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An iterative algorithm to approximate a common element of the set of common fixed points for a finite family of strict pseudo-contractions and of the set of solutions for a modified system of variational inequalities

Abstract

In this paper, we introduce a new iterative algorithm for finding a common element of the set of fixed points of a finite family of κ i -strictly pseudo-contractive mappings and the set of solutions of new variational inequalities problems in Hilbert space. By using our main results, we obtain an interesting theorem involving a finite family of κ-strictly pseudo-contractive mappings and two sets of solutions of the variational inequalities problem.

1 Introduction

Let H be a real Hilbert space whose inner product and norm are denoted by and ,, respectively. Let C be a nonempty closed convex subset of H. A mapping S:CC is called nonexpansive if

SxSyxy,

for all x,yC.

A mapping S is called a κ-strictly pseudo-contractive mapping if there exists κ[0,1) such that

S x S y 2 x y 2 +κ ( I T ) x ( I T ) y 2 ,

for all x,yC.

It is easy to see that every noexpansive mapping is a κ-strictly pseudo-contractive mapping.

Let A:CH. The variational inequality problem is to find a point uC such that

Au,vu0
(1.1)

for all vC. The set of solutions of (1.1) is denoted by VI(C,A).

Variational inequalities were initially studied by Kinderlehrer and Stampacchia [1] and Lions and Stampacchia [2]. Such a problem has been studied by many researchers, and it is connected with a wide range of applications in industry, finance, economics, social sciences, ecology, regional, pure and applied sciences; see, e.g., [39].

A mapping A of C into H is called α-inverse-strongly monotone, see [10], if there exists a positive real number α such that

xy,AxAyα A x A y 2

for all x,yC.

Let D 1 , D 2 :CH be two mappings. In 2008, Ceng et al. [11] introduced a problem for finding ( x , z )C×C such that

{ λ 1 D 1 z + x z , x x 0 , x C , λ 2 D 2 x + z x , x z 0 , x C ,
(1.2)

which is called a system of variational inequalities where λ 1 , λ 2 >0. By a modification of (1.2), we consider the problem for finding ( x , z )C×C such that

{ x ( I λ 1 D 1 ) ( a x + ( 1 a ) z ) , x x 0 , x C , z ( I λ 2 D 2 ) x , x z 0 , x C ,
(1.3)

which is called a modification of system of variational inequalities, for every λ 1 , λ 2 >0 and a[0,1]. If a=0, (1.3) reduce to (1.2).

In 2008, Ceng et al. [11] introduce and studied a relaxed extragradient method for finding solutions of a general system of variational inequalities with inverse-strongly monotone mappings in a real Hilbert space as follows.

Theorem 1.1 Let C be a nonempty closed convex subset of a real Hilbert space H. Let the mappings A,B:CH be α-inverse-strongly monotone and β-inverse-strongly monotone, respectively. Let S:CC be a nonexpansive mapping such that F(S)Ω, where Ω is the set of fixed points of the mapping G:CC, defined by G(x)= P C ( P C (xμBx)λA P C (xμBx)), for all xC. Suppose that x 1 =uC and { x n } is generated by

{ y n = P C ( x n μ B x n ) , x n + 1 = α n u + β n x n + γ n P C ( x n λ A x n ) ,
(1.4)

where λ(0,2α), μ(0,2β) and { α n }, { β n }, { γ n } are three sequences in [0,1] such that

(i) α n + β n + γ n = 1 , n 1 , (ii) lim n α n = 0 and n = 1 α n = , (iii) 0 < lim inf n β n lim sup n β n < 1 .

Then { x n } converges strongly to x ˜ = P F ( S ) Ω u and ( x ˜ , y ˜ ) is a solution of problem (1.2), where y ˜ = P C ( x ˜ μB x ˜ ).

In the last decade, many author studied the problem for finding an element of the set of fixed points of a nonlinear mapping; see, for instance, [1214].

From the motivation of [11] and the research in the same direction, we prove a strong convergence theorem for finding a common element of the set of fixed points of a finite family of κ i -strictly pseudo-contractive mappings and the set of solutions of a modified general system of variational inequalities problems. Moreover, in the last section, we prove an interesting theorem involving the set of a finite family of κ i -strictly pseudo-contractive mappings and two sets of solutions of variational inequalities problems by using our main results.

2 Preliminaries

In this section, we collect and give some useful lemmas that will be used for our main result in the next section.

Let C be a closed convex subset of a real Hilbert space H, let P C be the metric projection of H onto C, i.e., for xH, P C x satisfies the property

x P C x= min y C xy.

It is well known that P C is a nonexpansive mapping and satisfies

xy, P C x P C y P C x P C y 2 ,x,yH.

Obviously, this immediately implies that

( x y ) ( P C x P C y ) 2 x y 2 P C x P C y 2 ,x,yH.

The following characterizes the projection P C .

Lemma 2.1 (See [15])

Given xH and yC. Then P C x=y if and only if the following inequality holds:

xy,yz0,zC.

Lemma 2.2 (See [16])

Let { s n } be a sequence of nonnegative real numbers satisfying

s n + 1 =(1 α n ) s n + α n β n ,n0,

where { α n }, { β n } satisfy the conditions

( 1 ) { α n } [ 0 , 1 ] , n = 1 α n = , ( 2 ) lim sup n β n 0 or n = 1 | α n β n | < .

Then lim n s n =0.

