# Strong convergence theorems for equilibrium problems and weak Bregman relatively nonexpansive mappings in Banach spaces

- Ravi P Agarwal
^{1, 2}, - Jia-Wei Chen
^{3}Email author and - Yeol Je Cho
^{4}Email author

**2013**:119

https://doi.org/10.1186/1029-242X-2013-119

© Agarwal et al.; licensee Springer 2013

**Received: **20 September 2012

**Accepted: **26 February 2013

**Published: **20 March 2013

## Abstract

In this paper, a shrinking projection algorithm based on the prediction correction method for equilibrium problems and weak Bregman relatively nonexpansive mappings is introduced and investigated in Banach spaces, and then the strong convergence of the sequence generated by the proposed algorithm is derived under some suitable assumptions. These results are new and develop some recent results in this field.

**MSC:**26B25, 47H09, 47J05, 47J25.

## Keywords

## 1 Introduction

In this paper, without other specifications, let *R* be the set of real numbers, *C* be a nonempty, closed and convex subset of a real reflexive Banach space *E* with the dual space ${E}^{\ast}$. The norm and the dual pair between ${E}^{\ast}$ and *E* are denoted by $\parallel \cdot \parallel $ and $\u3008\cdot ,\cdot \u3009$, respectively. Let $f:E\to R\cup \{+\mathrm{\infty}\}$ be a proper convex and lower semicontinuous function. Denote the domain of *f* by dom*f*, *i.e.*, $domf=\{x\in E:f(x)<+\mathrm{\infty}\}$. The *Fenchel conjugate* of *f* is the function ${f}^{\ast}:{E}^{\ast}\to (-\mathrm{\infty},+\mathrm{\infty}]$ defined by ${f}^{\ast}(\xi )=sup\{\u3008\xi ,x\u3009-f(x):x\in E\}$. Let $T:C\to C$ be a nonlinear mapping. Denote by $F(T)=\{x\in C:Tx=x\}$ the set of fixed points of *T*. A mapping *T* is said to be *nonexpansive* if $\parallel Tx-Ty\parallel \le \parallel x-y\parallel $ for all $x,y\in C$.

where $H:C\times C\to R$ is functional. Denote the set of solutions of the problem (1.1) by $EP(H)$. Since then, various equilibrium problems have been investigated. It is well known that equilibrium problems and their generalizations have been important tools for solving problems arising in the fields of linear or nonlinear programming, variational inequalities, complementary problems, optimization problems, fixed point problems and have been widely applied to physics, structural analysis, management science and economics *etc.* One of the most important and interesting topics in the theory of equilibria is to develop efficient and implementable algorithms for solving equilibrium problems and their generalizations (see, *e.g.*, [2–8] and the references therein). Since the equilibrium problems have very close connections with both the fixed point problems and the variational inequalities problems, finding the common elements of these problems has drawn many people’s attention and has become one of the hot topics in the related fields in the past few years (see, *e.g.*, [9–16] and the references therein).

In 1967, Bregman [17] discovered an elegant and effective technique for using of the so-called Bregman distance function ${D}_{f}$ (see, Section 2, Definition 2.1) in the process of designing and analyzing feasibility and optimization algorithms. This opened a growing area of research in which Bregman’s technique has been applied in various ways in order to design and analyze not only iterative algorithms for solving feasibility and optimization problems, but also algorithms for solving variational inequalities, for approximating equilibria, for computing fixed points of nonlinear mappings and so on (see, *e.g.*, [18–24] and the references therein). In 2005, Butnariu and Resmerita [25] presented Bregman-type iterative algorithms and studied the convergence of the Bregman-type iterative method of solving some nonlinear operator equations.

*E*, respectively:

*E*with ${e}_{n}^{i}\to 0$ and ${proj}_{C}^{f}$ is the Bregman projection with respect to

*f*from

*E*onto a closed and convex subset

*C*. Further, under some suitable conditions, they obtained two strong convergence theorems of maximal monotone operators in a reflexive Banach space. Reich and Sabach [7] also studied the convergence of two iterative algorithms for finitely many Bregman strongly nonexpansive operators in a Banach space. In [15], Reich and Sabach proposed the following algorithms for finding common fixed points of finitely many Bregman firmly nonexpansive operators ${T}_{i}:C\to C$ ($i=1,2,\dots ,N$) in a reflexive Banach space

*E*if ${\bigcap}_{i=1}^{N}F({T}_{i})\ne \mathrm{\varnothing}$:

Under some suitable conditions, they proved that the sequence $\{{x}_{n}\}$ generated by (1.2) converges strongly to ${\bigcap}_{i=1}^{N}F({T}_{i})$ and applied the result to the solution of convex feasibility and equilibrium problems.

Very recently, Chen *et al.* [27] introduced the concept of weak Bregman relatively nonexpansive mappings in a reflexive Banach space and gave an example to illustrate the existence of a weak Bregman relatively nonexpansive mapping and the difference between a weak Bregman relatively nonexpansive mapping and a Bregman relatively nonexpansive mapping. They also proved the strong convergence of the sequences generated by the constructed algorithms with errors for finding a fixed point of weak Bregman relatively nonexpansive mappings and Bregman relatively nonexpansive mappings under some suitable conditions.

