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Convergence of a regularization algorithm for nonexpansive and monotone operators in Hilbert spaces

Abstract

Variational inequality, fixed point and generalized equilibrium problems are investigated via a regularization algorithm. It is proved that the sequence generated in the regularization algorithm converges strongly to a common solution of the three problems in the framework of Hilbert spaces. The results presented in this paper improve and extend the corresponding ones announced by many authors.

1 Introduction and preliminaries

In this paper, we always assume that H is a real Hilbert space with inner product x,y and induced norm x= x , x for x,yH. Let C be a nonempty, closed, and convex subset of H.

Let A:CH be a mapping. Recall that A is said to be monotone iff

AxAy,xy0,x,yC.

Recall that A is said to be strongly monotone iff there exists a constant α>0 such that

AxAy,xyα x y 2 ,x,yC.

For such a case, A is also said to be α-strongly monotone. Recall that A is said to be inverse-strongly monotone iff there exists a constant α>0 such that

AxAy,xyα A x A y 2 ,x,yC.

For such a case, A is also said to be α-inverse-strongly monotone.

Recall that the classical variational inequality is to find an xC such that

Ax,yx0,yC.
(1.1)

In this paper, we always use VI(C,A) to denote the solution set of (1.1) and use P C denote the metric projection from H onto C. It is well known that xC is a solution of (1.1) iff x is a fixed point of the mapping P C (IrA), where r>0 is a constant, I stands for the identity mapping. If A is strongly monotone and Lipschitz continuous, the existence and uniqueness of solutions of equilibrium (1.1) is guaranteed by the Banach contraction principle.

Recall that a set-valued mapping M:HH is said to be monotone iff, for all x,yH, fMx, and gMy imply xy,fg>0. M is maximal iff the graph Graph(M) of R is not properly contained in the graph of any other monotone mapping. It is well known that a monotone mapping M is maximal if and only if, for any (x,f)H×H, xy,fg0, for all (y,g)Graph(M) implies fRx.

Let S:CC be a mapping. F(S) stands for the fixed point set of S; that is, F(S):={xC:x=Sx}.

Recall that S is said to be contractive iff there exists a constant α(0,1) such that

SxSyαxy,x,yC.

For such a case, S is also said to be α-contractive. We know that the mapping enjoys a unique fixed point and Picard’s algorithm can be employed to approximate its unique fixed point.

Recall that S is said to be nonexpansive iff

SxSyxy,x,yC.

If C is a closed, bounded and convex subset of H, then F(S) is not empty; see [1].

Let { S i :CC} be a family of infinitely nonexpansive mappings and { γ i } be a nonnegative real sequence with 0 γ i <1, i1. For n1, define a mapping W n :CC as follows:

U n , n + 1 = I , U n , n = γ n S n U n , n + 1 + ( 1 γ n ) I , U n , n 1 = γ n 1 S n 1 U n , n + ( 1 γ n 1 ) I , U n , k = γ k S k U n , k + 1 + ( 1 γ k ) I , U n , k 1 = γ k 1 S k 1 U n , k + ( 1 γ k 1 ) I , U n , 2 = γ 2 S 2 U n , 3 + ( 1 γ 2 ) I , W n = U n , 1 = γ 1 S 1 U n , 2 + ( 1 γ 1 ) I .
(1.2)

Such a mapping W n is nonexpansive from C to C and it is called a W-mapping generated by S n , S n 1 ,, S 1 and γ n , γ n 1 ,, γ 1 ; see [2] and the references therein.

Let T:CH be a monotone mapping and let F be a bifunction of C×C into , where denotes the set of real numbers. We consider the following generalized equilibrium problem:

Find xC such that F(x,y)+Tx,yx0,yC.
(1.3)

In this paper, the set of such xC is denoted by EP(F,T), i.e.,

GEP(F,A)= { x C : F ( x , y ) + T x , y x 0 , y C } .

If T0, the zero mapping, then the problem (1.3) is reduced to the following equilibrium problem [3]:

Find xC such that F(x,y)0,yC.
(1.4)

In this paper, the set of such an xC is denoted by EP(F).

If F0, then the problem (1.3) is reduced to the classical variational inequality (1.1).