Lemma 2.3 (See [17])

Let { x n } and { z n } be bounded sequences in a Banach space X and let { β n } be a sequence in [0,1] with 0< lim inf n β n lim sup n β n <1. Suppose that

x n + 1 = β n x n +(1 β n ) z n

for all integer n0 and

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

Then lim n x n z n =0.

Definition 2.1 (See [18])

Let C be a nonempty convex subset of a real Hilbert space. Let { T i } i = 1 N be a finite family of κ i -strict pseudo-contractions of C into itself. For each j=1,2,,N, let α j =( α 1 j , α 2 j , α 3 j )I×I×I, where I[0,1] and α 1 j + α 2 j + α 3 j =1. Define the mapping S:CC as follows:

U 0 = I , U 1 = α 1 1 T 1 U 0 + α 2 1 U 0 + α 3 1 I , U 2 = α 1 2 T 2 U 1 + α 2 2 U 1 + α 3 2 I , U 3 = α 1 3 T 3 U 2 + α 2 3 U 2 + α 3 3 I , U N 1 = α 1 N 1 T N 1 U N 2 + α 2 N 1 U N 2 + α 3 N 1 I , S = U N = α 1 N T N U N 1 + α 2 N U N 1 + α 3 N I .
(2.1)

This mapping is called S-mapping generated by T 1 , T 2 ,, T N and α 1 , α 2 ,, α N .

Lemma 2.4 (See [18])

Let C be a nonempty closed convex subset of a real Hilbert space. Let { T i } i = 1 N be a finite family of κ-strict pseudo-contractive mappings of C into C with i = 1 N F( T i ) and κ=max{ κ i :i=1,2,,N} and let α j =( α 1 j , α 2 j , α 3 j )I×I×I, j=1,2,3,,N, where I=[0,1], α 1 j + α 2 j + α 3 j =1, α 1 j , α 3 j (κ,1) for all j=1,2,,N1 and α 1 N (κ,1], α 3 N [κ,1), α 2 j [κ,1) for all j=1,2,,N. Let S be a mapping generated by T 1 , T 2 ,, T N and α 1 , α 2 ,, α N . Then F(S)= i = 1 N F( T i ) and S is a nonexpansive mapping.

Lemma 2.5 (See [19])

Let E be a uniformly convex Banach space, C be a nonempty closed convex subset of E and let S:CC be a nonexpansive mapping. Then IS is demi-closed at zero.

Lemma 2.6 In a real Hilbert space H, the following inequality holds:

x + y 2 x 2 +2y,x+y

for all x,yH.

Lemma 2.7 Let C be a nonempty closed convex subset of a Hilbert space H and let D 1 , D 2 :CH be mappings. For every λ 1 , λ 2 >0 and a[0,1], the following statements are equivalent:

  1. (a)

    ( x , z )C×C is a solution of problem (1.3),

  2. (b)

    x is a fixed point of the mapping G:CC, i.e., x F(G), defined by

    G(x)= P C (I λ 1 D 1 ) ( a x + ( 1 a ) P C ( I λ 2 D 2 ) x ) ,

where z = P C (I λ 2 D 2 ) x .

Proof (a) (b) Let ( x , z )C×C be a solution of problem (1.3). For every λ 1 , λ 2 >0 and a[0,1], we have

{ x ( I λ 1 D 1 ) ( a x + ( 1 a ) z ) , x x 0 , x C , z ( I λ 2 D 2 ) x , x z 0 , x C .

From the properties of P C , we have

{ x = P C ( I λ 1 D 1 ) ( a x + ( 1 a ) z ) , z = P C ( I λ 2 D 2 ) x .

It implies that

x = P C (I λ 1 D 1 ) ( a x + ( 1 a ) P C ( I λ 2 D 2 ) x ) =G ( x ) .

Hence, we have x F(G), where z = P C (I λ 2 D 2 ) x .

(b) (a) Let x F(G) and z = P C (I λ 2 D 2 ) x . Then, we have

x = G ( x ) = P C ( I λ 1 D 1 ) ( a x + ( 1 a ) P C ( I λ 2 D 2 ) x ) = P C ( I λ 1 D 1 ) ( a x + ( 1 a ) z ) .

From the properties of P C , we have

{ x ( I λ 1 D 1 ) ( a x + ( 1 a ) z ) , x x 0 , x C , z ( I λ 2 D 2 ) x , x z 0 , x C .

Hence, we have ( x , z )C×C is a solution of (1.3). □

3 Main results

Theorem 3.1 Let C be a nonempty closed convex subset of a real Hilbert space H and let D 1 , D 2 :CH be d 1 , d 2 -inverse strongly monotone mappings, respectively. Define the mapping G:CC by G(x)= P C (I λ 1 D 1 )(ax+(1a) P C (I λ 2 D 2 )x) for all xC, λ 1 , λ 2 >0 and a[0,1). Let { T i } i = 1 N be a finite family of κ-strict pseudo-contractive mappings of C into C with F= i = 1 N F( T i )F(G) and κ=max{ κ i :i=1,2,,N} and let α j =( α 1 j , α 2 j , α 3 j )I×I×I, j=1,2,3,,N, where I=[0,1], α 1 j + α 2 j + α 3 j =1, α 1 j , α 3 j (κ,1) for all j=1,2,,N1 and α 1 N (κ,1], α 3 N [κ,1), α 2 j [κ,1) for all j=1,2,,N. Let S be a mapping generated by T 1 , T 2 ,, T N and α 1 , α 2 ,, α N . Suppose that x 1 ,uC and let { x n } be the sequence generated by

{ y n = P C ( I λ 2 D 2 ) x n , x n + 1 = α n u + β n x n + γ n S P C ( a x n + ( 1 a ) y n λ 1 D 1 ( a x n + ( 1 a ) y n ) ) , x n + 1 = n 1 ,
(3.1)

where λ 1 (0,2 d 1 ), λ 2 (0,2 d 2 ) and { α n }, { β n }, { γ n } are sequences in [0,1]. Assume that the following conditions hold:

(i) α n + β n + γ n = 1 , (ii) lim n α n = 0 and n = 1 α n = , (iii) 0 < lim inf n β n lim sup n β n < 1 .

