Skip to main content

A new iterative method for equilibrium problems and fixed point problems for infinite family of nonself strictly pseudocontractive mappings

Abstract

The purpose of this paper is to present an iterative method for finding a common element of the set of solutions for an equilibrium problem and the set of common fixed points for a countably infinite family of nonself λ i -strictly pseudocontractive mappings { T i } i = 1 from a closed convex subset C into a Hilbert space H.

MSC:47H17, 47H20.

1 Introduction and preliminaries

Let H be a real Hilbert space with the inner product , and the norm , respectively. Let C be a nonempty closed convex subset of H, and let G:C×C(,+) be a bifunction. The equilibrium problem for G is to find u C such that

G ( u , v ) 0,vC.
(1.1)

The set of solutions of (1.1) is denoted by EP(G). The equilibrium problem (1.1) includes as special cases numerous problems in physics, optimization, economics, transportation, and engineering.

Assume that the bifunction G satisfies the following standard properties.

Assumption A Let G:C×C(,+) be a bifunction satisfying conditions (A1)-(A4).

  1. (A1)

    G(u,u)=0, uC;

  2. (A2)

    G(u,v)+G(v,u)0, (u,v)C×C;

  3. (A3)

    For each uC, G(u,):C(,+) is lower semicontinuous and convex;

  4. (A4)

    lim sup t + 0 G((1t)u+tz,v)G(u,v), (u,z,v)C×C×C.

Recall that a mapping T in H is said to be λ-strictly pseudocontractive in the terminology of Browder and Petryshyn [1], if there exists a constant 0λ<1 such that

T x T y 2 x y 2 +λ ( I T ) x ( I T ) y 2

for all x,yD(T), the domain of T, where I is the identity operator in H. Clearly, when λ=0, T is nonexpansive, i.e.,

T ( x ) T ( y ) xy.

It means that the class of λ-strictly pseudocontractive mappings strictly includes the class of nonexpansive mappings.

A single-valued mapping A in H is said to be monotone, if

A ( x ) A ( y ) , x y 0,x,yD(A),

and λ-inverse strongly monotone, if there exists a positive constant λ such that

A ( x ) A ( y ) , x y λ A ( x ) A ( y ) 2 ,x,yD(A).

Therefore, any λ-inverse strongly monotone mapping is monotone and Lipschitz continuous with the Lipschitz constant L A =1/λ. It is well known [2] that if T is a nonexpansive mapping, then IT is (1/2)-inverse strongly monotone. It is easy to verify that if T is λ-strictly pseudocontractive, then it is (1λ)/2-inverse strongly monotone. Hence, IT is Lipschitz continuous with the Lipschitz constant L=2/(1λ).

Let { T i } i = 1 be a countably infinite family of nonself λ i -strictly pseudocontractive mappings from C into H with the set of fixed points F( T i ) (i.e., F( T i )={xC:x= T i x}). Set F:= i = 1 F( T i ). Assume that

S:=FEP(G).

The problem studied in this paper is to find an element

u S.
(1.2)

If T i I, i1, then problem (1.2) is reduced to (1.1) and shown in [3] and [4] to cover monotone inclusion problems, saddle point problems, variational inequality problems, minimization problems, the Nash equilibria in noncooperative games, vector equilibrium problems, as well as certain fixed point problems (see also [5]). For finding approximative solutions of (1.1), there exist several approaches: the regularization approach [610], the gap-function approach [8, 1113], and iterative procedure approach [1430].

In the case that G0 and T i =I, i>1, (1.2) is a problem of finding a fixed point for a λ-strictly pseudocontractive mapping in C (see [31]).

In the case that G0 and T i =I, i>N>1, (1.2) is a problem of finding a common fixed point for a finite family of λ i -strictly pseudocontractive mappings T i in C studied in [32], where the following algorithm is constructed:

Let x 0 C and { α n }, { β n }, { γ n } be three sequences in [0,1] satisfying α n + β n + γ n =1 for all n1, and let { u n } be a sequence in C. Then the sequence { x n } generated by

x n = α n x n 1 + β n T n x n + γ n u n ,
(1.3)

where T n = T n mod N , is called the implicit iteration process with mean errors for a finite family of strictly pseudocontractive mappings { T i } i = 1 N . The sequence { x n } converges weakly to a common fixed point of the maps { T i } i = 1 N .

