1 Introduction

Let T be a mapping with domain \(D(T)\) and range \(R(T)\) in a Banach space E. Then T is called nonexpansive if

$$\|Tx-Ty\|\leq\|x-y\| $$

for all \(x,y\in D(T)\). The fixed point set of T is denoted by \(F(T):= \{x\in K; T x = x\}\).

In 2010, Aoyama et al. [1] introduced a class of λ-hybrid mappings, that is, a mapping T is called a λ-hybrid mapping in Hilbert space H if

$$\|Tx-Ty\|^{2}\leq\|x-y\|^{2}+2(1-\lambda)\langle x-Tx,y-Ty \rangle $$

for all \(x,y\in D(T)\). They showed a fixed point theorem and an ergodic theorem for such a mapping. Clearly, a nonexpansive mapping is a 1-hybrid mapping. In 2011, Aoyama and Kohsaka [2] also introduced the concept of α-nonexpansive mapping, that is, a mapping T is called α-nonexpansive if \(\alpha<1\) and

$$\|Tx-Ty\|^{2} \leq\alpha\|Tx-y\|+\alpha\|Ty-x\|+(1-2\alpha)\|x-y\| $$

for all \(x,y\in D(T)\). Obviously, a nonexpansive mapping is 0-nonexpansive and a λ-hybrid mapping is \(\frac{1-\lambda }{2-\lambda}\)-nonexpansive if \(\lambda<2\) in a Hilbert space H (for more details, see [2]).

The following classical result for nonexpansive mappings was showed to still hold for α-nonexpansive mappings in a uniformly convex Banach space E.

Theorem 1.1

([2])

Let C be a nonempty and closed convex subset of uniformly convex Banach space E and \(T:C\to C\) be an α-nonexpansive mapping. Then \(F(T)\ne\emptyset\) if and only if \(\{T^{n}x\}\) is bounded for some \(x \in C\).

Very recently, Bachar and Khamsi [3] introduced the concept of a monotone nonexpansive mapping in a Banach space E endowed with the partial order ‘≤’ and investigated common approximate fixed points of monotone nonexpansive semigroups. A mapping \(T:D(T)\to R(T)\) is called monotone nonexpansive if T is monotone (\(Tx\leq Ty\) whenever \(x\leq y\)) and

$$\|Tx-Ty\|\leq\|x-y\| $$

for all \(x,y\in D(T)\) with \(x\leq y\). Clearly, a monotone nonexpansive mapping may be discontinuous.

In this paper, we show the following existence theorem of fixed points for a monotone nonexpansive mapping T.

Theorem 1.2

Let K be a nonempty and closed convex subset of a uniformly convex Banach space \((E,\leq)\) and \(T : K\to K\) be a monotone nonexpansive mapping. Assume that there exists \(x\in K\) such that \(x\leq Tx\) (or \(Tx\leq x\)) and the sequence \(\{T^{n}x\}\) is bounded. Then \(F(T)\ne\emptyset\) and \(x\leq y^{*}\) (or \(y^{*}\leq x\)) for some \(y^{*}\in F(T)\).

In order to finding a fixed point of a nonexpansive mapping T, Mann [4] introduced the following iteration scheme which is referred to as the Mann iteration: for any \(x_{1}\in D(T)\),

$$ x_{n+1}=\beta_{n}x_{n}+(1- \beta_{n})Tx_{n} $$
(1.1)

for each \(n\geq1\), where \(\beta_{n}\in[0,1]\) is a sequence with some conditions. Subsequently, many mathematical workers have been investigated the convergence of the Mann iteration and its modified version for nonexpansive mappings and pseudo-contractions. For example, see [514]. However, there are not many convergence theorems of such an iteration in an ordered Banach space \((E,\leq)\). Recently, Dehaish and Khamsi [15] obtained the weak convergence of the Mann iteration for a monotone nonexpansive mapping provided \(\alpha _{n}\in[a,b]\subset(0,1)\). But their results do not entail \(\beta _{n}=\frac{1}{n+1}\).

Motivated by the above results, we consider the weak convergence of the Mann iteration scheme for a monotone nonexpansive mapping T under the condition

$$\sum_{n=1}^{\infty}\beta_{n}(1- \beta_{n})=\infty, $$

which contain \(\beta_{n}=\frac{1}{n+1}\) as a special case.

