4). Let r>0 and xH. Then there exists zC such that

Θ(z,y)+ 1 r yz,zx0,yC.

Lemma 2.2 [21]

Let C be a nonempty closed convex subset of H. Let Θ be a bifunction from C×C to satisfying (A1)-(A5) and φ:CR be a proper lower semicontinuous and convex function. For r>0 and xH, define a mapping T r :HC as follows:

T r x= { z C : Θ ( z , y ) + φ ( y ) φ ( z ) + 1 r y z , z x 0 , y C }

for all xH. Assume that either (B1) or (B2) holds. Then the following hold:

  1. (1)

    for each xH, T r x;

  2. (2)

    T r is single-valued;

  3. (3)

    T r is firmly nonexpansive; that is, for any x,yH,

    T r x T r y 2 T r x T r y,xy;
  4. (4)

    F( T r )=MEP(Θ,φ);

  5. (5)

    MEP(Θ,φ) is closed and convex.

We need the following lemmas for the proof of our main results.

Lemma 2.3 [22]

Let H be a Hilbert space, C be a closed convex subset of H. If S is a k-strictly pseudocontractive mapping on C, then the fixed point set F(S) is closed convex, so that the projection P F ( S ) is well defined.

Lemma 2.4 [22]

Let H be a real Hilbert space and C be a closed convex subset of H. Let S:CH be a k-strictly pseudocontractive mapping with F(S). Then F( P C S)=F(S).

Lemma 2.5 [22]

Let H be a real Hilbert space, C be a closed convex subset of H, and S:CH be a k-strictly pseudocontractive mapping. Define a mapping T:CH by Tx=λx+(1λ)Sx for all xC. Then as λ[k,1), T is a nonexpansive mapping such that F(T)=F(S).

Lemma 2.6 [23]

Let { s n } be a sequence of non-negative real numbers satisfying

s n + 1 (1 ξ n ) s n + ξ n δ n ,n1,

where { ξ n } and { δ n } satisfy the following conditions:

  1. (i)

    { ξ n }[0,1] and n = 1 ξ n =,

  2. (ii)

    lim sup n δ n 0 or n = 1 ξ n δ n <.

Then lim n s n =0.

Lemma 2.7 [24]

Let { x n } and { z n } be bounded sequences in a real Banach space E and { γ n } be a sequence in [0,1] which satisfies the following condition:

0< lim inf n γ n lim sup n γ n <1.

Suppose that x n + 1 = γ n x n +(1 γ n ) z n for all n1 and

lim sup n ( z n + 1 z n x n + 1 x n ) 0.

Then lim n z n x n =0.

Lemma 2.8 In a real Hilbert space H, the following inequality holds:

x + y 2 x 2 +2y,x+y,x,yH.

The following lemma can be easily proven, and therefore, we omit the proof.

Lemma 2.9 Let V:HH be an l-Lipschitzian mapping with a constant l0, and F:HH be a ρ-Lipschitzian and η-strongly monotone operator with constants ρ,η>0. Then for 0γl<μη,

( μ F γ V ) x ( μ F γ V ) y , x y (μηγl) x y 2 ,x,yC.

That is, μFγV is strongly monotone with a constant μηγl.

Finally, the following lemma is an improvement of Lemma 2.9 in [20] (see also [15]).

Lemma 2.10 Let H be a real Hilbert space H. Let F:HH be a ρ-Lipschizian and η-strongly monotone operator with 0<ηρ. Let 0<μ< 2 η ρ 2 and 0<t<ς1. Then S:=ςItμF:HH is a contraction with a contractive constant ςtτ, where τ=1 1 μ ( 2 η μ ρ 2 ) .