If T i =I, i>1, then (1.2) is a problem of finding a fixed point for a λ-strictly pseudocontractive mapping in C, which is an equilibrium point for G (see [33]).

Theorem 1.1 [33]

Let C be a nonempty closed convex subset of a Hilbert space H. Let G be a bifunction from C×C to (,+) satisfying (A1)-(A4), and let S be a nonexpansive mapping of C into H such that

F(S)EP(G).

Let f be a contraction of H into itself, and let { x n } and { u n } be sequences generated by x 1 H and

{ G ( u n , y ) + 1 r n y u n , u n x n 0 , y C , x n + 1 = α n f ( x n ) + ( 1 α n ) S u n

for all n0, where { α n }[0,1] and { r n }(0,) satisfy

lim n α n = 0 , n = 1 α n = , n = 1 | α n + 1 α n | < , lim inf n r n > 0 , n = 1 | r n + 1 r n | < .

Then { x n } and { u n } converge strongly to zF(S)EP(G), where z= P F ( S ) EP ( G ) f(z).

If T i =I, i>N>1, then (1.2) is a problem of finding a common fixed point for a finite family of λ i -strictly pseudocontractive mapping T i from C into H, which is an equilibrium point for G. We have constructed regularization algorithms (see [10, 19, 29]). First algorithm is defined as follows. The regularization solution u α is an element being a solution for the single equilibrium problem

{ G α ( u α , v ) 0 v C , u α C , G α ( u , v ) : = i = 0 N α μ i G i ( u , v ) + α u , v u , α > 0 , G 0 ( u , v ) = G ( u , v ) , G i ( u , v ) = A i ( u ) , v u , i = 1 , , N , μ 0 = 0 < μ i < μ i + 1 < 1 , i = 2 , , N 1 ,
(1.4)

where α is the regularization parameter.

Theorem 1.2 [19]

For each α>0, problem (1.4) has a unique solution u α such that

  1. (i)

    lim α + 0 u α = u , u S.

  2. (ii)

    u y, yS.

  3. (iii)

    u α u β ( u +dN) | α β | α , α,β>0, where d is a positive constant.

In the second algorithm, the regularization solution is defined on the base of the inertial proximal point algorithm proposed by Alvarez and Attouch [34], where the sequence { z n } is defined by an equilibrium problem

c ˜ n ( i = 0 N α n μ i F i ( z n + 1 , v ) + α n z n + 1 , v z n + 1 ) + z n + 1 z n , v z n + 1 γ n z n z n 1 , v z n + 1 0 v C , z 0 , z 1 C ,

and { c ˜ n } and { γ n } are the sequences of positive numbers.

Theorem 1.3 [19]

Assume that the parameters c ˜ n , γ n and α n are chosen such that

  1. (i)

    0< c 0 < c ˜ n , 0 γ n < γ 0 ,

  2. (ii)

    n = 1 b n =+, b n = c ˜ n α n /(1+ c ˜ n α n ),

  3. (iii)

    n = 1 γ n b n 1 z n z n 1 <+,

  4. (iv)

    lim n α n =0, lim n | α n α n + 1 | α n b n =0.

Then the sequence { z n } converges strongly to the element u , as n+.

In the case that G0, Maingé [35] considered the following iteration method:

x n + 1 = α n D x n + i 1 w i , n T i x n ,n0,
(1.5)

where D:CC is a given contraction with constant ρ[0,1), x 0 C is a starting point, { α n }(0,1), w i , n 0 for all i1 and i 1 w i , n =1 α n with the following conditions:

  1. C1.

    n = 0 α n =.

  2. C2.

    For all i N I :={i: T i I},

    1. (a)

      1 w i , n |1 α n 1 α n |0, or n 1 w i , n | α n α n 1 |<,

    2. (b)

      1 α n | 1 w i , n 1 w i , n 1 |0, or n | 1 w i , n 1 w i , n 1 |<,

    3. (c)

      1 w i , n α n k 0 | w k , n w k , n 1 |0, or n 1 w i , n k 0 | w k , n w k , n 1 |<.