2 Preliminaries and basic results

Let P be a closed convex cone of a real Banach space E. A partial order ‘≤’ with respect to P in E is defined as follows:

$$x\leq y \quad (x< y )\quad \mbox{if and only if} \quad y-x\in P\quad ( y-x\in P \mbox{ and }x\ne y) $$

for all \(x,y\in E\).

Throughout this paper, let E be a Banach space with the norm ‘\(\| \cdot\|\)’ and the partial order ‘≤’. Let \(F(T)=\{x\in H: Tx=x\}\) denote the set of all fixed points of a mapping T. An order interval \([x,y]\) for all \(x,y\in E\) is given by

$$ [x,y]=\{z\in E: x\leq z\leq y\}. $$
(2.1)

Obviously, the order interval \([x,y]\) is closed and convex. In fact, let \(z_{1},z_{2}\in[x,y]\). Then \(z_{1}-x\in P\), \(z_{2}-x\in P\), \(y-z_{1}\in P\), and \(y-z_{2}\in P\); and so, for any \(t\in(0,1)\),

$$\begin{aligned}& tz_{1}+(1-t)z_{2}-x=t(z_{1}-x)+(1-t) (z_{2}-x)\in P, \\& y-\bigl(tz_{1}+(1-t)z_{2}\bigr)=t(y-z_{1})+(1-t) (y-z_{2})\in P. \end{aligned}$$

Thus \(tz_{1}+(1-t)z_{2}\in[x,y]\), that is, \([x,y]\) is convex. Let \(\{z_{n}\} \subset[x,y]\) with \(\lim_{n\to\infty}z_{n}=z\). Then, for each \(n\geq 1\), \(z_{n}-x\in P\) and \(y-z_{n}\in P\), and hence we have

$$\lim_{n\to\infty}z_{n}-x= z-x\in P,\qquad \lim _{n\to\infty}y-z_{n}= y-z\in P, $$

that is, \(x\leq z\leq y\) and so \(z\in[x,y]\), that is, \([x,y]\) is closed. Then the convexity of the order interval \([x,y]\) implies that

$$ x\leq tx+(1-t)y\leq y $$
(2.2)

for all \(x,y\in E\) with \(x\leq y\).

Definition 2.1

Let K be a nonempty closed and convex subset of a Banach space E. A mapping \(T : K \to E\) is said to be:

  1. (1)

    monotone [3] if \(Tx\leq Ty\) for all \(x, y \in K\) with \(x\leq y\);

  2. (2)

    monotone nonexpansive [3] if T is monotone and

    $$\|Tx-Ty\|\leq\|x-y\| $$

    for all \(x, y \in K\) with \(x\leq y\).

A Banach space E is said to be:

  1. (1)

    strictly convex if \(\|\frac{x+y}{2}\|<1\) for all \(x,y\in E\) with \(\|x\|=\|y\|=1\) and \(x\neq y\);

  2. (2)

    uniformly convex if, for all \(\varepsilon\in (0,2]\), there exists \(\delta>0\) such that \(\frac{\|x+y\|}{2}<1-\delta\) for all \(x,y\in E\) with \(\|x\|=\|y\|=1\) and \(\|x-y\|\geq\varepsilon\).

The following inequality was showed by Xu [16] in a uniformly convex Banach space E, which is known as Xus inequality.

Lemma 2.2

(Xu [16], Theorem 2)

For any real numbers \(q>1\) and \(r>0\), a Banach space E is uniformly convex if and only if there exists a continuous strictly increasing convex function \(g:[0,+\infty)\to[0,+\infty)\) with \(g(0)=0\) such that

$$ \bigl\Vert t x+(1-t)y\bigr\Vert ^{q}\leq t \Vert x \Vert ^{q}+(1-t)\Vert y\Vert ^{q}-\omega(q,t)g\bigl( \Vert x-y\Vert \bigr) $$
(2.3)

for all \(x,y\in B_{r}(0)=\{x\in E; \|x\|\leq r\}\) and \(t\in[0,1]\), where \(\omega(q,t)=t^{q}(1-t)+t(1-t)^{q}\). In particular, take \(q=2\) and \(t=\frac{1}{2}\),

$$ \biggl\Vert \frac{x+y}{2}\biggr\Vert ^{2}\leq \frac{1}{2}\Vert x\Vert ^{2}+\frac{1}{2}\Vert y\Vert ^{2}-\frac{1}{4}g\bigl(\Vert x-y\Vert \bigr). $$
(2.4)

The following conclusion is well known.