To study equilibrium problems (1.3) and (1.4), we may assume that F satisfies the following conditions:

(A1) F(x,x)=0 for all xC;

(A2) F is monotone, i.e., F(x,y)+F(y,x)0 for all x,yC;

(A3) for each x,y,zC,

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

(A4) for each xC, yF(x,y) is convex and weakly lower semi-continuous.

Many important problems have reformulations which require finding solutions of equilibriums (1.3) and (1.4), for instance, image recovery, inverse problems, network allocation, transportation problems and optimization problems; see [311] and the references therein. For solving solutions of equilibriums (1.3) and (1.4), regularization methods recently have been extensively studied; see [1128] and the references therein.

In this paper, motivated and inspired by the research going on in this direction, we study the variational inequality (1.1), and the fixed point and equilibrium problem (1.3) based on a regularization algorithm. It is proved that the sequence generated in the regularization algorithm converges strongly to a common solutions of the three problems in the framework of Hilbert spaces. The results presented in this paper improve and extend the corresponding results in Chang et al. [11], Takahashi and Takahashi [13] and Hao [29].

The following lemmas play an important role in our paper.

Lemma 1.1 [3]

Let F:C×CR be a bifunction satisfying (A1)-(A4). Then, for any r>0 and xH, there exists zC such that

F(z,y)+ 1 r yz,zx0,yC.

Define a mapping T r :HC as follows:

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

then the following conclusions hold:

  1. (1)

    T r is single-valued;

  2. (2)

    T r is firmly nonexpansive, i.e., for any x,yH,

    T r x T r y 2 T r x T r y,xy;
  3. (3)

    F( T r )=EP(F);

  4. (4)

    EP(F) is closed and convex.

Lemma 1.2 [30]

Assume that { α n } is a sequence of nonnegative real numbers such that

α n + 1 (1 γ n ) α n + δ n ,

where { γ n } is a sequence in (0,1) and { δ n } is a sequence such that

  1. (1)

    n = 1 γ n =;

  2. (2)

    lim sup n δ n / γ n 0 or n = 1 | δ n |<.

Then lim n α n =0.

Lemma 1.3 [2]

Let { S i :CC} be a family of infinitely nonexpansive mappings with a nonempty common fixed point set and let { γ i } be a real sequence such that 0< γ i l<1, where l is some real number, i1. Then

  1. (1)

    W n is nonexpansive and F( W n )= i = 1 F( S i ), for each n1;

  2. (2)

    for each xC and for each positive integer k, the limit lim n U n , k exists.

  3. (3)

    the mapping W:CC defined by

    Wx:= lim n W n x= lim n U n , 1 x,xC,
    (1.5)

is a nonexpansive mapping satisfying F(W)= i = 1 F( S i ) and it is called the W-mapping generated by S 1 , S 2 , and γ 1 , γ 2 , .

Lemma 1.4 [31]

Let { x n } and { y n } be bounded sequences in H 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 =(1 β n ) y n + β n x n for all n0 and

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

Then lim n y n x n =0.

Lemma 1.5 [11]

Let { S i :CC} be a family of infinitely nonexpansive mappings with a nonempty common fixed point set and let { γ i } be a real sequence such that 0< γ i l<1, i1. If K is any bounded subset of C, then

lim n sup x K Wx W n x=0.

Throughout this paper, we always assume that 0< γ i l<1, i1.

Lemma 1.6 [10]

Let A:CH a Lipschitz monotone mapping and let N C x be the normal cone to C at xC; that is, N C x={yH:xu,y,uC}. Define

Dx={ A x + N C x , x C , x C .

Then D is maximal monotone and 0Dx if and only if xVI(C,A).