Proof First, we show that IμF is strictly contractive. In fact, by applying the ρ-Lipschitz continuity and η-strongly monotonicity of F, we obtain for x,yH,

( I μ F ) x ( I μ F ) y 2 = ( x y ) μ ( F x F y ) 2 = x y 2 2 μ F x F y , x y + μ 2 F x F y 2 x y 2 2 μ η x y 2 + μ 2 ρ 2 x y 2 = ( 1 μ ( 2 η μ ρ 2 ) ) x y 2 ,

and so

( I μ F ) x ( I μ F ) y 1 μ ( 2 η μ ρ 2 ) xy.
(2.3)

Now, noting that S:=ςItμF=(ςt)It(μFI), by (2.3) we have for x,yH,

S x S y = ( ς t ) ( x y ) t ( ( μ F I ) x ( μ F I ) y ) ( ς t ) x y + t ( μ F I ) x ( μ F I ) y ( ς t ) x y + t 1 μ ( 2 η μ ρ 2 ) x y = ( ς t ( 1 1 μ ( 2 η μ ρ 2 ) ) ) x y = ( ς t τ ) x y .

Hence, S is a contraction with a contractive constant ςtτ. □

3 Main results

Let H be a real Hilbert space, and let C be a nonempty closed convex subset of H. Let V:HH be an l-Lipschitzian mapping with a constant l>0, and F:HH be a ρ-Lipschitzian and η-strongly monotone operator with 0<ηρ. Let 0<μ< 2 η ρ 2 and 0<γl<τ, where τ=1 1 μ ( 2 η μ ρ 2 ) . Let { T r n } be a sequence of mappings defined as in Lemma 2.2 and S:CH be a k-strictly pseudocontractive mapping. Define a mapping S n :CH by S n x= β n x+(1 β n )Sx, xC, where β n [k,1). Then, by Lemma 2.5, S n is nonexpansive.

Consider the following mapping Q n on H defined by

Q n x= α n γVx+(I α n μF) S n T r n x,xH,n1,

where α n (0,1). By Lemmas 2.2 and 2.10, we have

Q n x Q n y α n γ V x V y + ( I α n μ F ) S n T r n x ( I α n μ F ) S n T r n y α n γ l x y + ( 1 α n τ ) x y = ( 1 α n ( τ γ l ) ) x y .

Since 0<1 α n (τγl)<1, Q n is a contraction. Therefore, by the Banach contraction principle, Q n has a unique fixed point x n H, which uniquely solves the fixed point equation

x n = α n γV x n +(I α n μF) S n T r n x n .

Now, we prove the convergence of the sequence { x n } and show the existence of the qMEP(Θ,φ)F(S), which solves the variational inequality

( μ F γ V ) q , p q 0,pMEP(Θ,φ)F(S).
(3.1)

Equivalently, q= P MEP ( Θ , φ ) F ( S ) (IμF+γV)q.

Theorem 3.1 Let C be a nonempty closed convex subset of a real Hilbert space H and Θ be a bifunction from C×CR satisfying (A1)-(A5). Let S:CH be a k-strictly pseudocontractive non-self mapping such that F(S)MEP(Θ,φ). Let F:HH be a ρ-Lipschitzian and η-strongly monotone operator with 0<ηρ. Let V:HH be an l-Lipschitzian mapping with a constant l>0. Let 0<μ< 2 η ρ 2 and 0<γl<τ, where τ=1 1 μ ( 2 η μ ρ 2 ) . Assume that either (B1) or (B2) holds. Let { x n } be a sequence generated by

{ Θ ( u n , y ) + φ ( y ) φ ( u n ) + 1 r n y u n , u n x n 0 , y C , y n = β n u n + ( 1 β n ) S u n , x n = α n γ V x n + ( I α n μ F ) y n , n 1 ,
(3.2)

where u n = T r n x n , y n = S n u n , and { r n }(0,) satisfying lim inf n r n >0. If { α n } and { β n } satisfy the following conditions:

  1. (i)

    { α n }(0,1), lim n α n =0;

  2. (ii)

    0k β n λ<1 and lim n β n =λ,

then { x n } converges strongly to a point qF(S)MEP(Θ,φ), which solves the variational inequality (3.1).

Proof Note that from the condition (i), without loss of generality, we assume that α n τ<1 for n1.