Lemma 2.3

(Takahashi [17], Theorem 1.3.11)

Let K be a nonempty closed convex subset of a reflexive Banach space E. Assume that \(\varphi:K\to R\) is a proper convex lower semi-continuous and coercive function. Then the function φ attains its minimum on K, that is, there exists \(x\in K\) such that

$$\varphi(x)=\inf_{y\in K} \varphi(y). $$

3 Main results

3.1 Existence of fixed points

In this section, we prove some existence theorems of fixed points of a monotone nonexpansive mapping in a uniformly convex Banach space \((E,\leq)\).

Theorem 3.1

Let K be a nonempty and closed convex subset of a uniformly convex Banach space \((E,\leq)\) and \(T : K\to K\) be a monotone nonexpansive mapping. Assume that there exists \(x\in K\) such that \(x\leq Tx\), the sequence \(\{T^{n}x\}_{n=1}^{\infty}\) is bounded. Then \(F(T)\ne\emptyset\) and \(y'\geq x\) for some \(y'\in F(T)\).

Proof

Let \(x_{1}=x\) and \(x_{n+1}=Tx_{n}=T^{n}x\). Then \(x_{1}=x\leq Tx=x_{2}\), and so,

$$x_{2}=Tx_{1}=Tx\leq Tx_{2}=T^{2}x=x_{3}. $$

By analogy, we must have

$$x=x_{1}\leq x_{2}\leq x_{3}\leq\cdots\leq x_{n}\leq x_{n+1}\leq\cdots. $$

Let \(K_{n}=\{z\in K:x_{n}\leq z\}\) for all \(n\geq1\). Clearly, for each \(n\geq1\), \(K_{n}\) is closed convex and \(y\in K_{n}\) and so \(K_{n}\) is nonempty too. Let \(K^{*}=\bigcap_{n=1}^{\infty}K_{n}\). Then \(K^{*}\) is a nonempty closed convex subset of K. Since \(\{x_{n}\}\) is bounded, we can define a function \(\varphi:K^{*}\to[0,+\infty)\) as follows:

$$\varphi(z)=\limsup_{n\to\infty}\|x_{n}-z\|^{2} $$

for all \(z\in K^{*}\). From Lemma 2.3, it follows that there exists \(y^{*}\in K_{1}\) such that

$$ \varphi\bigl(y^{*}\bigr)=\inf_{z\in K^{*}} \varphi(z). $$
(3.1)

Now, we show \(y^{*}=Ty^{*}\). In fact, by the definition of \(K^{*}\), we obtain

$$x_{1}\leq x_{2}\leq x_{3}\leq\cdots\leq x_{n}\leq x_{n+1}\leq\cdots\leq y^{*}. $$

Then we have \(x_{n+1}=Tx_{n}\leq Ty^{*}\) by the monotonicity of T and hence, for each \(n\geq1\), \(x_{n}\leq Ty^{*}\). So we have \(Ty^{*}\in K^{*}\). From the convexity of \(K^{*}\), it follows that \(\frac{y^{*}+Ty^{*}}{2}\in K^{*}\) and so, by (3.1), we have

$$ \varphi\bigl(y^{*}\bigr)\leq\varphi \biggl(\frac{y^{*}+Ty^{*}}{2} \biggr),\qquad \varphi \bigl(y^{*}\bigr)\leq\varphi\bigl(Ty^{*}\bigr). $$
(3.2)

On the other hand, we have

$$\begin{aligned} \varphi\bigl(Ty^{*}\bigr)&=\limsup_{n\to\infty}\bigl\Vert x_{n+1}-Ty^{*}\bigr\Vert ^{2} \\ &=\limsup_{n\to\infty}\bigl\Vert Tx_{n}-Ty^{*}\bigr\Vert ^{2} \\ &\leq\limsup_{n\to\infty}\bigl\Vert x_{n}-y^{*}\bigr\Vert ^{2} \\ &=\varphi\bigl(y^{*}\bigr). \end{aligned}$$
(3.3)