2 Main results

Theorem 2.1 Let C be a nonempty closed convex subset of H. Let F be a bifunction from C×C to which satisfies (A1)-(A4) and let f:CC be a κ-contraction. Let A:CH be an α-inverse-strongly monotone mapping and let B:CH be a β-inverse-strongly monotone mapping. Let T:CH be a τ-inverse-strongly monotone mapping. Let { S i :CC} be a family of infinitely nonexpansive mappings. Assume that Σ= i = 1 F( S i )GEP(F,T)VI(C,A)VI(C,B) is not empty. Let { α n }, { β n }, and { γ n } be sequences in (0,1) such that α n + β n + γ n =1. Let { r n }, { s n }, and { λ n } be positive number sequences. Let x 1 C and let { x n } be a sequence generated by

{ y n = P C ( u n s n B u n ) , x n + 1 = α n f ( y n ) + β n W n P C ( y n r n A y n ) + γ n x n , n 1 ,
(2.1)

where { u n } is such that F( u n ,y)+T x n ,y u n + 1 λ n y u n , u n x n 0, yC, and { W n } is the sequence generated in (1.5). Assume that the following restrictions hold:

  1. (a)

    0<a λ n b<2τ and lim n | λ n + 1 λ n |=0,

  2. (b)

    0< a r n b <2α and lim n | r n + 1 r n |=0,

  3. (c)

    0< a s n b <2β and lim n | s n + 1 s n |=0,

  4. (d)

    lim n α n =0, n = 1 α n =,

  5. (e)

    0< lim inf n γ n lim sup n γ n <1,

where a, a , a , b, b , and b are real constants. Then { x n } converges strongly to x ¯ Σ, which solves uniquely the following variational inequality:

x ¯ f ( x ¯ ) , x ¯ x 0,xΣ.

Proof Since A is inverse-strongly monotone, we see from restriction (b) that

( I r n A ) x ( I r n A ) y 2 = x y 2 2 r n x y , A x A y + r n 2 A x A y 2 x y 2 2 r n α A x A y 2 + r n 2 A x A y 2 = x y 2 + r n ( r n 2 α ) A x A y 2 x y 2 , x , y C .

This shows that I r n A is nonexpansive. In the same way, we find that I s n B and I λ n T are nonexpansive. Note that u n can be re-written as u n = T λ n (I λ n T) x n . Let x Σ. It follows that

u n x ( I λ n T ) x n ( I λ n T ) x x n x .

Putting z n = P C ( y n r n )A y n , we see that z n x y n x x n x .

x n + 1 x α n f ( y n ) x + β n W n z n x + γ n x n x α n κ y n x + α n f ( x ) x + β n z n x + γ n x n x ( 1 α n ( 1 κ ) ) x n x + α n ( 1 κ ) f ( x ) x 1 κ .

This implies that

x n x max { x 1 x , f ( x ) x 1 κ } <.

This yields the result that the sequence { x n } is bounded, and so are { y n }, { z n }, and { u n }. Without loss of generality, we can assume that there exists a bounded set KC such that x n , y n , z n , u n K. Since u n = T λ n (I λ n ) x n , we find that

F( u n + 1 ,y)+ 1 λ n + 1 y u n + 1 , u n + 1 ( I r n + 1 T ) x n + 1 0,yC,
(2.2)

and

F( u n ,y)+ 1 λ n y u n , u n ( I λ n T ) x n 0,yC.
(2.3)

Let y= u n in (2.2) and y= u n + 1 in (2.3). By adding up these two inequalities, we obtain

u n + 1 u n , u n u n + 1 + u n + 1 ( I λ n A 3 ) x n λ n λ n + 1 ( u n + 1 ( I λ n + 1 A 3 ) x n + 1 ) 0.

This implies that

u n + 1 u n 2 u n + 1 u n , ( I λ n + 1 T ) x n + 1 ( I λ n T ) x n + ( 1 λ n λ n + 1 ) ( u n + 1 ( I λ n + 1 T ) x n + 1 ) u n + 1 u n ( ( I λ n + 1 T ) x n + 1 ( I λ n T ) x n + | 1 λ n λ n + 1 | u n + 1 ( I λ n + 1 T ) x n + 1 ) .

It follows that

u n + 1 u n ( I λ n + 1 T ) x n + 1 ( I λ n T ) x n + | λ n + 1 λ n | λ n + 1 u n + 1 ( I λ n + 1 T ) x n + 1 x n + 1 x n + | λ n + 1 λ n | M 1 ,
(2.4)

where M 1 is an appropriate constant such that

M 1 = sup n 1 { T x n + u n + 1 ( I λ n + 1 T ) x n + 1 a } .