This paper is devoted to investigating the shrinking projection algorithm based on the prediction correction method for finding a common element of solutions to the equilibrium problem (1.1) and fixed points to weak Bregman relatively nonexpansive mappings in Banach spaces, and then the strong convergence of the sequence generated by the proposed algorithm is derived under some suitable assumptions.

## 2 Preliminaries

Let $T:C\to C$ be a nonlinear mapping. A point $\omega \in C$ is called an *asymptotic fixed point* of *T* (see [28]) if *C* contains a sequence $\{{x}_{n}\}$ which converges weakly to *ω* such that ${lim}_{n\to \mathrm{\infty}}\parallel T{x}_{n}-{x}_{n}\parallel =0$. A point $\omega \in C$ is called a *strong asymptotic fixed point* of *T* (see [28]) if *C* contains a sequence $\{{x}_{n}\}$ which converges strongly to *ω* such that ${lim}_{n\to \mathrm{\infty}}\parallel T{x}_{n}-{x}_{n}\parallel =0$. We denote the sets of asymptotic fixed points and strong asymptotic fixed points of *T* by $\stackrel{\u02c6}{F}(T)$ and $\tilde{F}(T)$, respectively.

*E*; we denote the strong convergence of $\{{x}_{n}\}$ to $x\in E$ by ${x}_{n}\to x$. For any $x\in int(domf)$, the

*right-hand derivative*of

*f*at

*x*in the direction $y\in E$ is defined by

*f* is called *Gâteaux differentiable* at *x* if, for all $y\in E$, ${lim}_{t\searrow 0}\frac{f(x+ty)-f(x)}{t}$ exists. In this case, ${f}^{\prime}(x,y)$ coincides with $\mathrm{\nabla}f(x)$, the value of the gradient of *f* at *x*. *f* is called *Gâteaux differentiable* if it is Gâteaux differentiable for any $x\in int(domf)$. *f* is called *Fréchet differentiable* at *x* if this limit is attained uniformly for $\parallel y\parallel =1$. We say that *f* is *uniformly Fréchet differentiable* on a subset *C* of *E* if the limit is attained uniformly for $x\in C$ and $\parallel y\parallel =1$.

The Legendre function $f:E\to (-\mathrm{\infty},+\mathrm{\infty}]$ is defined in [18]. From [18], if *E* is a reflexive Banach space, then *f* is the Legendre function if and only if it satisfies the following conditions (L1) and (L2):

(L1) The interior of the domain of *f*, $int(domf)$, is nonempty, *f* is Gâteaux differentiable on $int(domf)$ and $domf=int(domf)$;

(L2) The interior of the domain of ${f}^{\ast}$, $int(dom{f}^{\ast})$, is nonempty, ${f}^{\ast}$ is Gâteaux differentiable on $int(dom{f}^{\ast})$ and $dom{f}^{\ast}=int(dom{f}^{\ast})$.

*E*is reflexive, we know that ${(\mathrm{\nabla}f)}^{-1}=\mathrm{\nabla}{f}^{\ast}$ (see [29]). This, by (L1) and (L2), implies the following equalities:

By Bauschke *et al.* [[18], Theorem 5.4], the conditions (L1) and (L2) also yield that the functions *f* and ${f}^{\ast}$ are strictly convex on the interior of their respective domains. From now on we assume that the convex function $f:E\to (-\mathrm{\infty},+\mathrm{\infty}]$ is Legendre.

We first recall some definitions and lemmas which are needed in our main results.

**Assumption 2.1** Let *C* be a nonempty, closed convex subset of a uniformly convex and uniformly smooth Banach space *E*, and let $H:C\times C\to R$ satisfy the following conditions (C1)-(C4):

(C1) $H(x,x)=0$ for all $x\in C$;

(C2) *H* is monotone, *i.e.*, $H(x,y)+H(y,x)\le 0$ for all $x,y\in C$;

(C4) for all $x\in C$, $H(x,\cdot )$ is convex and lower semicontinuous.

is called *the Bregman distance* with respect to *f*.

**Remark 2.1** [15]

- (1)the
*three point identity*, for any $x\in domf$ and $y,z\in int(domf)$,${D}_{f}(x,y)+{D}_{f}(y,z)-{D}_{f}(x,z)=\u3008\mathrm{\nabla}f(z)-\mathrm{\nabla}f(y),x-y\u3009;$ - (2)the
*four point identity*, for any $y,\omega \in domf$ and $x,z\in int(domf)$,${D}_{f}(y,x)-{D}_{f}(y,z)-{D}_{f}(\omega ,x)+{D}_{f}(\omega ,z)=\u3008\mathrm{\nabla}f(z)-\mathrm{\nabla}f(x),y-\omega \u3009.$

**Definition 2.2** [17]

**Remark 2.2**

- (1)
If

*E*is a Hilbert space and $f(y)=\frac{1}{2}{\parallel x\parallel}^{2}$ for all $x\in E$, then the Bregman projection ${proj}_{C}^{f}(x)$ is reduced to the metric projection of*x*onto*C*; - (2)If
*E*is a smooth Banach space and $f(y)=\frac{1}{2}{\parallel x\parallel}^{2}$ for all $x\in E$, then the Bregman projection ${proj}_{C}^{f}(x)$ is reduced to the generalized projection ${\mathrm{\Pi}}_{C}(x)$ (see [11, 28]), which is defined by$\varphi ({\mathrm{\Pi}}_{C}(x),x)=\underset{y\in C}{min}\varphi (y,x),$

where $\varphi (y,x)={\parallel y\parallel}^{2}-2\u3008y,J(x)\u3009+{\parallel x\parallel}^{2}$, *J* is the normalized duality mapping from *E* to ${2}^{{E}^{\ast}}$.