Combining (3.2) and (3.3), we have

$$ \varphi\bigl(Ty^{*}\bigr)=\varphi\bigl(y^{*}\bigr). $$
(3.4)

It follows from Lemma 2.2 (\(q=2\) and \(t=\frac{1}{2}\)) and (3.4) that

$$\begin{aligned} \varphi \biggl(\frac{y^{*}+Ty^{*}}{2} \biggr)&= \limsup_{n\to\infty}\biggl\Vert x_{n}-\frac{y^{*}+Ty^{*}}{2}\biggr\Vert ^{2} \\ &=\limsup_{n\to\infty}\biggl\Vert \frac{x_{n}-y^{*}}{2}+ \frac{x_{n}-Ty^{*}}{2} \biggr\Vert ^{2} \\ &\leq\limsup_{n\to\infty} \biggl(\frac{1}{2}\bigl\Vert x_{n}-y^{*}\bigr\Vert ^{2}+\frac{1}{2}\bigl\Vert x_{n}-Ty^{*}\bigr\Vert ^{2}-\frac{1}{4}g\bigl(\bigl\Vert y^{*}-Ty^{*}\bigr\Vert \bigr) \biggr) \\ &\leq\frac{1}{2}\varphi\bigl(y^{*}\bigr)+\frac{1}{2}\varphi\bigl(Ty^{*} \bigr)-\frac{1}{4}g\bigl(\bigl\Vert y^{*}-Ty^{*}\bigr\Vert \bigr) \\ &= \varphi\bigl(y^{*}\bigr)-\frac{1}{4}g\bigl(\bigl\Vert y^{*}-Ty^{*}\bigr\Vert \bigr). \end{aligned}$$

Noticing (3.2), we have

$$g\bigl(\bigl\Vert y^{*}-Ty^{*}\bigr\Vert \bigr)\leq\varphi\bigl(y^{*}\bigr)- \varphi \biggl(\frac{y^{*}+Ty^{*}}{2} \biggr)\leq0 $$

and so \(g(\|y^{*}-Ty^{*}\|)=0\). Thus we have \(y^{*}=Ty^{*}\) by the property of g. This yields the desired conclusion. This completes the proof. □

Theorem 3.2

Let K be a nonempty and closed convex subset of a uniformly convex Banach space \((E,\leq)\) and \(T : K\to K\) be a monotone nonexpansive mapping. Assume that there exists \(x\in K\) such that \(Tx\leq x\), the sequence \(\{T^{n}x\}_{n=1}^{\infty}\) is bounded and all \(n\geq1\). Then \(F(T)\ne\emptyset\) and \(y'\leq x\) for some \(y'\in F(T)\).

Proof

Let \(x_{1}=x\), \(x_{n+1}=Tx_{n}=T^{n}x\), and let \(K_{n}=\{z\in K:z\leq x_{n}\}\) for all \(n\geq1\). Using the same proof technique of Theorem 3.1, it is easy to obtain

$$x_{n+1}\leq x_{n} $$

for all \(n\geq1\) and \(K^{*}=\bigcap_{n=1}^{\infty}K_{n}\) is a nonempty closed convex subset of K. The remainder of the proof is the same as ones of Theorem 3.1 and so we omit it. □

Theorem 3.3

Let E be a uniformly convex Banach space with the partial order ‘’ with respect to closed convex cone P and \(T : P\to P\) be a monotone nonexpansive mapping. Assume that the sequence \(\{T^{n}0\}_{n=1}^{\infty}\) is bounded. Then \(F(T)\ne\emptyset\).

Proof

It follows from the definition of the partial order ‘≤’ that \(0\leq T0\). Then the conclusions directly follow from Theorem 3.1. □

Denote \(\mathbb{R}^{m}=\{(r_{1}, r_{2},\ldots, r_{m}): r_{i}\in \mathbb{R}, i=1,2,\ldots,m\}\) and \(\mathbb{R}^{m}_{+}=\{(r_{1}, r_{2},\ldots, r_{m}): r_{i}\geq0, i=1,2,\ldots,m\}\), where \(\mathbb{R}\) is the set of all real numbers.