It follows from (2.4) that

y n + 1 y n P C ( u n + 1 s n + 1 B u n + 1 ) P C ( u n s n + 1 B u n ) + P C ( u n s n + 1 B u n ) P C ( u n s n B u n ) u n + 1 u n + | s n + 1 s n | B u n x n + 1 x n + | λ n + 1 λ n | M 1 + | s n + 1 s n | B u n .

Hence, we have

z n + 1 z n P C ( y n + 1 r n + 1 A y n + 1 ) P C ( y n r n + 1 A y n ) + P C ( y n r n + 1 A y n ) P C ( y n r n A y n ) y n + 1 y n + | r n + 1 r n | A y n x n + 1 x n + M 2 ( | λ n + 1 λ n | + | s n + 1 s n | + | r n + 1 r n | ) ,
(2.5)

where M 2 =max{ M 1 , sup n 1 {A y n }, sup n 1 {B u n }}. This implies from (2.5) that

W n + 1 z n + 1 W n z n W n + 1 z n + 1 W z n + 1 + W z n + 1 W z n + W z n W n z n sup x K { W n + 1 x W x + W x W n x } + x n + 1 x n + M 2 ( | λ n + 1 λ n | + | s n + 1 s n | + | r n + 1 r n | ) ,
(2.6)

where K is the bounded subset of C defined above. Let x n + 1 =(1 γ n ) q n + γ n x n . It follows that

q n + 1 q n = α n + 1 f ( y n + 1 ) + β n + 1 W n + 1 z n + 1 1 γ n + 1 α n f ( y n ) + β n W n z n 1 γ n = α n + 1 1 γ n + 1 f ( y n + 1 ) + 1 α n + 1 γ n + 1 1 γ n + 1 W n + 1 z n + 1 ( α n 1 γ n f ( y n ) + 1 α n γ n 1 γ n W n z n ) = α n + 1 1 γ n + 1 ( f ( y n + 1 ) W n + 1 z n + 1 ) α n 1 γ n ( f ( y n ) W n z n ) + W n + 1 z n + 1 W n z n .

By use of (2.6), we find that

q n + 1 q n α n + 1 1 γ n + 1 f ( y n + 1 ) W n + 1 z n + 1 + α n 1 γ n f ( y n ) W n z n + W n + 1 z n + 1 W n z n α n + 1 1 γ n + 1 f ( y n + 1 ) W n + 1 z n + 1 + α n 1 γ n f ( y n ) W n z n + sup x K { W n + 1 x W x + W x W n x } + x n + 1 x n + M 2 ( | λ n + 1 λ n | + | s n + 1 s n | + | r n + 1 r n | ) .

This implies that

q n + 1 q n x n + 1 x n α n + 1 1 γ n + 1 f ( y n + 1 ) W n + 1 z n + 1 + α n 1 γ n f ( y n ) W n z n + sup x K { W n + 1 x W x + W x W n x } + M 2 ( | λ n + 1 λ n | + | s n + 1 s n | + | r n + 1 r n | ) .

It follows from restrictions (a)-(e) that

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

This implies from Lemma 1.4 that lim n q n x n =0. It follows that

lim n x n + 1 x n =0.
(2.7)

Since A is inverse-strongly monotone, we find that

z n x 2 ( I r n A ) y n ( I r n A ) x 2 y n x 2 2 r n α A y n A x 2 + r n 2 A y n A x 2 x n x 2 + r n ( r n 2 α ) A y n A x 2 .

It follows that

x n + 1 x 2 α n f ( y n ) x 2 + β n W n z n x 2 + γ n x n x 2 α n f ( y n ) x 2 + β n z n x 2 + γ n x n x 2 α n f ( y n ) x 2 + r n ( r n 2 α ) β n A y n A x 2 + x n x 2 .

Hence, we have

r n ( 2 α r n ) β n A y n A x 2 α n f ( y n ) x 2 + ( x n x + x n + 1 x ) x n x n + 1 .