*C*be a nonempty, closed and convex set of dom

*f*. The operator $T:C\to int(domf)$ with $F(T)\ne \mathrm{\varnothing}$ is called:

- (1)
*quasi-Bregman nonexpansive*if${D}_{f}(u,Tx)\le {D}_{f}(u,x),\phantom{\rule{1em}{0ex}}\mathrm{\forall}x\in C,u\in F(T);$ - (2)
*Bregman relatively nonexpansive*if $\stackrel{\u02c6}{F}(T)=F(T)$ and${D}_{f}(u,Tx)\le {D}_{f}(u,x),\phantom{\rule{1em}{0ex}}\mathrm{\forall}x\in C,u\in F(T);$ - (3)
*Bregman firmly nonexpansive*if$\u3008\mathrm{\nabla}f(Tx)-\mathrm{\nabla}f(Ty),Tx-Ty\u3009\le \u3008\mathrm{\nabla}f(x)-\mathrm{\nabla}f(y),Tx-Ty\u3009,\phantom{\rule{1em}{0ex}}\mathrm{\forall}x,y\in C,$

- (4)
*a weak Bregman relatively nonexpansive mapping*with $F(T)\ne \mathrm{\varnothing}$ if $\tilde{F}(T)=F(T)$ and${D}_{f}(u,Tx)\le {D}_{f}(u,x),\phantom{\rule{1em}{0ex}}\mathrm{\forall}x\in C,u\in F(T).$

**Definition 2.4** [4]

*resolvent*of

*H*is the operator ${Res}_{H}^{f}:E\to {2}^{C}$ defined by

**Definition 2.5** [21]

*f*is called:

- (1)
*totally convex*at $x\in int(domf)$ if its modulus of total convexity at*x*, that is, the function ${\nu}_{f}:int(domf)\times [0,+\mathrm{\infty})\to [0,+\mathrm{\infty})$ defined by${\nu}_{f}(x,t):=inf\{{D}_{f}(y,x):y\in domf,\parallel y-x\parallel =t\},$

- (2)
*totally convex*if it is totally convex at every point $x\in int(domf)$; - (3)
*totally convex on bounded sets*if ${\nu}_{f}(B,t)$ is positive for any nonempty bounded subset*B*of*E*and $t>0$, where the modulus of total convexity of the function*f*on the set*B*is the function ${\nu}_{f}:int(domf)\times [0,+\mathrm{\infty})\to [0,+\mathrm{\infty})$ defined by${\nu}_{f}(B,t):=inf\{{\nu}_{f}(x,t):x\in B\cap domf\}.$

- (1)
*cofinite*if $dom{f}^{\ast}={E}^{\ast}$; - (2)
*coercive*if ${lim}_{\parallel x\parallel \to +\mathrm{\infty}}(f(x)/\parallel x\parallel )=+\mathrm{\infty}$; - (3)
*sequentially consistent*if for any two sequences $\{{x}_{n}\}$ and $\{{y}_{n}\}$ in*E*such that $\{{x}_{n}\}$ is bounded,$\underset{n\to \mathrm{\infty}}{lim}{D}_{f}({y}_{n},{x}_{n})=0\phantom{\rule{1em}{0ex}}\Rightarrow \phantom{\rule{1em}{0ex}}\underset{n\to \mathrm{\infty}}{lim}\parallel {y}_{n}-{x}_{n}\parallel =0.$

**Lemma 2.1** [[26], Proposition 2.3]

*If* $f:E\to (-\mathrm{\infty},+\mathrm{\infty}]$ *is Fréchet differentiable and totally convex*, *then* *f* *is cofinite*.

**Lemma 2.2** [[25], Theorem 2.10]

*Let*$f:E\to (-\mathrm{\infty},+\mathrm{\infty}]$

*be a convex function whose domain contains at least two points*.

*Then the following statements hold*:

- (1)
*f**is sequentially consistent if and only if it is totally convex on bounded sets*; - (2)
*If**f**is lower semicontinuous*,*then**f**is sequentially consistent if and only if it is uniformly convex on bounded sets*; - (3)
*If**f**is uniformly strictly convex on bounded sets*,*then it is sequentially consistent and the converse implication holds when**f**is lower semicontinuous*,*Fréchet differentiable on its domain and the Fréchet derivative*∇*f**is uniformly continuous on bounded sets*.