Theorem 3.4

Let \(T : \mathbb{R}^{m}_{+}\to\mathbb {R}^{m}_{+}\) be a monotone nonexpansive mapping. Assume that the sequence \(\{T^{n}0\}_{n=1}^{\infty}\) is bounded. Then \(F(T)\ne\emptyset\).

Proof

Let \(T^{n}0=(r^{(n)}_{1},r^{(n)}_{2},\ldots,r^{(n)}_{m})\in\mathbb {R}^{m}_{+}\). It follows from the boundedness of the sequence \(\{T^{n}0\}\) that there exist a positive real number r such that \(r^{(n)}_{i}\leq r\) for all n and \(i=1,2,\ldots,m\). Take \(y=(r,r,\ldots,r)\). So the conclusions directly follow from Theorem 3.3. □

Theorem 3.5

Let K be a nonempty and closed convex subset of a Banach space \((E,\leq)\) and \(T : K\to K\) be a monotone nonexpansive mapping. Assume that \(F(T)\ne\emptyset\) and there exist \(x\in K\) and \(p\in F(T)\) such that \(p\leq x\) (or \(x\leq p\)). Then the sequence \(\{T^{n}x\}\) is bounded.

Proof

Let \(x_{1}=x\) and \(x_{n+1}=Tx_{n}=T^{n}x\). Then it follows from the conditions \(p=Tp\) and \(p\leq x\) (or \(x\leq p\)) that \(p=Tp\leq Tx_{n}=x_{n+1}\) (or \(x_{n+1}=Tx_{n}\leq Tp=p\)) for all \(n\geq1\) and so

$$\begin{aligned}& \|x_{2}-p\|=\|Tx_{1}-Tp\| \leq\|x_{1}-p\|=\|x-p \|, \\& \|x_{3}-p\|=\|Tx_{2}-Tp\|\leq\|x_{2}-p\|\leq\|x-p \|, \\& \ldots, \\& \|x_{n}-p\|=\|Tx_{n-1}-Tp\| \leq\|x_{n-1}-p\|\leq\|x-p \|, \\& \|x_{n+1}-p\|=\|Tx_{n}-Tp\| \leq\|x_{n}-p\|\leq\|x-p \|, \\& \ldots \end{aligned}$$

and so \(\|x_{n}-p\|\leq\|x-p\|\) for all \(n\geq1\) and hence the sequence \(\{T^{n}x\}\) is bounded. This completes the proof. □

Theorem 3.6

Let E be a Banach space with the partial order ‘’ with respect to closed convex cone P and \(T : P\to P\) be a monotone nonexpansive mapping. Assume that \(F(T)\ne \emptyset\). Then the sequence \(\{T^{n}0\}\) is bounded. Furthermore, the sequence \(\{T^{n}x\}\) is bounded for all \(x\in P\).

Proof

It follows from the definition of T that \(0\leq p\) for all \(p\in F(T)\). Then the conclusion that \(\{T^{n}0\}\) is bounded directly follows from Theorem 3.5. For each \(x\in P\), it is obvious that \(0\leq x\) and hence, by the monotonicity of T, we have

$$T0\leq Tx, T^{2}0\leq T^{2}x, \ldots, T^{n}0\leq T^{n}x, \ldots. $$

It follows from the definition of a monotone nonexpansive mapping that

$$\begin{aligned}& \Vert Tx-T0\Vert \leq \Vert x-0\Vert =\Vert x\Vert , \\& \bigl\Vert T^{2}x-T^{2}0\bigr\Vert \leq \Vert Tx-T0 \Vert \leq \Vert x\Vert , \\& \ldots, \\& \bigl\Vert T^{n}x-T^{n}0\bigr\Vert \leq\bigl\Vert T^{n-1}x-T^{n-1}0\bigr\Vert \leq \Vert x\Vert , \\& \bigl\Vert T^{n+1}x-T^{n+1}0\bigr\Vert \leq\bigl\Vert T^{n}x-T^{n}0\bigr\Vert \leq \Vert x\Vert , \\& \ldots \end{aligned}$$

and so the sequence \(\{T^{n}x\}\) is bounded. The desired conclusion follows. This completes the proof. □

Theorem 3.7

Let \(T : \mathbb{R}^{m}_{+}\to\mathbb {R}^{m}_{+}\) be a monotone nonexpansive mapping. Then \(F(T)\ne\emptyset\) if and only if the sequence \(\{T^{n}0\}\) is bounded.