By use of the restrictions (a), (d), and (e), we obtain from (2.7)

lim n A y n A x =0.
(2.8)

Since the metric projection is firmly nonexpansive, we find that

z n x 2 ( I r n A ) y n ( I r n A ) x , z n x = 1 2 { ( I r n A ) y n ( I r n A ) x 2 + z n x 2 ( I r n A ) y n ( I r n A ) x ( z n x ) 2 } 1 2 { y n x 2 + z n x 2 y n z n r n ( A y n A x ) 2 } 1 2 { x n x 2 + z n x 2 y n z n 2 + 2 r n y n z n A y n A x } .

Hence, we have

z n x 2 x n x 2 y n z n 2 +2 r n y n z n A y n A x .

This further implies that

x n + 1 x 2 α n f ( y n ) x 2 + β n W n z n x 2 + γ n x n x 2 α n f ( y n ) x 2 + β n z n x 2 + γ n x n x 2 α n f ( y n ) x 2 β n y n z n 2 + 2 r n y n z n A y n A x + x n x 2 ,

which yields

β n y n z n 2 α n f ( y n ) x 2 + 2 r n y n z n A y n A x + x n x 2 x n + 1 x 2 α n f ( y n ) x 2 + 2 r n y n z n A y n A x + ( x n x + x n + 1 x ) x n + 1 x n .

By use of restrictions (b), (d), and (e), we find from (2.7) that

lim n y n z n =0.
(2.9)

Since B is inverse-strongly monotone, we find that

y n x 2 ( I s n B ) u n ( I s n B ) x 2 u n x 2 2 s n β B u n B x 2 + s n 2 B u n B x 2 x n x 2 + s n ( s n 2 β ) B u n B x 2 .

It follows that

x n + 1 x 2 α n f ( y n ) x 2 + β n W n z n x 2 + γ n x n x 2 α n f ( y n ) x 2 + β n y n x 2 + γ n x n x 2 α n f ( y n ) x 2 + s n ( s n 2 β ) β n B u n B x 2 + x n x 2 .

Hence, we have

s n ( 2 β s n ) β n B u n B x 2 α n f ( y n ) x 2 + ( x n x + x n + 1 x ) x n x n + 1 .

By use of the restrictions (c), (d), and (e), we obtain from (2.7)

lim n B u n B x =0.
(2.10)

Since the metric projection is firmly nonexpansive, we find that

y n x 2 ( I s n B ) u n ( I s n B ) x , y n x = 1 2 { ( I s n B ) u n ( I s n B ) x 2 + y n x 2 ( I s n B ) y n ( I s n B ) x ( y n x ) 2 } 1 2 { u n x 2 + y n x 2 u n y n s n ( B u n B x ) 2 } 1 2 { x n x 2 + y n x 2 u n y n 2 + 2 s n u n y n B u n B x } .

Hence, we have

y n x 2 x n x 2 u n y n 2 +2 s n u n y n B u n B x .

This further implies that

x n + 1 x 2 α n f ( y n ) x 2 + β n W n z n x 2 + γ n x n x 2 α n f ( y n ) x 2 + β n y n x 2 + γ n x n x 2 α n f ( y n ) x 2 β n u n y n 2 + 2 s n u n y n B u n B x + x n x 2 ,

which yields

β n u n y n 2 α n f ( y n ) x 2 + 2 s n u n y n B u n B x + x n x 2 x n + 1 x 2 α n f ( y n ) x 2 + 2 s n u n y n B u n B x + ( x n x + x n + 1 x ) x n + 1 x n .

By use of restrictions (c), (d), and (e), we find from (2.7) that

lim n y n u n =0.
(2.11)

Since T is inverse-strongly monotone, we find that

x n + 1 x 2 α n f ( y n ) x 2 + β n u n x 2 + γ n x n x 2 α n f ( y n ) x 2 + β n x n x λ n ( T x n T x ) 2 + γ n x n x 2 α n f ( y n ) x 2 + x n x 2 λ n β n ( 2 τ λ n ) T x n T x 2 .

This implies that

λ n β n ( 2 τ λ n ) T x n T x 2 α n f ( y n ) x 2 + ( x n x + x n + 1 x ) x n x n + 1 .