First, we can show easily the uniqueness of a solution of the variational inequality (3.1). In fact, noting that 0γl<τ and μητρη, it follows from Lemma 2.9 that

( μ F γ V ) x ( μ F γ V ) y , x y (μηγl) x y 2 .

That is, μFγV is strongly monotone for 0γl<τμη. So, the variational inequality (3.1) has only one solution. In what follows, we use qF(S)MEP(Θ,φ) to denote the unique solution of the variational inequality (3.1).

Now, take pF(S)MEP(Θ,φ). Since u n = T r n x n and p= T r n p, from Lemma 2.2, we know that

u n p x n p,n1.

Moreover, from S n p=p, it follows that

y n p= S n u n S n p u n p x n p.
(3.3)

Thus, we have

x n p = α n ( γ V x n μ F p ) + ( I α n μ F ) y n ( I α n μ F ) p ( 1 α n τ ) y n p + α n ( γ l x n p + γ V p μ F p ) ( 1 α n ( τ γ l ) ) x n p + α n γ V p μ F p .

This implies that x n p γ V p μ F p τ γ l . Hence, { x n } is bounded, and we also obtain that { u n }, { y n } and {V x n } are bounded. We note that

u n y n u n x n + x n y n = u n x n + α n γ V x n μ F y n .
(3.4)

Using Lemma 2.2, we obtain

u n p 2 = T r n x n T r n p 2 x n p , u n p = 1 2 ( x n p 2 + u n p 2 x n u n 2 ) ,

and so

u n p 2 x n p 2 x n u n 2 .
(3.5)

Then, from Lemma 2.8, (3.3) and (3.5), we have

x n p 2 = α n ( γ V x n μ F p ) + ( I α n μ F ) y n ( I α n μ F ) p 2 ( 1 α n τ ) 2 y n p 2 + 2 α n γ V x n μ F p , x n p ( 1 α n τ ) 2 u n p 2 + 2 α n γ V x n V p , x n p + 2 α n γ V p μ F p x n p ( 1 α n τ ) 2 ( x n p 2 x n u n 2 ) + 2 α n γ l x n p 2 + 2 α n γ V p μ F p x n p = ( 1 2 α n ( τ γ l ) + ( α n τ ) 2 ) x n p 2 ( 1 α n τ ) 2 x n u n 2 + 2 α n γ V p μ F p x n p x n p 2 + α n 2 τ 2 x n p 2 ( 1 α n τ ) 2 x n u n 2 + 2 α n γ V p μ F p x n p ,

and hence

( 1 α n τ ) 2 x n u n 2 α n 2 τ 2 x n p 2 +2 α n γVpμFp x n p.

Since α n 0, it follows that

lim n x n u n =0.

From (3.4), we know that

lim n u n y n =0.
(3.6)

Define T:CH by Tx=λx+(1λ)Sx. Then by Lemma 2.5, T is nonexpansive with F(T)=F(S). Notice that

T u n u n T u n y n + y n u n | λ β n | u n S u n + y n u n .

By (3.6) and β n λ, we obtain

lim n T u n u n =0.

Consider a subsequence { u n i } of { u n }. Since { u n } is bounded, there exists a subsequence { u n i j } of { u n i } which converges weakly to q.

Next, we show that qF(S)MEP(Θ,φ). Without loss of generality, we can assume that u n i q. Since C is closed and convex, C is weakly closed. So, we have qC. Let us show qF(T). Assume that qF(T). Since u n i q and qTq, it follows from the Opial condition that

lim inf i u n i q < lim inf i u n i T q lim inf i ( u n i T u n i + T u n i T q ) lim inf i u n i q ,

which is a contradiction. So, we get qF(T), and hence qF(S).

We shall show that qMEP(Θ,φ). Since u n = T r n x n , for any yC, we have

Θ( u n ,y)+φ(y)φ( u n )+ 1 r n y u n , u n x n 0.

It follows from (A2) that

φ(y)φ( u n )+ 1 r n y u n , u n x n Θ(y, u n ).

Replacing n by n i , we have

φ(y)φ( u n i )+ 1 r n i y u n i , u n i x n i Θ(y, u n i ).