  3. C3.

    α n w i , n 0 for all i N I .

Then the sequence { x n } given by (1.5) converges strongly to x ¯ the unique fixed point of P F oD, where P F is the metric projection from H onto .

For solving (1.2), Ceng and Yao [36] proposed the following algorithm:

Let x 1 H be an arbitrary element and

{ G ( u n , v ) + 1 r n u n x n , v u n , v C , y n = ( 1 γ n ) x n + γ n W n u n , x n + 1 = ( 1 α n β n ) x n + α n f ( y n ) + β n W n y n ,
(1.6)

where { α n }, { β n }, and { γ n } are three sequences in (0,1) such that α n + β n 1, and the mapping W n is defined by

{ U n , n + 1 = I , U n , n = λ n T n U n , n + 1 + ( 1 λ n ) I , U n , n 1 = λ n 1 T n 1 U n , n + ( 1 λ n 1 ) I , U n , k = λ k T n U n , k + 1 + ( 1 λ k ) I , U n , k 1 = λ k 1 T k 1 U n , k + ( 1 λ k 1 ) I , U n , 2 = λ 2 T 2 U n , 3 + ( 1 λ 2 ) I , W n = U n , 1 = λ 1 T 1 U n , 2 + ( 1 λ 1 ) I .

Theorem 1.4 [36]

Let C be a nonempty closed convex subset of a real Hilbert space H. Let G:C×C(,+) be a bifunction satisfying (A1)-(A4), and let { T i } i = 1 be a sequence of nonexpansive self-mappings on C such that

S= i = 1 F( T i )EP(G).

Suppose that { α n }, { β n }, and { γ n } are sequences in (0,1) such that α n + β n 1, and { r n }(0,) is a real sequence. Suppose that the following conditions are satisfied:

  1. (i)

    lim n α n =0 and n = 0 α n =;

  2. (ii)

    0<lim inf n β n lim sup n β n <1;

  3. (iii)

    0<lim inf n γ n lim sup n γ n <1 and lim n | γ n + 1 γ n |=0;

  4. (iv)

    0<lim inf n r n and lim n | r n + 1 r n |=0.

Let f be a contraction of C into itself and given x 0 C. Then the sequences { x n } and { u n } generated by (1.6), where { λ n } is a sequence in (0,b] for some b(0,1), converge strongly to x i = 1 F( T i )EP(G), where x = P i = 1 F ( T i ) EP ( G ) f( x ).

2 Main results

In this section, for solving problem (1.2), we present a new iterative method.

Let z 0 be an arbitrary element in a Hilbert space H, the sequence of iterations { z n } is defined by finding u n C such that

{ G ( u n , y ) + u n z n , y u n 0 , y C , z n + 1 = P C ( z n β n [ z n u n + i = 1 γ i A i ( z n ) + α n z n ] ) z n + 1 = P C ( z n β n [ i = 1 γ i A i ( z n ) + ( 1 + α n ) z n u n ] ) , n 0 ,
(2.1)

where P C is the metric projection of H onto C, and { α n }, { β n }, and { γ i } are three sequences of positive numbers such that

i = 1 γ i 2 1 λ i =γ<.
(2.2)

Also, we construct a regularization solution u α for (1.2) by solving the following variational inequality problem: find u α C such that

{ A 0 ( u α ) + i = 1 γ i A i ( u α ) + α u α , v u α 0 , v C , A i = I T i , i 0 ,
(2.3)

where T 0 (x)={zC:G(z,v)+zx,vz0vC}, { γ i } is a sequence of positive numbers satisfying (2,2), and α is a small regularization parameter tending to zero.

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

Lemma 2.1 [7]

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

G(z,v)+ 1 r zx,vz0,vC.