**Lemma 2.3** [[30], Proposition 2.1]

*Let* $f:E\to R$ *be uniformly Fréchet differentiable and bounded on bounded subsets of* *E*. *Then* ∇*f* *is uniformly continuous on bounded subsets of* *E* *from the strong topology of* *E* *to the strong topology of* ${E}^{\ast}$.

**Lemma 2.4** [[26], Lemma 3.1]

*Let* $f:E\to R$ *be a Gâteaux differentiable and totally convex function*. *If* ${x}_{0}\in E$ *and the sequence* $\{{D}_{f}({x}_{n},{x}_{0})\}$ *is bounded*, *then the sequence* $\{{x}_{n}\}$ *is also bounded*.

**Lemma 2.5** [[26], Proposition 2.2]

*Let* $f:E\to R$ *be a Gâteaux differentiable and totally convex function*, ${x}_{0}\in E$ *and let* *C* *be a nonempty*, *closed convex subset of* *E*. *Suppose that the sequence* $\{{x}_{n}\}$ *is bounded and any weak subsequential limit of* $\{{x}_{n}\}$ *belongs to* *C*. *If* ${D}_{f}({x}_{n},{x}_{0})\le {D}_{f}({proj}_{C}^{f}({x}_{0}),{x}_{0})$ *for any* $n\in N$, *then* ${\{{x}_{n}\}}_{n=1}^{\mathrm{\infty}}$ *converges strongly to* ${proj}_{C}^{f}({x}_{0})$.

**Lemma 2.6** [[27], Proposition 2.17]

*Let* $f:E\to (-\mathrm{\infty},+\mathrm{\infty}]$ *be the Legendre function*. *Let* *C* *be a nonempty*, *closed convex subset of* $int(domf)$ *and* $T:C\to C$ *be a quasi*-*Bregman nonexpansive mapping with respect to* *f*. *Then* $F(T)$ *is closed and convex*.

**Lemma 2.7** [[27], Lemma 2.18]

*Let*$f:E\to (-\mathrm{\infty},+\mathrm{\infty}]$

*be Gâteaux differentiable and proper convex lower semicontinuous*.

*Then*,

*for all*$z\in E$,

*where* ${\{{x}_{i}\}}_{i=1}^{N}\subset E$ *and* ${\{{t}_{i}\}}_{i=1}^{N}\subset (0,1)$ *with* ${\sum}_{i=1}^{N}{t}_{i}=1$.

**Lemma 2.8** [[25], Corollary 4.4]

*Let*$f:E\to (-\mathrm{\infty},+\mathrm{\infty}]$

*be Gâteaux differentiable and totally convex on*$int(domf)$.

*Let*$x\in int(domf)$

*and*$C\subset int(domf)$

*be a nonempty*,

*closed convex set*.

*If*$\stackrel{\u02c6}{x}\in C$,

*then the following statements are equivalent*:

- (1)
*the vector*$\stackrel{\u02c6}{x}$*is the Bregman projection of**x**onto**C**with respect to**f*; - (2)
*the vector*$\stackrel{\u02c6}{x}$*is the unique solution of the variational inequality*:$\u3008\mathrm{\nabla}f(x)-\mathrm{\nabla}f(z),z-y\u3009\ge 0,\phantom{\rule{1em}{0ex}}\mathrm{\forall}y\in C;$ - (3)
*the vector*$\stackrel{\u02c6}{x}$*is the unique solution of the inequality*:${D}_{f}(y,z)+{D}_{f}(z,x)\le {D}_{f}(y,x),\phantom{\rule{1em}{0ex}}\mathrm{\forall}y\in C.$

**Lemma 2.9** [[7], Lemmas 1 and 2]

*Let*$f:E\to (-\mathrm{\infty},+\mathrm{\infty}]$

*be a coercive Legendre function*.

*Let*

*C*

*be a nonempty*,

*closed and convex subset of*$int(domf)$.

*Assume that*$H:C\times C\to R$

*satisfies Assumption*2.1.

*Then the following results hold*:

- (1)${Res}_{H}^{f}$
*is single*-*valued and*$dom({Res}_{H}^{f})=E$; - (2)${Res}_{H}^{f}$
*is Bregman firmly nonexpansive*; - (3)$EP(H)$
*is a closed and convex subset of**C**and*$EP(H)=F({Res}_{H}^{f})$; - (4)
*for all*$x\in E$*and for all*$u\in F({Res}_{H}^{f})$,${D}_{f}(u,{Res}_{H}^{f}(x))+{D}_{f}({Res}_{H}^{f}(x),x)\le {D}_{f}(u,x).$

**Lemma 2.10** [[31], Proposition 5]

*Let* $f:E\to R$ *be a Legendre function such that* $\mathrm{\nabla}{f}^{\ast}$ *is bounded on bounded subsets of* $intdom{f}^{\ast}$. *Let* $x\in E$. *If* $\{{D}_{f}(x,{x}_{n})\}$ *is bounded*, *then the sequence* $\{{x}_{n}\}$ *is bounded too*.