Then { x n } converges strongly to x 0 = P F u and ( x 0 , y 0 ) is a solution of (1.3), where y 0 = P C (I λ 2 D 2 ) x 0 .

Proof First, we show that P C (I λ 1 D 1 ) and P C (I λ 2 D 2 ) are nonexpansive mappings for every λ 1 (0,2 d 1 ), λ 2 (0,2 d 2 ). Let x,yC. Since D 1 is d 1 -inverse strongly monotone and λ 1 <2 d 1 , we have

( I λ 1 D 1 ) x ( I λ 1 D 1 ) y 2 = x y λ 1 ( D 1 x D 1 y ) 2 = x y 2 2 λ 1 x y , D 1 x D 1 y + λ 1 2 D 1 x D 1 y 2 x y 2 2 d 1 λ 1 D 1 x D 1 y 2 + λ 1 2 D 1 x D 1 y 2 = x y 2 + λ 1 ( λ 1 2 d 1 ) D 1 x D 1 y 2 x y 2 .
(3.2)

Thus (I λ 1 D 1 ) is a nonexpansive mapping. By using the same method as (3.2), we have (I λ 2 D 2 ) is a nonexpansive mapping. Hence, P C (I λ 1 D 1 ), P C (I λ 2 D 2 ) are nonexpansive mappings. It is easy to see that the mapping G is a nonexpansive mapping. Let x F. Then we have x =S x and

x =G ( x ) = P C (I λ 1 D 1 ) ( a x + ( 1 a ) P C ( I λ 2 D 2 ) x ) .

Put w n = P C (I λ 1 D 1 )(a x n +(1a) y n ) and y = P C (I λ 2 D 2 ) x , we can rewrite (3.1) by

x n + 1 = α n u+ β n x n + γ n S w n ,n1,

and x = P C (I λ 1 D 1 )(a x +(1a) y ).

From the definition of x n , we have

x n + 1 x = α n ( u x ) + β n ( x n x ) + γ n ( S w n x ) α n u x + β n x n x + γ n w n x = α n u x + β n x n x + γ n P C ( I λ 1 D 1 ) ( a x n + ( 1 a ) y n ) P C ( I λ 1 D 1 ) ( a x + ( 1 a ) P C ( I λ 2 D 2 ) x ) α n u x + β n x n x + γ n a ( x n x ) + ( 1 a ) ( P C ( I λ 2 D 2 ) x n P C ( I λ 2 D 2 ) x ) α n u x + β n x n x + γ n ( a x n x + ( 1 a ) x n x ) = α n u x + ( 1 α n ) x n x max { u x , x 1 x } .

By induction we can conclude that x n x max{u x , x 1 x } for all nN. It implies that { x n } is bounded and so are { y n } and { w n }.

Next, we show that lim n x n + 1 x n =0.

Let

x n + 1 =(1 β n ) z n + β n x n ,
(3.3)

where z n = x n + 1 β n x n 1 β n .

Since x n + 1 β n x n = α n u+ γ n S w n and (3.3), we have

z n + 1 z n = x n + 2 β n + 1 x n + 1 1 β n + 1 x n + 1 β n x n 1 β n = α n + 1 u + γ n + 1 S w n + 1 1 β n + 1 α n u + γ n S w n 1 β n γ n + 1 S w n 1 β n + 1 + γ n + 1 S w n 1 β n + 1 = ( α n + 1 1 β n + 1 α n 1 β n ) u + γ n + 1 1 β n + 1 ( S w n + 1 S w n ) + ( γ n + 1 1 β n + 1 γ n 1 β n ) S w n = ( α n + 1 1 β n + 1 α n 1 β n ) u + γ n + 1 1 β n + 1 ( S w n + 1 S w n ) + ( α n 1 β n α n + 1 1 β n + 1 ) S w n .

It follows that

z n + 1 z n | α n + 1 1 β n + 1 α n 1 β n | u + γ n + 1 1 β n + 1 S w n + 1 S w n + | α n + 1 1 β n + 1 α n 1 β n | S w n = | α n + 1 1 β n + 1 α n 1 β n | ( u + S w n ) + γ n + 1 1 β n + 1 w n + 1 w n = | α n + 1 1 β n + 1 α n 1 β n | ( u + S w n ) + γ n + 1 1 β n + 1 P C ( I λ 1 D 1 ) ( a x n + 1 + ( 1 a ) y n + 1 ) P C ( I λ 1 D 1 ) ( a x n + ( 1 a ) y n ) | α n + 1 1 β n + 1 α n 1 β n | ( u + S w n ) + γ n + 1 1 β n + 1 a ( x n + 1 x n ) + ( 1 a ) ( y n + 1 y n ) | α n + 1 1 β n + 1 α n 1 β n | ( u + S w n ) + γ n + 1 1 β n + 1 ( a x n + 1 x n + ( 1 a ) P C ( I λ 2 D 2 ) x n + 1 P C ( I λ 2 D 2 ) x n ) | α n + 1 1 β n + 1 α n 1 β n | ( u + S w n ) + x n + 1 x n .