Since u n i x n i r n i 0 and u n i q, it follows from (A4) that

0φ(y)+φ(q)+Θ(y,q),yC.

Put z t =ty+(1t)q for all t(0,1] and yC. Then we have z t C and

φ( z t )+φ(q)+Θ( z t ,q)0.
(3.7)

By (A1), (A4) and (3.7), we have

0 = Θ ( z t , z t ) + φ ( z t ) φ ( z t ) t Θ ( z t , y ) + ( 1 t ) Θ ( z t , q ) + t φ ( y ) + ( 1 t ) φ ( q ) φ ( z t ) t ( Θ ( z t , y ) + φ ( y ) φ ( z t ) ) + ( 1 t ) ( Θ ( z t , q ) + φ ( q ) φ ( z t ) ) t ( Θ ( z t , y ) + φ ( y ) φ ( z t ) ) ,

and hence

0Θ( z t ,y)+φ(y)φ( z t ).
(3.8)

Letting t0, by (A3) we have for each yC,

0Θ(q,y)+φ(y)φ(q).

This implies that qMEP(Θ,φ). Therefore, qF(S)MEP(Θ,φ).

On the other hand, we note that

x n q= α n (γV x n μFq)+(I α n μF) y n (I α n μF)q.

It follows that

x n q 2 = α n γ V x n μ F q , x n q + ( I α n μ F ) y n ( I α n μ F ) q , x n q α n γ V x n μ F q , x n q + ( I α n μ F ) y n ( I α n μ F ) q x n q α n γ V x n μ F q , x n q + ( 1 α n τ ) y n q x n q α n γ V x n μ F q , x n q + ( 1 α n τ ) x n q 2 .

Hence, we obtain

x n q 2 1 τ γ V x n μ F q , x n q = 1 τ ( γ V x n V q , x n q + γ V q μ F q , x n q ) 1 τ ( γ l x n q 2 + γ V q μ F q , x n q ) .

This implies that

x n q 2 γ V q μ F q , x n q τ γ l .

In particular, we have

x n i q 2 γ V q μ F q , x n i q τ γ l .
(3.9)

Since x n i q, it follows that x n i q as i.

Now, we show that q solves the variational inequality (3.1). Since x n = α n γV x n +(I α n μF) S n T r n x n , we have

(μFγV) x n = 1 α n ( ( I α n μ F ) x n ( I α n μ F ) S n T r n x n ) .

It follows that for pF(S)MEP(Θ,φ),

( μ F γ V ) x n , x n p = 1 α n ( I α n μ F ) x n ( I α n μ F ) S n T r n x n , x n p = 1 α n ( I S n T r n ) x n ( I S n T r n ) p , x n p + μ F x n μ F S n T r n x n , x n p μ F x n μ F S n T r n x n , x n p
(3.10)

since I S n T r n is monotone (i.e., xy,(I S n T r n )x(I S n T r n )y0 for all x,yH. This is due to the nonexpansivity of S n T r n ). Since x n y n = α n γV x n μF y n 0 as n, by replacing n in (3.10) with n i and letting i, we obtain

( μ F γ V ) q , q p = lim i ( μ F γ V ) x n i , x n i p lim i μ F x n i μ F y n i , x n i p = 0 .
(3.11)

That is, qF(S)MEP(Θ,φ) is a solution of the variational inequality (3.1).

Finally, we show that the sequence { x n } converges strongly to q. To this end, let { x n k } be another subsequence of { x n } and assume x n k q ˆ . By the same proof as the one above, we have q ˆ F(S)MEP(Θ,φ). Moreover, it follows from (3.10) that

( μ F γ V ) q , q q ˆ 0.
(3.12)

Interchanging q and q ˆ , we obtain

( μ F γ V ) q ˆ , q ˆ q 0.
(3.13)

Lemma 2.9 and adding these two inequalities (3.12) and (3.13) yield

(μηγl) q q ˆ 2 ( μ F γ V ) q ( μ F γ V ) q ˆ , q q ˆ 0.