Lemma 2.2 [7]

Assume that G:C×C(,+) satisfies conditions (A1)-(A4). For r>0 and xH, define a mapping T r :HC as follows:

T r (x)= { z C : G ( z , v ) + 1 r z x , v z 0 v C } .
(2.4)

Then the following statements hold:

  1. (i)

    T r is single-valued;

  2. (ii)

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

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

    F( T r )=EP(G);

  4. (iv)

    EP(G) is closed and convex.

It is easy to see that T r is a nonexpansive mapping.

Lemma 2.3 [37]

Let { a n }, { b n }, and { c n } be the sequences of positive numbers satisfying the conditions:

  1. (i)

    a n + 1 (1 b n ) a n + c n , b n <1,

  2. (ii)

    n = 0 b n =+, lim n + c n b n =0.

Then lim n + a n =0.

Lemma 2.4 [38, 39]

Assume that T is a λ-strictly pseudocontractive mapping of a closed convex subset C of a Hilbert space H. Then IT is demiclosed at zero; that is, whenever { x n } is a sequence in C weakly converging to some xC, and the sequence {(IT)( x n )} strongly converges to zero, it follows that (IT)(x)=0.

Now, we are in a position to introduce and prove the main results.

Theorem 2.5 Let C be a nonempty closed convex subset of a real Hilbert space H. Let G:C×C(,+) be a bifunction satisfying (A1)-(A4), and let { T i } i = 1 be a sequence of nonself λ i -strictly pseudocontractive mappings from C into H such that

S= i = 1 F( T i )EP(G).

Assume that { γ i } satisfies condition (2.2). Then for each α>0, problem (2.3) has a unique solution u α such that

  1. (i)

    lim α 0 u α = u , u S and u y, yS,

  2. (ii)

    u α u β | α β | α u .

Proof First, we prove that problem (2.3) has a unique solution. Set

A:= i = 1 γ i A i .

Let x be a common fixed point of { T i } i 1 . Since

γ i A i ( x ) γ i A i ( x ) A i ( x ) + γ i A i ( x ) γ i 2 1 λ i x x

and i = 1 γ i 2 1 λ i =γ<+, the mapping A is well defined, and i = 1 γ i A i (x) converges absolutely for each xC. It is easy to see that A is Lipschitz continuous with the Lipschitz constant L A =γ and monotone.

Set

G i (u,v)= γ i A i ( u ) , v u ,i1

and

G 0 (u,v)= A 0 ( u ) , v u .

Then, problem (2.3) is equivalent to that: find u α C such that

G α ( u α ,v)0,vC,
(2.5)

where

G α (u,v)= G ˜ (u,v)+αu,vu

and

G ˜ (u,v)= i = 0 G i (u,v)= A 0 ( u ) + A ( u ) , v u .

It is not difficult to verify that for each i0, G i (u,v) is a bifunction. Therefore, G ˜ (u,v)(u,v) also is a bifunction, i.e., G ˜ (u,v)(u,v) satisfies Assumption A. By using Lemma 2.2 with (1/r)=α>0 and x=0, we can conclude that problem (2.5) (consequently (2.3)) has a unique solution u α for each α>0.

(i) Next, we prove that

u α y,yS.
(2.6)

Since yS, we have A i (y)=0, i0. Thus,

i = 0 γ i A i ( u α ) , y u α +α u α ,y u α 0,yS.
(2.7)

Since

γ i A i ( u α ) , u α y 0,yS,i0,

from (2.7), follows (2.6). Then, there exists a subsequence { u α k } of { u α } that converges weakly to some element u H. Now, we have to prove that u S. The (1 λ l )/2-inverse strongly monotone property of A l implies that

0 γ l 1 λ l 2 A l ( u α k ) 2 γ l A l ( u α k ) , u α k y i = 1 γ i A i ( u α k ) , u α k y α k u α k , u α k y α k y , y u α k .

Therefore,

lim k A l ( u α k ) =0.

By virtue of Lemma 2.4, we have u F( T l ). Since the closed convex set S has only one element with the minimal norm, using (2.6) and the weak convergence of { u α }, we can conclude that all the sequence { u α } converges strongly to u as α0.