From conditions (ii) and (iii), we have

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

From Lemma 2.3 and (3.3) we have lim n z n x n =0. Since x n + 1 x n =(1 β n )( z n x n ), then we have

lim n x n + 1 x n =0.
(3.4)

From the definition of w n , we have

w n + 1 w n P C ( I λ 1 D 1 ) ( a x n + 1 + ( 1 a ) y n + 1 ) P C ( I λ 1 D 1 ) ( a x n + ( 1 a ) y n ) a x n + 1 x n + ( 1 a ) y n + 1 y n = a x n + 1 x n + ( 1 a ) P C ( I λ 2 D 2 ) x n + 1 P C ( I λ 2 D 2 ) x n a x n + 1 x n + ( 1 a ) x n + 1 x n = x n + 1 x n .

From (3.4), we obtain

lim n w n + 1 w n =0.
(3.5)

From the definition of x n , we have

x n + 1 x n = α n (u x n )+ γ n (S w n x n ).

From (3.4), conditions (ii) and (iii), we have

lim n S w n x n =0.
(3.6)

From the definition of y n , we have

y n + 1 y n = P C ( I λ 2 D 2 ) x n + 1 P C ( I λ 2 D 2 ) x n x n + 1 x n .
(3.7)

From (3.4) and (3.7), we derive

lim n y n + 1 y n =0.
(3.8)

From the nonexpansiveness of P C (I λ 1 D 1 ) and P C (I λ 2 D 2 ), we have

x n + 1 x 2 α n u x 2 + β n x n x 2 + γ n S w n x 2 α n u x 2 + β n x n x 2 + γ n w n x 2 = α n u x 2 + β n x n x 2 + γ n P C ( I λ 1 D 1 ) ( a x n + ( 1 a ) y n ) P C ( I λ 1 D 1 ) ( a x + ( 1 a ) y ) 2 α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) y n y 2 ) = α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) P C ( I λ 2 D 2 ) x n P C ( I λ 2 D 2 ) x 2 ) α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) ( I λ 2 D 2 ) x n ( I λ 2 D 2 ) x 2 ) = α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) ( x n x ) λ 2 ( D 2 x n D 2 x ) 2 ) = α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) ( x n x 2 2 λ 2 x n x , D 2 x n D 2 x + λ 2 2 D x n D x 2 ) ) α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) ( x n x 2 2 λ 2 d 2 D 2 x n D 2 x 2 + λ 2 2 D x n D x 2 ) ) = α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) ( x n x 2 λ 2 ( 2 d 2 λ 2 ) D 2 x n D 2 x 2 ) ) = α n u x 2 + β n x n x 2 + γ n ( x n x 2 λ 2 ( 1 a ) ( 2 d 2 λ 2 ) D 2 x n D 2 x 2 ) α n u x 2 + x n x 2 λ 2 γ n ( 1 a ) ( 2 d 2 λ 2 ) D 2 x n D 2 x 2 .

It implies that

λ 2 γ n ( 1 a ) ( 2 d 2 λ 2 ) D 2 x n D 2 x 2 α n u x 2 + x n x 2 x n + 1 x 2 α n u x 2 + ( x n x + x n + 1 x ) × x n + 1 x n .
(3.9)

From (3.4), (3.9) conditions (ii) and (iii), we have

lim n D 2 x n D 2 x =0.
(3.10)

Put h =a x +(1a) y and h n =a x n +(1a) y n . From the definition of x n , we have

x n + 1 x 2 α n u x 2 + β n x n x 2 + γ n w n x 2 = α n u x 2 + β n x n x 2 + γ n P C ( I λ 1 D 1 ) h n P C ( I λ 1 D 1 ) h 2 α n u x 2 + β n x n x 2 + γ n ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h 2 = α n u x 2 + β n x n x 2 + γ n ( h n h ) λ 1 ( D 1 h n D 1 h ) 2 = α n u x 2 + β n x n x 2 + γ n ( h n h 2 2 λ 1 h n h , D 1 h n D 1 h + λ 1 2 D 1 h n D 1 h 2 ) α n u x 2 + β n x n x 2 + γ n ( h n h 2 2 λ 1 d 1 D 1 h n D 1 h 2 + λ 1 2 D 1 h n D 1 h 2 ) = α n u x 2 + β n x n x 2 + γ n ( h n h 2 λ 1 ( 2 d 1 λ 1 ) D 1 h n D 1 h 2 ) = α n u x 2 + β n x n x 2 + γ n ( a ( x n x ) + ( 1 a ) ( y n y ) 2 λ 1 ( 2 d 1 λ 1 ) D 1 h n D 1 h 2 ) α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) P C ( I λ 2 D 2 ) x n P C ( I λ 2 D 2 ) x 2 λ 1 ( 2 d 1 λ 1 ) D 1 h n D 1 h 2 ) α n u x 2 + x n x 2 λ 1 γ n ( 2 d 1 λ 1 ) D 1 h n D 1 h 2 ,

which implies that

λ 1 γ n ( 2 d 1 λ 1 ) D 1 h n D 1 h 2 α n u x 2 + x n x 2 x n + 1 x 2 α n u x 2 + ( x n x + x n + 1 x ) × x n + 1 x n .
(3.11)