Hence, q= q ˆ . Therefore, we conclude that x n q as n.

The variational inequality (3.1) can be rewritten as

( I μ F + γ V ) q q , q p 0,pF(S)MEP(Θ,φ).

By (2.2), this is equivalent to the fixed point equation

P F ( S ) MEP ( Θ , φ ) (IμF+γV)q=q.

 □

Now, we establish the strong convergence of an explicit iterative scheme for finding a common element of the set of solutions of a mixed equilibrium problem and the set of fixed points of a k-strictly pseudocontractive non-self mapping.

Theorem 3.2 Let C be a nonempty closed convex subset of a real Hilbert space H and Θ be a bifunction from C×CR satisfying (A1)-(A5). Let S:CH be a k-strictly pseudocontractive non-self mapping such that F(S)MEP(Θ,φ). Let F:HH be a ρ-Lipschitzian and η-strongly monotone operator with 0<ηρ. Let V:HH be an l-Lipschitzian mapping with a constant l>0. Let 0<μ< 2 η ρ 2 and 0<γl<τ, where τ=1 1 μ ( 2 η μ ρ 2 ) . Assume that either (B1) or (B2) holds. Let { x n } and { u n } be sequences generated by

{ Θ ( u n , y ) + φ ( y ) φ ( u n ) + 1 r n y u n , u n x n 0 , y C , y n = β n u n + ( 1 β n ) S u n , x n + 1 = α n γ V x n + λ n x n + ( ( 1 λ n ) I α n μ F ) y n , n 1 ,
(3.14)

where u n = T r n x n and y n = S n u n . If { α n }, { β n }, { r n } and { λ n } satisfy the following conditions:

  1. (i)

    { α n }(0,1), lim n α n =0, n = 1 α n =;

  2. (ii)

    0k β n λ<1 and lim n β n =λ, lim n | β n + 1 β n |=0;

  3. (iii)

    { r n }(0,), lim inf n r n >0, lim n | r n + 1 r n |=0;

  4. (iv)

    { λ n }(0,1) and 0< lim inf n λ n lim sup n λ n <1,

then { x n } and { u n } converge strongly to a point qF(S)MEP(Θ,φ), which solves the variational inequality (3.1).

Proof First, from the condition (i), without loss of generality, we assume that α n τ<1, 2 α n ( τ γ l ) 1 α n γ l <1 and α n (1 λ n )<1 for n1.

We divide the proof into several steps as follows.

Step 1. We show that x n pmax{ x 0 p, γ V p μ F p τ γ l } for all n0 and all pF(S)MEP(Θ,φ). Indeed, let pF(S)MEP(Θ,φ). Then from Lemma 2.10, we have

From induction, we have

x n pmax { x 1 p , γ V p μ F p τ γ l } ,n1.

Hence, { x n } is bounded. From (3.3), { u n }, { y n }, {V x n }, {S u n } and {F y n } are also bounded.

Step 2. We show that lim n x n + 1 x n =0 and lim n u n + 1 u n =0. To show this, define

x n + 1 = λ n x n +(1 λ n ) z n ,n1.

Observe that from the definition of z n ,

z n + 1 z n = x n + 2 λ n + 1 x n + 1 1 λ n + 1 x n + 1 λ n x n 1 λ n = α n + 1 γ V x n + 1 + ( ( 1 λ n + 1 ) I α n + 1 μ F ) y n + 1 1 λ n + 1 α n γ V x n + ( ( 1 λ n ) I α n μ F ) y n 1 λ n = α n + 1 1 λ n + 1 γ V x n + 1 α n 1 λ n γ V x n + y n + 1 y n + α n 1 λ n μ F y n α n + 1 1 λ n + 1 μ F y n + 1 = α n + 1 1 λ n + 1 ( γ V x n + 1 μ F y n + 1 ) + α n 1 λ n ( μ F y n γ V x n ) + y n + 1 y n .