In view of the restrictions (a), (d), and (e), we see from (2.7) that

lim n T x n T x =0.
(2.12)

Since T λ n is firmly nonexpansive, we find that

u n x 2 = T λ n ( I λ n T ) x n T λ n ( I λ n T ) x 2 ( I λ n T ) x n ( I λ n T ) x , u n x 1 2 ( x n x 2 + u n x 2 x n u n 2 + 2 λ n T x n T x x n u n ) .

This in turn implies that

u n x 2 x n x 2 x n u n 2 +2 λ n T x n T x x n u n .

It follows that

x n + 1 x 2 α n f ( y n ) x 2 + β n u n x 2 + γ n x n x 2 α n f ( y n ) x 2 β n x n u n 2 + 2 λ n T x n T x x n u n + x n x 2 .

By use of restrictions (a), (d), and (e), we see from (2.7) and (2.12) that

lim n x n u n =0.
(2.13)

Next, we prove that

lim sup n f ( x ¯ ) x ¯ , x n x ¯ 0,

where x ¯ = P Σ f( x ¯ ). To see this, we choose a subsequence { x n i } of { x n } such that

lim sup n ( f I ) x ¯ , x n x ¯ = lim i ( f I ) x ¯ , x n i x ¯ .

Since { x n i } is bounded, there exists a subsequence { x n i j } of { x n i } which converges weakly to w. Without loss of generality, we may assume that x n i w. Since

β n W n z n x n x n x n + 1 + α n f ( y n ) x n .

In view of the restrictions (d) and (e), we obtain from (2.7)

lim n W n z n x n =0.
(2.14)

Note that

W n z n z n W n z n x n + x n u n + u n y n + y n z n .

In view of (2.8), (2.11), (2.13), and (2.14), we find that

lim n W n z n z n =0.
(2.15)

Suppose the contrary, w i = 1 F( S i ), i.e., Www. Since y n i w, we find from Opial’s condition [32] that

lim inf i z n i w < lim inf i z n i W w lim inf i { z n i W z n i + W z n i W w } lim inf i { z n i W z n i + z n i w } .

On the other hand, we have

W z n z n W z n W n z n + W n z n y n sup x K W x W n x + W n z n z n .

In view of Lemma 1.5, we obtain from (2.15) lim n W z n z n =0. It follows that lim inf i z n i w< lim inf i z n i w. Thus one derives a contradiction. Thus, we have w i = 1 F( S i ).

Next, we show that x ¯ VI(C,A). Let T be the maximal monotone mapping defined by

Dx={ B x + N C x , x C , , x C .

For any given (x,y)Graph(D), we have yBx N C x. Since y n C, by the definition of N C , we have x y n ,yBx0. Since y n = P C ( u n s n B u n ), we see that x y n , y n u n s n +B u n 0. It follows that

x y n i , y x y n i , B x x y n i , B x x y n i , y n i u n i s n i + B u n i = x y n i , B x B y n i + x y n i , B y n i B u n i x y n i , y n i u n i s n i x y n i , B y n i B u n i x y n i , y n i u n i s n i .

Since B is Lipschitz continuous, we see that xw,y0. Notice that D is maximal monotone and hence 0Tw. This shows that wVI(C,A). In the same way, we find that wVI(C,B).

Next, we show that wGEP(F,T). Since u n = T λ n (I λ n T) x n , for any yC, we find from (A2) that

T x n i ,y u n i + y u n i , u n i x n i λ n i F(y, u n i ),yC.
(2.16)

Putting y t =ty+(1t)w for any t(0,1] and yC, we see that y t C. It follows from (2.16) that

y t u n i , T y t y t u n i , T y t T x n i , y t u n i y t u n i , u n i x n i λ n i + F ( y t , u n i ) = y t u n i , T y t T u n i + y t u n i , T u n i T x n i y t u n i , u n i x n i λ n i + F ( y t , u n i ) .

In view of the monotonicity of T, and the restriction (a), we obtain from (A4)

y t w,T y t F( y t ,q).
(2.17)

From (A1) and (A4), we see that

0 = F ( y t , y t ) t F ( y t , y ) + ( 1 t ) F ( y t , w ) t F ( y t , y ) + ( 1 t ) y t w , T y t = t F ( y t , y ) + ( 1 t ) t y w , T y t .