From (3.4), (3.11), conditions (ii) and (iii), we can conclude

lim n D 1 h n D 1 h =0.
(3.12)

Next, we show that

lim n S w n w n =0.
(3.13)

From the definition of y n , we have

y n y 2 = P C ( I λ 2 D 2 ) x n P C ( I λ 2 D 2 ) x 2 x n λ 2 D 2 x n ( x λ 2 D 2 x ) , y n y = 1 2 ( x n λ 2 D 2 x n ( x λ 2 D 2 x ) 2 + y n y 2 x n λ 2 D 2 x n ( x λ 2 D 2 x ) ( y n y ) 2 ) = 1 2 ( x n λ 2 D 2 x n ( x λ 2 D 2 x ) 2 + y n y 2 x n y n ( x y ) λ 2 ( D 2 x n D 2 x ) 2 ) = 1 2 ( x n λ 2 D 2 x n ( x λ 2 D 2 x ) 2 + y n y 2 x n y n ( x y ) 2 + 2 λ 2 x n y n ( x y ) , D 2 x n D 2 x λ 1 2 D 2 x n D 2 x 2 ) .

It implies that

y n y x n λ 2 D 2 x n ( x λ 2 D 2 x ) 2 x n y n ( x y ) 2 + 2 λ 2 x n y n ( x y ) , D 2 x n D 2 x λ 1 2 D 2 x n D 2 x 2 x n x 2 x n y n ( x y ) 2 + 2 λ 2 x n y n ( x y ) , D 2 x n D 2 x λ 1 2 D 2 x n D 2 x 2 .
(3.14)

From the nonexpansiveness of P C (I λ 1 D 1 ) and (3.14), we have

x n + 1 x 2 α n u x 2 + β n x n x 2 + γ n S w n x 2 α n u x 2 + β n x n x 2 + γ n w n x 2 = α n u x 2 + β n x n x 2 + γ n P C ( I λ 1 D 1 ) ( a x n + ( 1 a ) y n ) P C ( I λ 1 D 1 ) ( a x + ( 1 a ) y ) 2 α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) y n y 2 ) α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) ( x n x 2 x n y n ( x y ) 2 + 2 λ 2 x n y n ( x y ) , D 2 x n D 2 x λ 1 2 D 2 x n D 2 x 2 ) ) α n u x 2 + β n x n x 2 + γ n ( a x n x 2 + ( 1 a ) x n x 2 ( 1 a ) x n y n ( x y ) 2 + 2 λ 2 x n y n ( x y ) D 2 x n D 2 x ) α n u x 2 + x n x 2 γ n ( 1 a ) x n y n ( x y ) 2 + 2 λ 2 x n y n ( x y ) D 2 x n D 2 x .

It follows that

γ n ( 1 a ) x n y n ( x y ) 2 α n u x 2 + x n x 2 x n + 1 x 2 + 2 λ 2 x n y n ( x y ) D 2 x n D 2 x α n u x 2 + ( x n x + x n + 1 x ) x n + 1 x n + 2 λ 2 x n y n ( x y ) D 2 x n D 2 x .

From condition (ii), (3.4) and (3.10), we have

lim n x n y n ( x y ) =0.
(3.15)

From the definition of w n , x , h n , h , we have

w n = P C (I λ 1 D 1 ) ( a x n + ( 1 a ) y n ) = P C (I λ 1 D 1 ) h n

and

x = P C (I λ 1 D 1 ) ( a x + ( 1 a ) y ) = P C (I λ 1 D 1 ) h .

From the properties of P C , we have

y n w n + ( x y ) 2 = y n y ( w n x ) 2 = y n a x n + a x n a y n + a y n λ 1 D 1 ( a x n + ( 1 a ) y n ) + λ 1 D 1 ( a x n + ( 1 a ) y n y + a x a x + a y a y + λ 1 D 1 ( a x + ( 1 a ) y ) λ 1 D 1 ( a x + ( 1 a ) y ) ( w n x ) 2 = a x n + ( 1 a ) y n λ 1 D 1 ( a x n + ( 1 a ) y n ) ( a x + ( 1 a ) y λ 1 D 1 ( a x + ( 1 a ) y ) ) ( w n x ) + λ 1 ( D 1 ( a x n + ( 1 a ) y n ) D 1 ( a x + ( 1 a ) y ) ) + a ( y n x n y + x ) 2 = ( I λ 1 D 1 ) ( a x n + ( 1 a ) y n ) ( I λ 1 D 1 ) ( a x + ( 1 a ) y ) ( w n x ) + λ 1 ( D 1 ( a x n + ( 1 a ) y n ) D 1 ( a x + ( 1 a ) y ) ) + a ( y n x n y + x ) 2 = ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h ( P C ( I λ 1 D 1 ) h n P C ( I λ 1 D 1 ) h ) + λ 1 ( D 1 h n D 1 h ) + a ( y n x n y + x ) 2 ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h ( P C ( I λ 1 D 1 ) h n P C ( I λ 1 D 1 ) h ) 2 + 2 λ 1 ( D 1 h n D 1 h ) + a ( y n x n y + x ) , y n w n + ( x y ) ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h 2 P C ( I λ 1 D 1 ) h n P C ( I λ 1 D 1 ) h 2 + 2 ( λ 1 D 1 h n D 1 h + a y n x n y + x ) × y n w n + ( x y ) = ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h 2 w n x 2 + 2 ( λ 1 D 1 h n D 1 h + a y n x n y + x ) × y n w n + ( x y ) ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h 2 S w n S x 2 + 2 ( λ 1 D 1 h n D 1 h + a y n x n y + x ) × y n w n + ( x y ) ( ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h + S w n S x ) × ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h ( S w n x ) + 2 ( λ 1 D 1 h n D 1 h + a y n x n y + x ) × y n w n + ( x y ) = ( ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h + S w n S x ) × h n h λ 1 ( D 1 h n D 1 h ) ( S w n x ) + 2 ( λ 1 D 1 h n D 1 h + a y n x n y + x ) × y n w n + ( x y ) = ( ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h + S w n S x ) × x n S w n + ( x h ) ( x n h n ) λ 1 ( D 1 h n D 1 h ) ) + 2 ( λ 1 D 1 h n D 1 h + a y n x n y + x ) × y n w n + ( x y ) ( ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h + S w n S x ) × ( x n S w n + ( x h ) ( x n h n ) + λ 1 D 1 h n D 1 h ) + 2 ( λ 1 D 1 h n D 1 h + a y n x n y + x ) × y n w n + ( x y ) = ( ( I λ 1 D 1 ) h n ( I λ 1 D 1 ) h + S w n S x ) × ( x n S w n + ( 1 a ) x y x n + y n + λ 1 D 1 h n D 1 h ) + 2 ( λ 1 D 1 h n D 1 h + a y n x n y + x ) × y n w n + ( x y ) .