Thus, it follows that

z n + 1 z n α n + 1 1 λ n + 1 ( γ V x n + 1 + μ F y n + 1 ) + α n 1 λ n ( μ F y n + γ V x n ) + y n + 1 y n .
(3.15)

On the one hand, we note that

y n + 1 y n = S n + 1 u n + 1 S n u n S n + 1 u n + 1 S n + 1 u n + S n + 1 u n S n u n u n + 1 u n + S n + 1 u n S n u n .
(3.16)

Noticing that

s n + 1 u n S n u n = β n + 1 u n + ( 1 β n + 1 ) S u n ( β n u n + ( 1 β n ) S u n ) | β n + 1 β n | u n S u n ,

from (3.16) we have

y n + 1 y n u n + 1 u n +| β n + 1 β n | u n S u n .
(3.17)

On the other hand, from u n + 1 = T r n + 1 x n + 1 and u n = T r n x n , we have

Θ( u n + 1 ,y)+φ(y)φ( u n + 1 )+ 1 r n + 1 y u n + 1 , u n + 1 x n + 1 0,yC
(3.18)

and

Θ( u n ,y)+φ(y)φ( u n )+ 1 r n y u n , u n x n 0,yC.
(3.19)

Putting y= u n in (3.18) and y= u n + 1 in (3.19), we obtain

Θ( u n + 1 , u n )+φ( u n )φ( u n + 1 )+ 1 r n + 1 u n u n + 1 , u n + 1 x n + 1 0

and

Θ( u n , u n + 1 )+φ( u n + 1 )φ( u n )+ 1 r n u n + 1 u n , u n x n 0.

By (A2), we have

u n + 1 u n , u n x n r n u n + 1 x n + 1 r n + 1 0,

and hence

u n + 1 u n , u n u n + 1 + u n + 1 x n r n r n + 1 ( u n + 1 x n + 1 ) 0.

Since lim inf n r n >0, we assume that there exists a real number c such that r n >c>0 for all n1. Thus, we have

u n + 1 u n 2 u n + 1 u n , x n + 1 x n + ( 1 r n r n + 1 ) ( u n + 1 x n + 1 ) u n + 1 u n { x n + 1 x n + | 1 r n r n + 1 | u n + 1 x n + 1 } ,

and hence

u n + 1 u n x n + 1 x n + 1 r n + 1 | r n + 1 r n | u n + 1 x n + 1 x n + 1 x n + 1 c | r n + 1 r n | L ,
(3.20)

where L=sup{ u n x n :n1}. Therefore, from (3.15), (3.17) and (3.20), we obtain

z n + 1 z n x n + 1 x n α n + 1 1 λ n + 1 ( γ V x n + 1 + μ F y n + 1 ) + α n 1 λ n ( μ F y n + γ V x n ) + | β n + 1 β n | u n S u n + 1 c | r n + 1 r n | L α n + 1 1 λ n + 1 ( γ V x n + 1 + μ F y n + 1 ) + α n 1 λ n ( μ F y n + γ V x n ) + ( | β n + 1 β n | + | r n + 1 r n | ) M 1 ,

where M 1 is an appropriate constant such that M 1 = L c +sup{ u n S u n :n1}. Thus, from conditions (i)-(iv), it follows that

lim sup n ( z n + 1 z n x n + 1 x n ) 0.

Hence, by Lemma 2.7, we have

lim n z n x n =0.

Consequently,

lim n x n + 1 x n = lim n (1 λ n ) z n x n =0,

and by (3.17) and (3.20),

lim n u n + 1 u n =0,and lim n y n + 1 y n =0.

Step 3. We show that lim n x n y n =0. Indeed, since

x n + 1 = α n γV x n + λ n x n + ( ( 1 λ n ) I α n μ F ) y n ,

we have

x n y n x n x n + 1 + x n + 1 y n x n x n + 1 + α n γ V x n μ F y n + λ n x n y n ,

that is,

x n y n 1 1 λ n x n x n + 1 + α n 1 λ n ( γ V x n + μ F y n ) .

So, from the conditions α n 0 and (iv) and Step 2, it follows that

lim n x n y n =0.