## 3 Main results

In this section, we will introduce a new shrinking projection algorithm based on the prediction correction method for finding a common element of solutions to the equilibrium problem (1.1) and fixed points to weak Bregman relatively nonexpansive mappings in Banach spaces, and then the strong convergence of the sequence generated by the proposed algorithm is proved under some suitable conditions.

Let $\{{\alpha}_{n}\}$ and $\{{\beta}_{n}\}$ be the sequences in $[0,1]$ such that ${lim}_{n\to \mathrm{\infty}}{\alpha}_{n}=0$ and ${lim\hspace{0.17em}inf}_{n\to \mathrm{\infty}}(1-{\alpha}_{n}){\beta}_{n}>0$. We propose the following shrinking projection algorithm based on the prediction correction method.

**Algorithm 3.1** Step 1: Select an arbitrary starting point ${x}_{0}\in C$, let ${Q}_{0}=C$ and ${C}_{0}=\{z\in C:{D}_{f}(z,{u}_{0})\le {D}_{f}(z,{x}_{0})\}$.

**Theorem 3.1** *Let* *C* *be a nonempty*, *closed and convex subset of a real reflexive Banach space* *E*, $f:E\to R$ *be a coercive Legendre function which is bounded*, *uniformly Fréchet differentiable and totally convex on a bounded subset of* *E*, *and* $\mathrm{\nabla}{f}^{\ast}$ *be bounded on bounded subsets of* ${E}^{\ast}$. *Let* $H:C\times C\to R$ *satisfy Assumption * 2.1 *and* $T:C\to C$ *be a weak Bregman relatively nonexpansive mapping such that* $EP(H)\cap F(T)\ne \mathrm{\varnothing}$. *Then the sequence* $\{{x}_{n}\}$ *generated by Algorithm* 3.1 *converges strongly to the point* ${proj}_{EP(H)\cap F(T)}^{f}({x}_{0})$, *where* ${proj}_{EP(H)\cap F(T)}^{f}({x}_{0})$ *is the Bregman projection of* *C* *onto* $EP(H)\cap F(T)$.

To prove Theorem 3.1, we need the following lemmas.

**Lemma 3.1** *Assume that* $EP(H)\cap F(T)\subseteq {C}_{n}\cap {Q}_{n}$ *for all* $n\ge 0$. *Then the sequence* $\{{x}_{n}\}$ *is bounded*.

*Proof*Since $\u3008\mathrm{\nabla}f({x}_{0})-\mathrm{\nabla}f({x}_{n}),v-{x}_{n}\u3009\le 0$ for all $v\in {Q}_{n}$, it follows from Lemma 2.8 that ${x}_{n}={proj}_{{Q}_{n}}^{f}({x}_{0})$ and so, by ${x}_{n+1}={proj}_{{C}_{n}\cap {Q}_{n}}^{f}({x}_{0})\in {Q}_{n}$, we have

Therefore, $\{{D}_{f}({x}_{n},{x}_{0})\}$ is bounded. Moreover, $\{{x}_{n}\}$ is bounded and so are $\{T({x}_{n})\}$, $\{{y}_{n}\}$, $\{{z}_{n}\}$. This completes the proof. □

**Lemma 3.2** *Assume that* $EP(H)\cap F(T)\subseteq {C}_{n}\cap {Q}_{n}$ *for all* $n\ge 0$. *Then the sequence* $\{{x}_{n}\}$ *is a Cauchy sequence*.

*Proof*By the proof of Lemma 3.1, we know that $\{{D}_{f}({x}_{n},{x}_{0})\}$ is bounded. It follows from (3.2) that ${lim}_{n\to \mathrm{\infty}}{D}_{f}({x}_{n},{x}_{0})$ exists. From ${x}_{m}\in {Q}_{m-1}\subseteq {Q}_{n}$ for all $m>n$ and Lemma 2.8, one has

*f*is totally convex on bounded subsets of

*E*, by Definition 2.6, Lemma 2.2 and (3.3), we obtain

Thus $\{{x}_{n}\}$ is a Cauchy sequence and so ${lim}_{n\to \mathrm{\infty}}\parallel {x}_{n+1}-{x}_{n}\parallel =0$. This completes the proof. □

**Lemma 3.3** *Assume that* $EP(H)\cap F(T)\subseteq {C}_{n}\cap {Q}_{n}$ *for all* $n\ge 0$. *Then the sequence* $\{{x}_{n}\}$ *converges strongly to a point in* $EP(H)\cap F(T)$.

*Proof*From Lemma 3.2, the sequence $\{{x}_{n}\}$ is a Cauchy sequence. Without loss of generality, let ${x}_{n}\to \stackrel{\u02c6}{\omega}\in C$. Since

*f*is uniformly Fréchet differentiable on bounded subsets of

*E*, it follows from Lemma 2.2 that ∇

*f*is norm-to-norm uniformly continuous on bounded subsets of

*E*. Hence, by (3.4), we have

*f*is a coercive Legendre function which is bounded, uniformly Fréchet differentiable and totally convex on a bounded subset of

*E*, it follows from Lemma 2.3 that

*f*is continuous on

*E*and ∇

*f*is uniformly continuous on bounded subsets of

*E*from the strong topology of

*E*to the strong topology of ${E}^{\ast}$. Therefore, we have

which shows that $\stackrel{\u02c6}{\omega}\in EP(H)$.