From (3.6), (3.12) and (3.15), we have

lim n y n w n + ( x y ) =0.
(3.16)

Since

x n w n x n y n ( x y ) + y n + ( x y ) w n

and (3.15), (3.16), then we have

lim n x n w n =0.
(3.17)

From (3.6) and (3.17), we can conclude that

lim n S w n w n =0.

Next we show that

lim sup n u x 0 , x n x 0 0,
(3.18)

where x 0 = P F u. To show this inequality, take a subsequence { x n k } of { x n } such that

lim sup n u x 0 , x n x 0 = lim k u x 0 , x n k x 0 .

Without loss of generality, we may assume that x n k ω as k, where ωC. From (3.17), we have w n k ω as k. From Lemma 2.5 and (3.13), we have

ωF(S).

From Lemma 2.4, we have F(S)= i = 1 N F( T i ). Then we obtain

ω i = 1 N F( T i ).

From the nonexpansiveness of the mapping G and the definition of w n , we have

w n G w n = P C ( I λ 1 D 1 ) ( a x n + ( 1 a ) P C ( I λ 2 D 2 ) x n ) G ( w n ) = G x n G w n x n w n .

From (3.17), we have

lim n w n G w n =0.
(3.19)

From w n k ω as k, (3.19) and Lemma 2.5, we have

ωF(G).

Hence, we can conclude that ωF.

Since x n k ω as k and ωF, we have

lim sup n u x 0 , x n x 0 = lim k u x 0 , x n k x 0 =u x 0 ,ω x 0 0.
(3.20)

From the definition of x n and x 0 = P F u, we have

x n + 1 x 0 2 = α n ( u x 0 ) + β n ( x n x 0 ) + γ n ( S w n x 0 ) 2 β n ( x n x 0 ) + γ n ( S w n x 0 ) 2 + 2 α n u x 0 , x n + 1 x 0 β n x n x 0 2 + γ n G x n x 0 2 + 2 α n u x 0 , x n + 1 x 0 β n x n x 0 2 + γ n x n x 0 2 + 2 α n u x 0 , x n + 1 x 0 ( 1 α n ) x n x 0 2 + 2 α n u x 0 , x n + 1 x 0 .

From condition (ii), (3.18) and Lemma 2.2, we can conclude that the sequence { x n } converges strongly to x 0 = P F u. This completes the proof. □

Remark 3.2 (1) If we take a=0, then the iterative scheme (3.1) reduces to the following scheme:

{ x 1 , u C , y n = P C ( I λ 2 D 2 ) x n , x n + 1 = α n u + β n x n + γ n S P C ( I λ 1 D 1 ) y n , n 1 ,
(3.21)

which is an improvement to (1.4). From Theorem 3.1, we obtain that the sequence { x n } generated by (3.21) converges strongly to x 0 = P i = 1 N F ( T i ) F ( G ) u, where the mapping G:CC defined by Gx= P C (I λ 1 D 1 ) P C (I λ 2 D 2 )x for all xC and ( x 0 , y 0 ) is a solution of (1.2) where y 0 = P C (I λ 2 D 2 ) x 0 .

(2) If we take N=1, α 1 1 =1 and T 1 =T, then the iterative scheme (3.1) reduces to the following scheme:

{ x 1 , u C , y n = P C ( I λ 2 D 2 ) x n , x n + 1 = α n u + β n x n + γ n T P C ( I λ 1 D 1 ) ( a x n + ( 1 a ) y n ) , n 1 ,
(3.22)

From Theorem 3.1, we obtain that the sequence { x n } generated by (3.22) converges strongly to x 0 = P F ( T ) F ( G ) u, where the mapping G:CC defined by G(x)= P C (I λ 1 D 1 )(ax+(1a) P C (I λ 2 D 2 )x) for all xC and ( x 0 , y 0 ) is a solution of (1.3) where y 0 = P C (I λ 2 D 2 ) x 0 .