Step 4. We show that lim n x n u n =0 and lim n u n y n =0. Indeed, since T r n is firmly nonexpansive, for pF(S)MEP(Θ,φ), we have

u n p 2 = T r n x n T r n p 2 x n p , u n p = 1 2 ( x n p 2 + u n p 2 x n u n 2 ) ,

and hence

u n p 2 x n p 2 x n u n 2 .
(3.21)

Then, by using the convexity of 2 , we have from (3.14) and (3.21),

(3.22)

where

M n = λ n x n y n [ 2 α n ( γ V x n + μ F y n + ( 2 α n ) y n p ) + λ n x n y n ] .

By Step 3, we know that lim n M n =0. Then from (3.22), we have

( 1 α n ) x n u n 2 α n γ V x n + ( I μ F ) y n p 2 + x n p 2 x n + 1 p 2 + M n α n ( γ V x n + μ F y n + y n p ) 2 + x n x n + 1 ( x n p + x n + 1 p ) + M n .

Since α n 0 and x n x n + 1 0, we obtain

lim n x n u n =0.
(3.23)

From Step 3, we also have

u n y n u n x n + x n y n 0,as n.
(3.24)

Step 5. We show that lim n T u n u n =0, where T:CH is defined by Tx=λx+(1λ)Sx. We know that T is nonexpansive with F(T)=F(S) by Lemma 2.5. Notice that

T u n u n T u n y n + y n u n | λ β n | u n S u n + y n u n .

By (3.24) and β n λ, we obtain

lim n T u n u n =0.

Step 6. We show that

lim sup n ( μ F γ V ) q , q x n 0,

where q= P F ( S ) MEP ( Θ , φ ) (IμF+γV)q is a unique solution of the variational inequality (3.1). To show this inequality, we choose a subsequence { x n i } of { x n } such that

lim i ( μ F γ V ) q , q x n i = lim sup n ( μ F γ V ) q , q x n .

Since { u n i } is bounded, there exists a subsequence { u n i j } which converges weakly to w. Without loss of generality, we can assume that u n i w. From Step 4 and Step 5, we obtain x n i w and T u n i w. By the same argument as in the proof of Theorem 3.1, we have wF(S)MEP(Θ,φ). Since q= P F ( S ) MEP ( Θ , φ ) (IμF+γV)q, it follows that

lim sup n ( μ F γ V ) q , q x n = lim i ( μ F γ V ) q , q x n i = ( μ F γ V ) q , q w 0 .

Step 7. We show that lim n x n q=0, where q= P F ( S ) MEP ( Θ , φ ) (IμF+γV)q is a unique solution of the variational inequality (3.1). From (3.14), we know that

x n + 1 q= α n (γV x n μFq)+ λ n ( y n q)+ ( ( 1 λ n ) I α n μ F ) y n ( ( 1 λ n ) I α n μ F ) q.

Applying Lemma 2.8 and Lemma 2.10, we have

x n + 1 q 2 λ n ( x n q ) + ( ( 1 λ n ) I α n μ F ) y n ( ( 1 λ n ) I α n μ F ) q 2 + 2 α n γ V x n μ F q , x n + 1 q ( ( 1 λ n α n τ ) y n q + λ n x n q ) 2 + 2 α n γ V x n V q , x n + 1 q + 2 α n γ V q μ F q , x n + 1 q ( 1 τ α n ) 2 x n q 2 + 2 α n γ l x n q x n + 1 q + 2 α n γ V q μ F q , x n + 1 q ( 1 τ α n ) 2 x n q 2 + α n γ l ( x n q 2 + x n + 1 q 2 ) + 2 α n γ V q μ F q , x n + 1 q .