Moreover, we have that ${lim}_{n\to \mathrm{\infty}}\parallel {x}_{n}-T({x}_{n})\parallel =0$. This together with ${x}_{n}\to \stackrel{\u02c6}{\omega}$ implies that $\stackrel{\u02c6}{\omega}\in \tilde{F}(T)$. In view of $\tilde{F}(T)=F(T)$, one has $\stackrel{\u02c6}{\omega}\in EP(H)\cap F(T)$. Therefore, the sequence $\{{x}_{n}\}$ generated by Algorithm 3.1 converges strongly to a point $\stackrel{\u02c6}{\omega}$ in $EP(H)\cap F(T)$. This completes the proof. □

Now, we prove Theorem 3.1 by using lemmas.

*Proof of Theorem 3.1* From Lemmas 2.6 and 2.9, it follows that $EP(H)\cap F(T)$ is a nonempty, closed and convex subset of *E*. Clearly, ${C}_{n}$ and ${Q}_{n}$ are closed and convex and so ${C}_{n}\cap {Q}_{n}$ are closed and convex for all $n\ge 0$.

which implies that $\omega \in {C}_{n}$ and so $EP(H)\cap F(T)\subseteq {C}_{n}$ for all $n\ge 0$.

This together with $EP(H)\cap F(T)\ne \mathrm{\varnothing}$ yields that ${C}_{n}\cap {Q}_{n}$ is a nonempty, closed convex subset of *C* for all $n\ge 0$. Thus $\{{x}_{n}\}$ is well defined and, from both Lemmas 3.2 and 3.3, the sequence $\{{x}_{n}\}$ is a Cauchy sequence and converges strongly to a point $\stackrel{\u02c6}{\omega}$ of $EP(H)\cap F(T)$.

Thus, by Lemma 2.5, we have ${x}_{n}\to {proj}_{EP(H)\cap F(T)}^{f}({x}_{0})$ as $n\to \mathrm{\infty}$. Therefore, the sequence $\{{x}_{n}\}$ converges strongly to the point ${proj}_{EP(H)\cap F(T)}^{f}({x}_{0})$. This completes the proof. □

**Remark 3.1**(1) If $f(x)=\frac{1}{2}{\parallel x\parallel}^{2}$ for all $x\in E$, then the weak Bregman relatively nonexpansive mapping is reduced to the weak relatively nonexpansive mapping defined by Su

*et al.*[32], that is,

*T*is called a

*weak relatively nonexpansive mapping*if the following conditions are satisfied:

*J*is the normalized duality mapping from

*E*to ${2}^{{E}^{\ast}}$;

- (2)
If $f(x)=\frac{1}{2}{\parallel x\parallel}^{2}$ for all $x\in E$, then Algorithm 3.1 is reduced to the following iterative algorithm.

**Algorithm 3.2** Step 1: Select an arbitrary starting point ${x}_{0}\in C$, let ${Q}_{0}=C$ and ${C}_{0}=\{z\in C:\varphi (z,{u}_{0})\le \varphi (z,{x}_{0})\}$.

- (3)
Particularly, if $EP(H)=C$, then Algorithm 3.2 is reduced to the following iterative algorithm.

**Algorithm 3.3** Step 1: Select an arbitrary starting point ${x}_{0}\in C$, let ${Q}_{0}=C$ and ${C}_{0}=\{z\in C:\varphi (z,{u}_{0})\le \varphi (z,{x}_{0})\}$.

- (4)
If $Tx=x$ for all $x\in C$, then, by Algorithm 3.3, we can get the following modified Mann iteration algorithm for the equilibrium problem (1.1).

**Algorithm 3.4** Step 1: Select an arbitrary starting point ${x}_{0}\in C$, let ${Q}_{0}=C$ and ${C}_{0}=\{z\in C:\varphi (z,{u}_{0})\le \varphi (z,{x}_{0})\}$.

If $f(x)=\frac{1}{2}{\parallel x\parallel}^{2}$ for all $x\in E$, then, by Theorem 3.1 and Remark 3.1, the following results hold.

**Corollary 3.1** *Let* *C* *be a nonempty*, *closed convex subset of a real reflexive Banach space E*. *Suppose that* $H:C\times C\to R$ *satisfies Assumption * 2.1 *and* $T:C\to C$ *is a weak relatively nonexpansive mapping such that* $EP(H)\cap F(T)\ne \mathrm{\varnothing}$. *Then the sequence* $\{{x}_{n}\}$ *generated by Algorithm* 3.2 *converges strongly to the point* ${\mathrm{\Pi}}_{EP(H)\cap F(T)}({x}_{0})$, *where* ${\mathrm{\Pi}}_{EP(H)\cap F(T)}({x}_{0})$ *is the generalized projection of* *C* *onto* $EP(H)\cap F(T)$.