4 Applications

In this section we prove a strong convergence theorem involving variational inequalities problems by using our main result. We need the following lemmas to prove the desired results.

Lemma 4.1 Let C be a nonempty closed convex subset of a real Hilbert space H. Let T,S:CC be nonexpansive mappings. Define a mapping B A :CC by B A x=T(αI+(1α)S)x for every xC and α(0,1). Then F( B A )=F(T)F(S) and B A is a nonexpansive mapping.

Proof It is easy to see that F(T)F(S)F( B A ). Let x 0 F( B A ) and x F(T)F(S). By the definition of B A , we have

x 0 x 2 = B x 0 x 2 = T ( α I + ( 1 α ) S ) x 0 x 2 α x 0 + ( 1 α ) S x 0 x 2 = α x 0 x 2 + ( 1 α ) S x 0 x 2 α ( 1 α ) x 0 S x 0 2 α x 0 x 2 + ( 1 α ) x 0 x 2 α ( 1 α ) x 0 S x 0 2 = x 0 x 2 α ( 1 α ) x 0 S x 0 2 .
(4.1)

From (4.1), it implies that

α(1α) x 0 S x 0 2 0.

Then we have x 0 =S x 0 , that is, x 0 F(S). By the definition of B A , we have

x 0 = B A x 0 =T ( α x 0 + ( 1 α ) S x 0 ) =T x 0 .

It follows that x 0 F(T). Then we have x 0 F(T)F(S). Hence F( B A )F(T)F(S).

Next, we show that B A is a nonexpansive mapping. Let x,yC, since

B A x B A y 2 = T ( α I + ( 1 α ) S ) x T ( α I + ( 1 α ) S ) y 2 ( α I + ( 1 α ) S ) x ( α I + ( 1 α ) S ) y 2 = α ( x y ) + ( 1 α ) ( S x S y ) 2 α x y 2 + ( 1 α ) S x S y 2 x y 2 .
(4.2)

Then we have B A is a nonexpansive mapping. □

Lemma 4.2 (See [15])

Let H be a real Hibert space, let C be a nonempty closed convex subset of H and let A be a mapping of C into H. Let uC. Then for λ>0,

u= P C (IλA)uuVI(C,A),

where P C is the metric projection of H onto C.

Lemma 4.3 Let C be a nonempty closed convex subset of a real Hilbert space H and let D 1 , D 2 :CH be d 1 , d 2 -inverse strongly monotone mappings, respectively, which VI(C, D 1 )VI(C, D 2 ). Define a mapping G:CC as in Lemma 2.7 for every λ 1 (0,2 d 1 ), λ 2 (0,2 d 2 ) and a(0,1). Then F(G)=VI(C, D 1 )VI(C, D 2 ).

Proof First, we show that (I λ 1 D 1 ), (I λ 2 D2) are nonexpansive. Let x,yC. Since D 1 is d 1 -inverse strongly monotone and λ 1 <2 d 1 , we have

( I λ 1 D 1 ) x ( I λ 1 D 1 ) y 2 = x y λ 1 ( D 1 x D 1 y ) 2 = x y 2 2 λ 1 x y , D 1 x D 1 y + λ 1 2 D 1 x D 1 y 2 x y 2 2 d 1 λ 1 D 1 x D 1 y 2 + λ 1 2 D 1 x D 1 y 2 = x y 2 + λ 1 ( λ 1 2 d 1 ) D 1 x D 1 y 2 x y 2 .
(4.3)

Thus (I λ 1 D 1 ) is nonexpansive. By using the same method as (4.3), we have (I λ 2 D 2 ) is a nonexpansive mapping. Hence P C (I λ 1 D 1 ), P C (I λ 2 D 2 ) are nonexpansive mappings. From

G(x)= P C (I λ 1 D 1 ) ( a x + ( 1 a ) P C ( I λ 2 D 2 ) x ) ,

for every xC and Lemma 4.1, we have

F(G)=F ( P C ( I λ 1 D 1 ) ) F ( P C ( I λ 2 D 2 ) ) .
(4.4)

From Lemma 4.2, we have

F(G)=VI(C, D 1 )VI(C, D 2 ).

 □

Theorem 4.4 Let C be a nonempty closed convex subset of a real Hilbert space H and let D 1 , D 2 :CH be d 1 , d 2 -inverse strongly monotone mappings, respectively. Define the mapping G:CC by G(x)= P C (I λ 1 D 1 )(ax+(1a) P C (I λ 2 D 2 )x) for all xC, λ 1 , λ 2 >0 and a(0,1). Let { T i } i = 1 N be a finite family of κ-strict pseudo-contractive mappings of C into C with F= i = 1 N F( T i )VI(C, D 1 )VI(C, D 2 ) and κ=max{ κ i :i=1,2,,N} and let α j =( α 1 j , α 2 j , α 3 j )I×I×I, j=1,2,3,,N, where I=[0,1], α 1 j + α 2 j + α 3 j =1, α 1 j , α 3 j (κ,1) for all j=1,2,,N1 and α 1 N (κ,1], α 3 N [κ,1), α 2 j [κ,1) for all j=1,2,,N. Let S be a mapping generated by T 1 , T 2 ,, T N and α 1 , α 2 ,, α N . Suppose that x 1 ,uC and let { x n } be a sequence generated by

{ y n = P C ( I λ 2 D 2 ) x n , x n + 1 = α n u + β n x n + γ n S P C ( a x n + ( 1 a ) y n λ 1 D 1 ( a x n + ( 1 a ) y n ) ) , x n + 1 = n 1 ,
(4.5)

where λ 1 (0,2 d 1 ), λ 2 (0,2 d 2 ) and { α n }, { β n }, { γ n } are sequences in [0,1]. Assume that the following conditions hold:

(i) α n + β n + γ n = 1 , (ii) lim n α n = 0 and n = 1 α n = , (iii) 0 < lim inf n β n lim sup n β n < 1 .