(ii) By virtue of (2.4), (2.5) and the monotone property of A i , we obtain

α u α , u β u α +β u β , u α u β 0

or

u α u β | α β | α u β | α β | α u

for each α,β>0. This completes the proof. □

Remark Obviously, if u α k u ˜ , where u α k is the solution of (2.4) with α= α k 0, as k+, then S.

Theorem 2.6 Let C be a nonempty closed convex subset of a real Hilbert space H. Let G:C×C(,+) be a bifunction satisfying (A1)-(A4), and let { T i } i = 1 be a sequence of nonself λ i -strictly pseudocontractive mappings from C into H such that

S= i = 1 F( T i )EP(G).

Assume that { γ i } satisfies condition (2.2), and α n , β n satisfy the following conditions:

α n , β n > 0 , lim n α n = 0 , lim n | α n α n + 1 | α n 2 β n = 0 , n = 0 α n β n = , lim ¯ n β n ( 2 + γ + α n ) 2 α n < 1 .

Then the sequence { z n } given by (2.1) converges strongly to u S, that is,

lim n z n = u S.

Proof Clearly, iteration { z n } in (2.1) has the form

z n + 1 = P C ( z n β n [ i = 0 γ i A i ( z n ) + α n z n ] ) , z 0 C,n0,
(2.8)

where γ 0 =1.

Let u n be the solution of (2.3) when α= α n . Then

u n = P C ( u n β n [ i = 0 γ i A i ( u n ) + α n u n ] ) .
(2.9)

Set Δ n = z n u n . Obviously,

Δ n + 1 = z n + 1 u n + 1 z n + 1 u n + u n + 1 u n .

From the nonexpansive property of P C , the monotone and Lipschitz continuous properties of A i , i0, (2.8), and (2.9), we have

z n + 1 u n z n u n β n [ i = 0 γ i ( A i ( z n ) A i ( u n ) ) + α n ( z n u n ) ] ,

and

z n u n β n [ i = 0 γ i ( A i ( z n ) A i ( u n ) ) + α n ( z n u n ) ] 2 = z n u n 2 + β n 2 [ i = 1 γ i ( A i ( z n ) A i ( u n ) ) + α n ( z n u n ) ] 2 2 β n i = 0 γ i ( A i ( z n ) A i ( u n ) ) + α n ( z n u n ) , z n u n z n u n 2 [ 1 2 β n α n + β n 2 ( 2 + i = 1 γ i 2 1 λ i + α n ) 2 ] .

Thus,

z n + 1 u n Δ n ( 1 2 β n α n + β n 2 ( 2 + γ + α n ) 2 ) 1 / 2 Δ n ( 1 β n α n ) 1 / 2 Δ n ( 1 1 2 β n α n ) .

Set

b n = 1 2 α n β n , c n = α n α n + 1 α n u .

It is not difficult to check that b n and c n satisfy the conditions in Lemma 2.3 for sufficiently large n. Hence, lim n + Δ n 2 =0. Since lim n u n = u , we have

lim n z n = u S.

This completes the proof. □

Remark The sequences α n = ( 1 + n ) p , 0<p<1/2, and β n = γ 0 α n with

0< γ 0 < 1 ( 2 + γ + α 0 ) 2

satisfy all the necessary conditions in Theorem 2.6.

3 Application

In this section, we show that algorithm (2.1) can be applied to find an element

u SVI ( C , A 0 ) ,
(3.1)

where VI(C, A 0 ) is the set of solutions of the following variational inequality problem:

A 0 ( u ) , v u 0,vC,uC,
(3.2)

involving a monotone hemicontinuous mapping A 0 . If A 0 is a λ-inverse strongly monotone mapping, and { T i } i 1 is a countably infinite family of nonexpansive self mappings in C, then problem (3.1) is recently studied in [40] and [41].

Let A 0 be a monotone hemicontinuous mapping. Then it is easy to see that G 0 (u,v):= A 0 (u),vu is a bifunction, i.e., G 0 (u,v) satisfies Assumption A. Using Lemma 2.2, we construct a nonexpansive mapping T 0 :HC such that

T 0 (x):= { z C : G 0 ( z , v ) + z x , v z 0 v C } .