**Corollary 3.2** *Let* *C* *be a nonempty*, *closed convex subset of a real reflexive Banach space E*. *Let* $T:C\to C$ *be a weak relatively nonexpansive mapping such that* $F(T)\ne \mathrm{\varnothing}$. *Then the sequence* $\{{x}_{n}\}$ *generated by Algorithm* 3.3 *converges strongly to the point* ${\mathrm{\Pi}}_{F(T)}^{f}({x}_{0})$, *where* ${\mathrm{\Pi}}_{F(T)}({x}_{0})$ *is the generalized projection of* *C* *onto* $F(T)$.

**Corollary 3.3** *Let* *C* *be a nonempty*, *closed convex subset of a real reflexive Banach space E*. *Suppose that* $H:C\times C\to R$ *satisfies Assumption * 2.1 *such that* $EP(H)\ne \mathrm{\varnothing}$. *Then the sequence* $\{{x}_{n}\}$ *generated by Algorithm* 3.4 *converges strongly to the point* ${\mathrm{\Pi}}_{EP(H)}({x}_{0})$, *where* ${\mathrm{\Pi}}_{EP(H)}({x}_{0})$ *is the generalized projection of* *C* *onto* $EP(H)$.

**Remark 3.2**

- (1)
It is well known that any closed and firmly nonexpansive-type mapping (see [11, 33]) is a weak Bregman relatively nonexpansive mapping whenever $f(x)=\frac{1}{2}{\parallel x\parallel}^{2}$ for all $x\in E$. If ${\beta}_{n}\equiv 1$ for all $n\ge 0$ and

*E*is a uniformly convex and uniformly smooth Banach space, then Corollary 3.2 improves [[11], Corollary 3.1]; - (2)
If ${\alpha}_{n}\equiv 0$ for all $n\ge 0$ and

*E*is a uniformly convex and uniformly smooth Banach space, then Corollary 3.2 is reduced to [[32], Theorem 3.1]; - (3)
If ${\beta}_{n}\equiv 1-{\beta}_{n}^{\prime}$ for all $n\ge 0$, ${\beta}_{n}^{\prime}\in [0,1]$, $f(x)=\frac{1}{2}{\parallel x\parallel}^{2}$ for all $x\in E$ and

*E*is a uniformly convex and uniformly smooth Banach space, then Corollary 3.1 improves [[11], Theorem 4.1].

## Declarations

### Acknowledgements

The authors are indebted to the referees and the associate editor for their insightful and pertinent comments on an earlier version of the work. The second author (Jiawei Chen) was supported by the Natural Science Foundation of China and the Fundamental Research Fund for the Central Universities, the third author (Yeol Je Cho) was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant Number: 2012-0008170).