Then { x n } converges strongly to x 0 = P F u.

Proof From Lemma 4.3 and Theorem 3.1 we can conclude the desired conclusion. □

References

  1. Kinderlehrer D, Stampacchia G: An Introduction to Variational Inequalities and Their Applications. Academic Press, New York; 1980.

    MATH  Google Scholar 

  2. Lions JL, Stampacchia G: Variational inequalities. Commun. Pure Appl. Math. 1967, 20: 493–517.

    Article  MathSciNet  Google Scholar 

  3. Chang SS, Joseph Lee HW, Chan CK: A new method for solving equilibrium problem fixed point problem and variational inequality problem with application to optimization. Nonlinear Anal. 2009, 70: 3307–3319.

    Article  MathSciNet  Google Scholar 

  4. Nadezhkina N, Takahashi W: Weak convergence theorem by an extragradientmethod for nonexpansive mappings and monotone mappings. J. Optim. Theory Appl. 2006, 128: 191–201.

    Article  MathSciNet  Google Scholar 

  5. Yao JC, Chadli O: Pseudomonotone complementarity problems and variational inequalities. In Handbook of Generalized Convexity and Monotonicity. Edited by: Crouzeix JP, Haddjissas N, Schaible S. Springer, New York; 2005:501–558.

    Chapter  Google Scholar 

  6. Yao Y, Yao JC: On modified iterative method for nonexpansive mappings and monotone mappings. Appl. Math. Comput. 2007, 186(2):1551–1558.

    Article  MathSciNet  Google Scholar 

  7. Ceng LC, Yao JC: Strong convergence theorems for variational inequalities and fixed point problems of asymptotically strict pseudocontractive mappings in the intermediate sense. Acta Appl. Math. 2011, 115: 167–191.

    Article  MathSciNet  Google Scholar 

  8. Sahu DR, Wong NC, Yao JC: A unified hybrid iterative method for solving variational inequalities involving generalized pseudo-contractive mappings. SIAM J. Control Optim. 2012, 50: 2335–2354.

    Article  MathSciNet  Google Scholar 

  9. Zeng LC, Ansari QH, Wong NC, Yao JC: An extragradient-like approximation method for variational inequalities and fixed point problems. Fixed Point Theory Appl. 2011., 2011: Article ID 22. doi:10.1186/1687–1812–2011–22

    Google Scholar 

  10. Iiduka H, Takahashi W: Weak convergence theorem by Ces‘aro means for nonexpansive mappings and inverse-strongly monotone mappings. J. Nonlinear Convex Anal. 2006, 7: 105–113.

    MathSciNet  Google Scholar 

  11. Ceng LC, Wang CY, Yao JC: Strong convergence theorems by a relaxed extragradient method for a general system of variational inequalities. Math. Methods Oper. Res. 2008, 67: 375–390.

    Article  MathSciNet  Google Scholar 

  12. Ceng LC, Ansari QH, Yao JC: Strong and weak convergence theorems for asymptotically strict pseudocontractive mappings in intermediate sense. J. Nonlinear Convex Anal. 2010, 11: 283–308.

    MathSciNet  Google Scholar 

  13. Ceng LC, Petruşel A, Yao JC: Iterative approximation of fixed points for asymptotically strict pseudocontractive type mappings in the intermediate sense. Taiwan. J. Math. 2011, 15: 587–606.

    Google Scholar 

  14. Ceng LC, Shyu DS, Yao JC: Relaxed composite implicit iteration process for common fixed points of a finite family of strictly pseudocontractive mappings. Fixed Point Theory Appl. 2009., 2009: Article ID 402602. doi:10.1155/2009/402602

    Google Scholar 

  15. Takahashi W: Nonlinear Functional Analysis. Yokohama Publishers, Yokohama; 2000.

    MATH  Google Scholar 

  16. Xu HK: An iterative approach to quadratic optimization. J. Optim. Theory Appl. 2003, 116(3):659–678.

    Article  MathSciNet  Google Scholar 

  17. 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.

    Article  MathSciNet  Google Scholar 

  18. Kangtunyakarn A, Suantai S: Strong convergence of a new iterative scheme for a finite family of strict pseudo-contractions. Comput. Math. Appl. 2010, 60: 680–694.

    Article  MathSciNet  Google Scholar 

  19. Browder FE: Nonlinear operators and nonlinear equations of evolution in Banach spaces. Proc. Symp. Pure Math. 1976, 18: 78–81.

    Google Scholar 

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Acknowledgements

This research was supported by the Research Administration Division of King Mongkut’s Institute of Technology Ladkrabang.

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Kangtunyakarn, A. An iterative algorithm to approximate a common element of the set of common fixed points for a finite family of strict pseudo-contractions and of the set of solutions for a modified system of variational inequalities. Fixed Point Theory Appl 2013, 143 (2013). https://doi.org/10.1186/1687-1812-2013-143

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