It follows from (A3) that wGEP(F,T). This proves that lim sup n f( x ¯ ) x ¯ , x n x ¯ 0.

Finally, we show that x n x ¯ , as n. Note that

x n + 1 x ¯ 2 = α n f ( y n ) x ¯ , x n + 1 x ¯ + β n W n z n x ¯ , x n + 1 x ¯ + γ n x n x ¯ , x n + 1 x ¯ α n κ y n x ¯ x n + 1 x ¯ + α n f ( x ¯ ) x ¯ , x n + 1 x ¯ + β n z n x ¯ x n + 1 x ¯ + γ n x n x ¯ x n + 1 x ¯ ( 1 α n ( 1 κ ) ) x n x ¯ x n + 1 x ¯ + α n f ( x ¯ ) x ¯ , x n + 1 x ¯ .

This implies that

x n + 1 x ¯ 2 ( 1 α n ( 1 κ ) ) x n x ¯ 2 +2 α n f ( x ¯ ) x ¯ , x n + 1 x ¯ .

From the restriction (d), we obtain from Lemma 1.2 lim n x n x ¯ =0. This completes the proof. □

Corollary 2.2 Let C be a nonempty closed convex subset of H. Let F be a bifunction from C×C to which satisfies (A1)-(A4) and let f:CC be a κ-contraction. Let T:CH be a τ-inverse-strongly monotone mapping. Let { S i :CC} be a family of infinitely nonexpansive mappings. Assume that Σ= i = 1 F( S i )GEP(F,T) is not empty. Let { α n }, { β n }, and { γ n } be sequences in (0,1) such that α n + β n + γ n =1. Let { λ n } be a positive number sequence. Let x 1 C and let { x n } be a sequence generated by

x n + 1 = α n f( y n )+ β n W n u n + γ n x n ,n1,

where { u n } is such that F( u n ,y)+T x n ,y u n + 1 λ n y u n , u n x n 0, yC, and { W n } is the sequence generated in (1.5). Assume that the following restrictions hold:

  1. (a)

    0<a λ n b<2τ and lim n | λ n + 1 λ n |=0,

  2. (b)

    lim n α n =0, n = 1 α n =,

  3. (c)

    0< lim inf n γ n lim sup n γ n <1,

where a and b are real constants. Then { x n } converges strongly to x ¯ Σ, which solves uniquely the following variational inequality:

x ¯ f ( x ¯ ) , x ¯ x 0,xΣ.

Corollary 2.3 Let C be a nonempty closed convex subset of H. Let F be a bifunction from C×C to which satisfies (A1)-(A4) and let f:CC be a κ-contraction. Let B:CH be a β-inverse-strongly monotone mapping. Let T:CH be a τ-inverse-strongly monotone mapping. Let { S i :CC} be a family of infinitely nonexpansive mappings. Assume that Σ= i = 1 F( S i )GEP(F,T)VI(C,B) is not empty. Let { α n }, { β n }, and { γ n } be sequences in (0,1) such that α n + β n + γ n =1. Let { s n } and { λ n } be positive number sequences. Let x 1 C and let { x n } be a sequence generated by

{ y n = P C ( u n s n B u n ) , x n + 1 = α n f ( y n ) + β n W n y n + γ n x n , n 1 ,

where { u n } is such that F( u n ,y)+T x n ,y u n + 1 λ n y u n , u n x n 0, yC, and { W n } is the sequence generated in (1.5). Assume that the following restrictions hold:

  1. (a)

    0<a λ n b<2τ and lim n | λ n + 1 λ n |=0,

  2. (b)

    0< a s n b <2β and lim n | s n + 1 s n |=0,

  3. (c)

    lim n α n =0, n = 1 α n =,

  4. (d)

    0< lim inf n γ n lim sup n γ n <1,

where a, a , b, and b are real constants. Then { x n } converges strongly to x ¯ Σ, which solves uniquely the following variational inequality:

x ¯ f ( x ¯ ) , x ¯ x 0,xΣ.