Then, F( T 0 )=VI(C, A 0 ). So, T 0 as T 0 are nonexpansive. Consequently, both mappings T 0 and T 0 are (1/2)-strictly pseudocontractive. Thus, the mapping I T 0 is also Lipschitz continuous with the Lipschitz constant L=2. Then, algorithm (2.1) has the form:

Let z 0 be an arbitrary element in a Hilbert space H, the sequence of iteration { z n } is defined by

{ u n C : G ( u n , y ) + u n z n , y u n 0 , y C , u n 0 C : G 0 ( u n 0 , y ) + u n 0 z n , y u n 0 0 , y C , z n + 1 = P C ( z n β n [ z n u n + z n u n 0 + i = 1 γ i A i ( z n ) + α n z n ] ) z n + 1 = P C ( z n β n [ i = 1 γ i A i ( z n ) + ( 2 + α n ) z n u n u n 0 ] ) , n 0 .
(3.3)

Theorem 3.1 Let C be a nonempty closed convex subset of a real Hilbert space H. Let G:C×C(,+) be a bifunction satisfying (A1)-(A4), let { T i } i = 1 be a sequence of nonself λ i -strictly pseudocontractive mappings from C into H, and let A 0 be a hemicontinuous monotone mapping from C into H such that

i = 1 F( T i )EP(G)VI ( C , A 0 ) .

Assume that { γ i } satisfies condition (2.2), and α n , β n satisfy the following conditions:

α n , β n > 0 , lim n α n = 0 , lim n | α n α n + 1 | α n 2 β n = 0 , n = 0 α n β n = , lim ¯ n β n ( 4 + γ + α n ) 2 α n < 1 .

Then

lim n z n = u i = 1 F( T i )EP(G)VI ( C , A 0 ) ,

where { z n } is defined by (3.3).

References

  1. Browder FE, Petryshyn WV: Construction of fixed points of nonlinear mappings in Hilbert spaces. J. Math. Anal. Appl. 1967, 20: 197–228. 10.1016/0022-247X(67)90085-6

    Article  MathSciNet  Google Scholar 

  2. Takahashi W, Toyota M: Weak convergence theorems for nonexpansive mappings and monotone mappings. J. Optim. Theory Appl. 2003, 118: 417–428. 10.1023/A:1025407607560

    Article  MathSciNet  Google Scholar 

  3. Blum E, Oettli W: From optimization and variational inequalities to equilibrium problems. Math. Stud. 1994, 63: 123–145.

    MathSciNet  Google Scholar 

  4. Oettli W: A remark on vector-valued equilibria and generalized monotonicity. Acta Math. Vietnam. 1997, 22: 215–221.

    MathSciNet  Google Scholar 

  5. Göpfert A, Riahi H, Tammer C, Zalinescu C: Variational Methods in Partially Ordered Spaces. Springer, New York; 2003.

    Google Scholar 

  6. Chadli O, Schaible S, Yao JC: Regularized equilibrium problems with an application to noncoercive hemivariational inequalities. J. Optim. Theory Appl. 2004, 121: 571–596.

    Article  MathSciNet  Google Scholar 

  7. Combettes PL, Hirstoaga SA: Equilibrium programming in Hilbert spaces. J. Nonlinear Convex Anal. 2005, 6(1):117–136.

    MathSciNet  Google Scholar 

  8. Konnov IV, Pinyagina OV: D-gap functions and descent methods for a class of monotone equilibrium problems. Lobachevskii J. Math. 2003, 13: 57–65.

    MathSciNet  Google Scholar 

  9. Stukalov AC: Regularization extragradient method for solving equilibrium programming problems in Hilbert spaces. Ž. Vyčisl. Mat. Mat. Fiz. 2005, 45(9):1538–1554.

    MathSciNet  Google Scholar 

  10. Kim JK, Tuyen TM: Regularization proximal point algorithm for finding a common fixed point of a finite family of nonexpansive mappings in Banach spaces. Fixed Point Theory Appl. 2011, 2011(52):1–10. 10.1186/1687-1812-2011-52

    Article  MathSciNet  Google Scholar 

  11. Konnov IV, Pinyagina OV: D-gap functions for a class of monotone equilibrium problems in Banach spaces. Comput. Methods Appl. Math. 2003, 3: 274–286.