Proof

The conclusions directly follow from Theorems 3.4 and 3.6. □

3.2 The convergence of the Mann iteration

In this section, for a monotone nonexpansive mapping T, we consider the Mann iteration sequence defined by

$$ x_{n+1}=\beta_{n}x_{n}+(1- \beta_{n})Tx_{n} $$
(3.5)

for each \(n\geq1\), where \(\{\beta_{n}\}\) in \((0,1)\) satisfies the following condition:

$$\sum_{n=1}^{\infty}\beta_{n}(1- \beta_{n})=\infty. $$

Clearly, the above condition contains \(\beta_{n}=\frac{1}{n+1}\) as a special case.

The following lemma is showed by Dehaish and Khamsi [15], where the conclusion (3) is obtained from the proof of Lemma 3.1 in [15].

Lemma 3.8

(Dehaish and Khamsi [15], Lemmas 3.1 and 3.2)

Let K be a nonempty and closed convex subset of a Banach space \((E,\leq)\) and \(T : K\to K\) be a monotone nonexpansive mapping. Assume that the sequence \(\{x_{n}\}\) is defined by (3.5) and \(x_{1}\leq Tx_{1}\) (or \(Tx_{1}\leq x_{1}\)). If \(F(T)\ne\emptyset\) and \(p\leq x_{1}\) (or \(x_{1}\leq p\)) for some \(p\in F(T)\), then

  1. (1)

    \(\{x_{n}\}\) is bounded and \(x_{n}\leq x_{n+1}\leq Tx_{n}\) (or \(Tx_{n}\leq x_{n+1}\leq x_{n}\));

  2. (2)

    \(\lim_{n\to\infty}\|x_{n}-p\|\) exists;

  3. (3)

    \(x_{n}\leq x\) (or \(x\leq x_{n}\)) for all \(n\geq1\) provided \(\{x_{n}\}\) weakly converges to a point \(x\in K\).

Theorem 3.9

Let K be a nonempty and closed convex subset of a uniformly convex Banach space \((E,\leq)\) and \(T : K\to K\) be a monotone nonexpansive mapping. Assume that the sequence \(\{x_{n}\}\) is defined by (3.5) and \(x_{1}\leq Tx_{1}\) (or \(Tx_{1}\leq x_{1}\)). If \(F(T)\ne\emptyset\) and \(p\leq x_{1}\) (or \(x_{1}\leq p\)) for some \(p\in F(T)\), then

$$\lim_{n\to\infty}\|x_{n}-Tx_{n}\|=0. $$

Proof

It follows from Lemma 3.8 that

$$p\leq x_{1}\leq x_{n} \quad (\mbox{or }\,\,x_{n}\leq x_{1}\leq p) $$

for all \(n\geq1\). Then it follows from the nonexpansiveness of T, \(p=Tp\), and an application of Lemma 2.2 (\(q=2\) and \(t=\beta _{n}\)) that

$$\begin{aligned} \Vert x_{n+1}-p\Vert ^{2}&=\bigl\Vert \beta_{n}(x_{n}-p)+(1-\beta_{n}) (Tx_{n}-Tp)\bigr\Vert ^{2} \\ &\leq\beta_{n}\Vert x_{n}-p\Vert ^{2}+(1- \beta_{n})\Vert Tx_{n}-Tp\Vert ^{2}- \beta_{n}(1-\beta _{n})g\bigl(\Vert x_{n}-Tx_{n} \Vert \bigr) \\ &\leq \Vert x_{n}-p\Vert ^{2}-\beta_{n}(1- \beta_{n})g\bigl(\Vert x_{n}-Tx_{n}\Vert \bigr), \end{aligned}$$

and so

$$\beta_{n}(1-\beta_{n})g\bigl(\Vert x_{n}-Tx_{n} \Vert \bigr)\leq \Vert x_{n}-p\Vert ^{2}-\Vert x_{n+1}-p\Vert ^{2}. $$