## Authors’ Affiliations

## References

- Blum E, Oettli W: From optimization and variational inequalities to equilibrium problems.
*Math. Stud.*1994, 63: 123–145.MathSciNetGoogle Scholar - Agarwal RP, Chen JW, Cho YJ, Wan Z: Stability analysis for parametric generalized vector quasi-variational-like inequality problems.
*J. Inequal. Appl.*2012., 2012: Article ID 57Google Scholar - Butnariu D, Iusem AN, Zalinescu C: On uniform convexity, total convexity and convergence of the proximal point and outer Bregman projection algorithms in Banach spaces.
*J. Convex Anal.*2003, 10: 35–61.MathSciNetGoogle Scholar - Combettes PL, Hirstoaga SA: Equilibrium programming in Hilbert spaces.
*J. Nonlinear Convex Anal.*2005, 6: 117–136.MathSciNetGoogle Scholar - Eckstein I: Nonlinear proximal point algorithms using Bregman function, with applications to convex programming.
*Math. Oper. Res.*1993, 18: 202–226. 10.1287/moor.18.1.202MathSciNetView ArticleGoogle Scholar - Kiwiel KC: Proximal minimization methods with generalized Bregman functions.
*SIAM J. Control Optim.*1997, 35: 1142–1168. 10.1137/S0363012995281742MathSciNetView ArticleGoogle Scholar - Reich S, Sabach S: Two strong convergence theorems for Bregman strongly nonexpansive operators in reflexive Banach spaces.
*Nonlinear Anal.*2010, 73: 122–135. 10.1016/j.na.2010.03.005MathSciNetView ArticleGoogle Scholar - Reich S, Sabach S: Existence and approximation of fixed points of Bregman firmly nonexpansive mappings in reflexive Banach spaces. In
*Fixed-Point Algorithms for Inverse Problems in Science and Engineering*. Springer, New York; 2011.Google Scholar - Chen JW, Cho YJ, Wan Z: Shrinking projection algorithms for equilibrium problems with a bifunction defined on the dual space of a Banach space.
*Fixed Point Theory Appl.*2011., 2011: Article ID 91Google Scholar - Chen JW, Wan Z, Cho YJ: Levitin-Polyak well-posedness by perturbations for systems of set-valued vector quasi-equilibrium problems.
*Math. Methods Oper. Res.*2013, 77: 33–64. 10.1007/s00186-012-0414-5MathSciNetView ArticleGoogle Scholar - Chen JW, Wan Z, Zou Y: Strong convergence theorems for firmly nonexpansive-type mappings and equilibrium problems in Banach spaces.
*Optimization*2011. doi:10.1080/02331934.2011.626779Google Scholar - Cho YJ, Kang JI, Sadaati R: Fixed points and stability of additive functional equations on Banach algebras.
*J. Comput. Anal. Appl.*2012, 14: 1103–1111.MathSciNetGoogle Scholar - Cho YJ, Kim JK, Dragomir SS 1. In
*Inequality Theory and Applications*. Nova Science Publishers, New York; 2002.Google Scholar - Cho YJ, Qin XL: Systems of generalized nonlinear variational inequalities and its projection methods.
*Nonlinear Anal.*2008, 69: 4443–4451. 10.1016/j.na.2007.11.001MathSciNetView ArticleGoogle Scholar - Reich S, Sabach S: A projection method for solving nonlinear problems in reflexive Banach spaces.
*J. Fixed Point Theory Appl.*2011. doi:10.1007/s11784–010–0037–5Google Scholar - Yao Y, Cho YJ, Liou YC: Algorithms of common solutions for variational inclusions, mixed equilibrium problems and fixed point problems.
*Eur. J. Oper. Res.*2011, 212: 242–250. 10.1016/j.ejor.2011.01.042MathSciNetView ArticleGoogle Scholar - Bregman LM: The relaxation method for finding common points of convex sets and its application to the solution of problems in convex programming.
*U.S.S.R. Comput. Math. Math. Phys.*1967, 7: 200–217.View ArticleGoogle Scholar - Bauschke HH, Borwein JM, Combettes PL: Essential smoothness, essential strict convexity, and Legendre functions in Banach spaces.
*Commun. Contemp. Math.*2001, 3: 615–647. 10.1142/S0219199701000524MathSciNetView ArticleGoogle Scholar - Bauschke HH, Borwein JM, Combettes PL: Bregman monotone optimization algorithms.
*SIAM J. Control Optim.*2003, 42: 596–636. 10.1137/S0363012902407120MathSciNetView ArticleGoogle Scholar - Bauschke HH, Combettes PL: Construction of best Bregman approximation in reflexive Banach spaces.
*Proc. Am. Math. Soc.*2003, 131: 3757–3766. 10.1090/S0002-9939-03-07050-3MathSciNetView ArticleGoogle Scholar - Butnariu D, Iusem AN Applied Optimization 40. In
*Totally Convex Functions for Fixed Points Computation and Infinite Dimensional Optimization*. Kluwer Academic, Dordrecht; 2000.View ArticleGoogle Scholar - Reich S: A weak convergence theorem for the alternating method with Bregman distances. Lect. Not. Pure Appl. Math. 178.
*Theory and Applications of Nonlinear Operators of Accretive and Monotone Type*1996, 313–318.Google Scholar - Resmerita E: On total convexity, Bregman projections and stability in Banach spaces.
*J. Convex Anal.*2004, 11: 1–16.MathSciNetGoogle Scholar - Solodov MV, Svaiter BF: An inexact hybrid generalized proximal point algorithm and some new results on the theory of Bregman functions.
*Math. Oper. Res.*2000, 25: 214–230. 10.1287/moor.25.2.214.12222MathSciNetView ArticleGoogle Scholar - Butnariu D, Resmerita E: Bregman distances, totally convex functions, and a method for solving operator equations in Banach spaces.
*Abstr. Appl. Anal.*2006, 2006: 1–39.MathSciNetView ArticleGoogle Scholar - Reich S, Sabach S: Two strong convergence theorems for a proximal method in reflexive Banach spaces.
*Numer. Funct. Anal. Optim.*2010, 31: 22–44. 10.1080/01630560903499852MathSciNetView ArticleGoogle Scholar - Chen JW, Wan Z, Yuan L,
*et al*.: Approximation of fixed points of weak Bregman relatively nonexpansive mappings in Banach spaces.*Int. J. Math. Math. Sci.*2011, 2011: 1–23.MathSciNetGoogle Scholar - Alber YI: Generalized projection operators in Banach spaces: properties and applications. 1.
*Functional Differential Equations*1993, 1–21. Proceedings of the Israel Seminar Ariel, IsraelGoogle Scholar - Bonnans JF, Shapiro A:
*Perturbation Analysis of Optimization Problem*. Springer, New York; 2000.View ArticleGoogle Scholar - Reich S, Sabach S: A strong convergence theorem for a proximal-type algorithm in reflexive Banach spaces.
*J. Nonlinear Convex Anal.*2009, 10: 471–485.MathSciNetGoogle Scholar - Kassay G, Reich S, Sabach S: Iterative methods for solving systems of variational inequalities in reflexive Banach spaces.
*SIAM J. Optim.*2011, 21: 1319–1344. 10.1137/110820002MathSciNetView ArticleGoogle Scholar - Su Y, Gao J, Zhou H: Monotone CQ algorithm of fixed points for weak relatively nonexpansive mappings and applications.
*J. Math. Res. Expo.*2007, 28: 957–967.MathSciNetGoogle Scholar - Takahashi W:
*Nonlinear Functional Analysis-Fixed Point Theory and Its Applications*. Yokohama Publishers, Yokohama; 2000.Google Scholar

## Copyright

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