This implies that

x n + 1 q 2 1 2 τ α n + τ 2 α n 2 + α n γ l 1 α n γ l x n q 2 + 2 α n 1 α n γ l γ V q μ F q , x n + 1 q = ( 1 2 ( τ γ l ) α n 1 α n γ l ) x n q 2 + τ 2 α n 2 1 α n γ α x n q 2 + 2 α n 1 α n γ l γ V q μ F q , x n + 1 q ( 1 2 ( τ γ l ) 1 α n γ l α n ) x n q 2 + 2 ( τ γ l ) α n 1 α n γ l ( τ 2 α n 2 ( τ γ l ) M 2 + 1 τ γ l μ F q γ V q , q x n + 1 ) = ( 1 ξ n ) x n q 2 + ξ n δ n ,

where M 2 =sup{ x n q 2 :n1}, ξ n = 2 ( τ γ l ) 1 α n γ l α n and

δ n = τ 2 α n 2 ( τ γ l ) M 2 + 1 τ γ l μFqγVq,q x n + 1 .

From the condition (i) and Step 6, it is easy to see that ξ n 0, n = 0 ξ n = and lim sup n δ n 0. Hence, by Lemma 2.6, we conclude x n q as n. This completes the proof. □

Remark 3.1

  1. (1)

    Theorem 3.1 and Theorem 3.2 extend and develop Theorem 3.1 and Theorem 3.2 of Liu [12], respectively, in the following ways:

  2. (a)

    The EP (1.2) in Theorem 3.1 and Theorem 3.2 of [12] is extended to the case of the MEP (1.1).

  3. (b)

    The strongly positive bounded linear operator A in Theorem 3.1 and Theorem 3.2 of [12] is extended to the case of the ρ-Lipschitzian and η-strongly monotone operator F. In fact, from the definitions, a strongly positive bounded linear operator A with a constant γ ¯ >0 is a A-Lipschitzian and γ ¯ -strongly monotone operator.

  4. (c)

    The contractive mapping f:HH with contractive coefficient α(0,1) in Theorem 3.1 and Theorem 3.2 of [12] is extended to the case of a Lipschitzian mapping V:HH with a constant l[0,).

  5. (d)

    The condition n = 1 | α n + 1 α n |< in Theorem 3.2 of [12] is removed.

  6. (e)

    The conditions n = 1 | β n + 1 β n |< and n = 1 | r n + 1 r n |< in Theorem 3.2 of [12] are also relaxed by the conditions lim n | β n + 1 β n |=0 and lim n | r n + 1 r n |=0, respectively.

  7. (2)

    Even if C=H, S is nonexpansive, { β n }={0}, r n =1, u n = x n , Θ(x,y)=0 and φ(x)=0, x,yC, Theorem 3.1 and Theorem 3.2 improve Theorem 3.1 and Theorem 3.2 of Tian [18] and Theorem 3.1 and Theorem 3.2 of Ceng et al. [19] from the class of nonexpansive mappings to the class of k-strictly pseudocontractive mappings. In particular, Theorem 3.2 develops Theorem 3.2 of Tian [18] and Theorem 3.2 of Ceng et al. [19] by removing the condition either n = 1 | α n + 1 α n |< or lim n α n / α n + 1 =1.

  8. (3)

    Theorem 3.1 also contains Theorem 3.1 of Plubtieng and Pungaeng [13] as a special case with the nonexpansive mapping S, and { β n }={0}, and φ0.

  9. (4)

    Theorem 3.2 also includes and improves Theorem 3.3 of Plubtieng and Punpaeng [13], Theorem 3.2 of Takahashi and Takahashi [14] as well as Theorem 3.2 of Tian [17], Theorem 2.1 of Jung [8], Theorem 3.1 of Jung [20] Theorem 2.1 of Cho et al. [7] and Theorem 3.4 of Marino and Xu [16] as some special cases.

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Acknowledgements

The author would like to thank the anonymous referees for their valuable comments and suggestions, which improved the presentation of this manuscript. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012000895).

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Jung, J.S. Iterative methods for mixed equilibrium problems and strictly pseudocontractive mappings. Fixed Point Theory Appl 2012, 184 (2012). https://doi.org/10.1186/1687-1812-2012-184

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Keywords

  • mixed equilibrium problem
  • k-strictly pseudocontractive mapping
  • nonexpansive mapping
  • fixed points
  • ρ-Lipschitzian and η-strongly monotone operator
  • variational inequality