    Article  MathSciNet  Google Scholar 

  12. Mastroeni G: Gap functions for equilibrium problems. J. Glob. Optim. 2003, 27: 411–426. 10.1023/A:1026050425030

    Article  MathSciNet  Google Scholar 

  13. Anh PN, Kim JK: An interior proximal cutting hyperplane method for equilibrium problems. J. Inequal. Appl. 2012., 2012: Article ID 99 10.1186/1029-242X-2012-99

    Google Scholar 

  14. Antipin AS: Equilibrium programming: gradient methods. Autom. Remote Control 1997, 58: 1337–1347.

    MathSciNet  Google Scholar 

  15. Antipin AS: Equilibrium programming: proximal methods. Ž. Vyčisl. Mat. Mat. Fiz. 1997, 37: 1327–1339. Translation in Comput. Math. Math. Phys. 37, 1285–1296 (1997)

    MathSciNet  Google Scholar 

  16. Antipin AS: Solution methods for variational inequalities with coupled constraints. Comput. Math. Math. Phys. 2000, 40: 1239–1254. Translated from Zh. Vychisl. Mat. Mat. Fiz. 40, 1291–1307 (2000)

    MathSciNet  Google Scholar 

  17. Antipin AS: Solving variational inequalities with coupling constraints with the use of differential equations. Differ. Equ. 2000, 36: 1587–1596. Translated from Differ. Uravn. 36, 1443–1451 (2000) 10.1007/BF02757358

    Article  MathSciNet  Google Scholar 

  18. Bounkhel M, Al-Senan BR: An iterative method for nonconvex equilibrium problems. J. Inequal. Pure Appl. Math. 2006., 7(2): Article ID 75

    Google Scholar 

  19. Buong N: Approximation methods for equilibrium problems and common solution for a finite family of inverse-strongly monotone problems in Hilbert spaces. Appl. Math. Sci. 2008, 2: 735–746.

    MathSciNet  Google Scholar 

  20. Chadli O, Konnov IV, Yao JC: Descent methods for equilibrium problems in Banach spaces. Comput. Math. Appl. 2004, 48: 609–616. 10.1016/j.camwa.2003.05.011

    Article  MathSciNet  Google Scholar 

  21. Mastroeni, G: On auxiliary principle for equilibrium problems, Technical Report of the Department of Mathematics of Pisa University, Italy 3.244.1258 (2000)

    Google Scholar 

  22. Moudafi A: Second-order differential proximal methods for equilibrium problems. J. Inequal. Pure Appl. Math. 2003., 4(1): Article ID 18

    Google Scholar 

  23. Moudafi A, Théra M Lecture Notes in Econom. and Math. Systems 477. In Proximal and Dynamical Approaches to Equilibrium Problems. Springer, Berlin; 1999:187–201.

    Google Scholar 

  24. Noor MA, Noor KI: On equilibrium problems. Appl. Math. E-Notes 2004, 4: 125–132.

    MathSciNet  Google Scholar 

  25. Kim JK, Nam YM, Sim JY: Convergence theorem of implicit iterative sequences for a finite family of asymptotically quasi-nonexpansive type mappings. Nonlinear Anal. TMA 2009, 71(12):2839–2848. 10.1016/j.na.2009.06.090

    Article  MathSciNet  Google Scholar 

  26. Kim JK, Cho SY, Qin X: Some results on generalized equilibrium problems involving strictly pseudocontractive mappings. Acta Math. Sci. 2011, 31(5):2041–2057. 10.1016/S0252-9602(11)60380-9

    Article  MathSciNet  Google Scholar 

  27. Kim JK: Strong convergence theorems by hybrid projection methods for equilibrium problems and fixed point problems of the asymptotically quasi-nonexpansive mappings. Fixed Point Theory Appl. 2011. 10.1186/1687-1812-2011-10

    Google Scholar 

  28. Kim JK, Buong N: An iterative method for common solution of a system of equilibrium problems in Hilbert spaces. Fixed Point Theory Appl. 2011., 2011: Article ID 780764 10.1155/2011/780764