Corollary 2.4 Let C be a nonempty closed convex subset of H. Let F be a bifunction from C×C to which satisfies (A1)-(A4) and let f:CC be a κ-contraction. Let A:CH be an α-inverse-strongly monotone mapping and let B:CH be a β-inverse-strongly monotone mapping. Let { S i :CC} be a family of infinitely nonexpansive mappings. Assume that Σ= i = 1 F( S i )EP(F)VI(C,A)VI(C,B) is not empty. Let { α n }, { β n }, and { γ n } be sequences in (0,1) such that α n + β n + γ n =1. Let { r n }, { s n }, and { λ n } be positive number sequences. Let x 1 C and let { x n } be a sequence generated by

{ y n = P C ( u n s n B u n ) , x n + 1 = α n f ( y n ) + β n W n P C ( y n r n A y n ) + γ n x n , n 1 ,

where { u n } is such that F( u n ,y)+ 1 λ n y u n , u n x n 0, yC, and { W n } is the sequence generated in (1.5). Assume that the following restrictions hold:

  1. (a)

    0<a λ n b<2τ and lim n | λ n + 1 λ n |=0,

  2. (b)

    0< a r n b <2α and lim n | r n + 1 r n |=0,

  3. (c)

    0< a s n b <2β and lim n | s n + 1 s n |=0,

  4. (d)

    lim n α n =0, n = 1 α n =,

  5. (e)

    0< lim inf n γ n lim sup n γ n <1,

where a, a , a , b, b , and b are real constants. Then { x n } converges strongly to x ¯ Σ, which solves uniquely the following variational inequality:

x ¯ f ( x ¯ ) , x ¯ x 0,xΣ.

Proof In Theorem 2.1, put T=0. Then, for all τ(0,), we have

x,y,TxTyτ T x T y 2 ,x,yC.

Taking a,b(0,) with 0<a<b< and choosing a sequence { λ n } of real numbers with a λ n b, we obtain the desired result by Theorem 2.1. □

Corollary 2.5 Let C be a nonempty closed convex subset of H. Let f:CC be a κ-contraction and let T:CH be a τ-inverse-strongly monotone mapping. Let A:CH be an α-inverse-strongly monotone mapping and let B:CH be a β-inverse-strongly monotone mapping. Let { S i :CC} be a family of infinitely nonexpansive mappings. Assume that Σ= i = 1 F( S i )VI(C,T)VI(C,A)VI(C,B) is not empty. Let { α n }, { β n }, and { γ n } be sequences in (0,1) such that α n + β n + γ n =1. Let { r n }, { s n }, and { λ n } be positive number sequences. Let x 1 C and let { x n } be a sequence generated by

{ u n = P C ( x n λ n T x n ) , y n = P C ( u n s n B u n ) , x n + 1 = α n f ( y n ) + β n W n P C ( y n r n A y n ) + γ n x n , n 1 ,

where { W n } is the sequence generated in (1.5). Assume that the following restrictions hold:

  1. (a)

    0<a λ n b<2τ and lim n | λ n + 1 λ n |=0,

  2. (b)

    0< a r n b <2α and lim n | r n + 1 r n |=0,

  3. (c)

    0< a s n b <2β and lim n | s n + 1 s n |=0,

  4. (d)

    lim n α n =0, n = 1 α n =,

  5. (e)

    0< lim inf n γ n lim sup n γ n <1,

where a, a , a , b, b , and b are real constants. Then { x n } converges strongly to x ¯ Σ, which solves uniquely the following variational inequality:

x ¯ f ( x ¯ ) , x ¯ x 0,xΣ.

Proof Putting F=0, we find that

T x n ,y u n + 1 λ n y u n , u n x n 0,yC,

is equivalent to

y u n , x n λ n T x n u n 0,yC,

that is, u n = P C ( x n λ n T x n ). This completes the proof. □

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Yuan, Q., Zhang, Y. Convergence of a regularization algorithm for nonexpansive and monotone operators in Hilbert spaces. Fixed Point Theory Appl 2014, 180 (2014). https://doi.org/10.1186/1687-1812-2014-180

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Keywords

  • equilibrium problem
  • fixed point
  • variational inequality
  • zero point