    Google Scholar 

  29. Kim JK, Buong N: Regularization inertial proximal point algorithm for monotone hemicontinuous mappings and inverse strongly monotone mappings in Hilbert spaces. J. Inequal. Appl. 2010., 2010: Article ID 451916 10.1155/2010/451916

    Google Scholar 

  30. Kim JK, Anh PN, Nam YM: Strong convergence of an extended extragradient method for equilibrium problems and fixed point problems. J. Korean Math. Soc. 2012, 49(1):187–200. 10.4134/JKMS.2012.49.1.187

    Article  MathSciNet  Google Scholar 

  31. Marino G, Xu HK: Weak and strong convergence theorems for strict pseudo-contractions in Hilbert spaces. J. Math. Anal. Appl. 2007, 329(2):336–346.

    Article  MathSciNet  Google Scholar 

  32. Wang G, Peng J, Lee HJ: Implicit iteration process with mean errors for common fixed point of a family of strictly pseudocontractive maps. Int. J. Math. Anal. 2007, 1: 89–99.

    MathSciNet  Google Scholar 

  33. Takahashi S, Takahashi W: Viscosity approximation methods for equilibrium problems and fixed point problems in Hilbert spaces. J. Math. Anal. Appl. 2007, 331: 506–515. 10.1016/j.jmaa.2006.08.036

    Article  MathSciNet  Google Scholar 

  34. Alvarez F, Attouch H: An inertial proximal method for maximal monotone operators via discretization of a nonlinear oscillator with damping. Set-Valued Anal. 2001, 9: 3–11. 10.1023/A:1011253113155

    Article  MathSciNet  Google Scholar 

  35. Maingé PE: Approximation methods for common fixed points of nonexpansive mappings in Hilbert spaces. J. Math. Anal. Appl. 2007, 325: 469–479. 10.1016/j.jmaa.2005.12.066

    Article  MathSciNet  Google Scholar 

  36. Ceng LC, Yao JC: Hybrid viscosity approximation schemes for equilibrium problems and fixed point problems of infinitely many nonexpansive mappings. Appl. Math. Comput. 2008, 198: 729–741. 10.1016/j.amc.2007.09.011

    Article  MathSciNet  Google Scholar 

  37. Vasin VV, Ageev AL: Incorrect Problems with Priori Information. Nauka, Ekaterenburg; 1993.

    Google Scholar 

  38. Osilike MO, Udomene A: Demiclosedness principle and convergence theorems for strictly pseudocontractive mappings. J. Math. Anal. Appl. 2001, 256: 431–445. 10.1006/jmaa.2000.7257

    Article  MathSciNet  Google Scholar 

  39. Li G, Kim JK: Demiclosedness principle and asymptotic behavior for nonexpansive mappings in metric spaces. Appl. Math. Lett. 2001, 14(5):645–649. 10.1016/S0893-9659(00)00207-X

    Article  MathSciNet  Google Scholar 

  40. Wangkeeree R: An extragradient approximation method for equilibrium problems and fixed point problems of a countable family of nonexpansive mappings. Fixed Point Theory Appl. 2008., 2008: Article ID 134148

    Google Scholar 

  41. Yao Y, Liou YC, Yao JC: A new hybrid iterative algorithm for fixed point problems, variational inequality problems, and mixed equilibrium problems. Fixed Point Theory Appl. 2008., 2008: Article ID 417089

    Google Scholar 

Download references

Acknowledgements

This work was supported by the Basic Science Research Program through the National Research Foundation (NRF) Grant funded by Ministry of Education of the Republic of Korea (2013R1A1A2054617).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jong Kyu Kim.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

The main idea of this paper was proposed by JKK. JKK and NB prepared the manuscript initially and performed all the steps of proof in this research. All authors read and approved the final manuscript.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Kim, J.K., Buong, N. A new iterative method for equilibrium problems and fixed point problems for infinite family of nonself strictly pseudocontractive mappings. Fixed Point Theory Appl 2013, 286 (2013). https://doi.org/10.1186/1687-1812-2013-286

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/1687-1812-2013-286

Keywords