Therefore, we have

$$ \sum_{n=1}^{\infty}\beta_{n}(1-\beta_{n})g\bigl(\Vert x_{n}-Tx_{n} \Vert \bigr)\leq \Vert x_{1}-p\Vert ^{2}< +\infty. $$
(3.6)

Now, we claim that there exists a subsequence \(\{x_{n_{k}}\}\) such that

$$ \lim_{k\to\infty}g\bigl(\Vert x_{n_{k}}-Tx_{n_{k}} \Vert \bigr)=0. $$
(3.7)

Suppose that the conclusion is not true. Then, for all subsequences \(\{ x_{n_{k}}\}\) such that \(\lim_{k\to\infty}g(\|x_{n_{k}}-Tx_{n_{k}}\|)>0\), we have

$$\liminf_{n\to\infty}g\bigl(\Vert x_{n}-Tx_{n} \Vert \bigr)>0. $$

Thus there exists a positive number a and a positive integer N such that \(g(\|x_{n}-Tx_{n}\|)>a>0\) for all \(n>N\). Consequently, we have

$$\beta_{n}(1-\beta_{n})g\bigl(\Vert x_{n}-Tx_{n} \Vert \bigr)\geq a\beta_{n}(1-\beta_{n}) $$

and hence, by the condition \(\sum_{n=1}^{\infty}\beta_{n}(1-\beta _{n})=+\infty\), we obtain

$$\sum_{n=1}^{\infty}\beta_{n}(1- \beta_{n})g\bigl(\Vert x_{n}-Tx_{n}\Vert \bigr)=+\infty. $$

This contradicts (3.6). So (3.7) holds and hence, by the property of g, we have

$$\lim_{k\to\infty}\|x_{n_{k}}-Tx_{n_{k}}\|=0. $$

On the other hand, we have

$$\begin{aligned} \Vert x_{n+1}-Tx_{n+1}\Vert &= \bigl\Vert \beta_{n}(x_{n}-Tx_{n})+(Tx_{n}-Tx_{n+1}) \bigr\Vert \\ &\leq\beta_{n}\Vert x_{n}-Tx_{n}\Vert +\Vert x_{n+1}-x_{n}\Vert \\ &= \beta_{n}\Vert x_{n}-x_{n}-Tx_{n} \Vert +(1-\beta_{n})\Vert x_{n}-Tx_{n}\Vert \\ &= \Vert x_{n}-Tx_{n}\Vert . \end{aligned}$$

Therefore, the sequence \(\{\|x_{n}-Tx_{n}\|\}\) is monotonically non-increasing and hence it follows that \(\lim_{n\to\infty}\| x_{n}-Tx_{n}\|\) exists. This yields the desired conclusion. This completes the proof. □

Recall that a Banach space E is said to satisfy Opials condition [12] if a sequence \(\{x_{n}\}\) with \(\{x_{n}\}\) weakly converges to a point \(x\in E\) implies

$$\limsup_{n\rightarrow\infty}\|x_{n}-x\|< \limsup _{n\rightarrow \infty}\|x_{n}-y\| $$

for all \(y\in E\) with \(y\neq x\).

Next, we show the weak convergence of the sequence \(\{x_{n}\}\) defined by (3.5). The proof is similar to the ones of Dehaish and Khamsi [15], but, for more details, we give the proof.

Theorem 3.10

Let K be a nonempty and closed convex subset of a uniformly convex Banach space \((E,\leq)\) and \(T : K\to K\) be a monotone nonexpansive mapping. Assume that E satisfies Opial’s condition and the sequence \(\{x_{n}\}\) is defined by (3.5) with \(x_{1}\leq Tx_{1}\) (or \(Tx_{1}\leq x_{1}\)). If \(F(T)\ne\emptyset\) and \(p\leq x_{1}\) (or \(x_{1}\leq p\)) for some \(p\in F(T)\), then \(\{x_{n}\}\) weakly converges to a fixed point \(x^{*}\) of T.

Proof

It follows from Lemma 3.8 and Theorem 3.9 that \(\{x_{n}\}\) is bounded and

$$\lim_{n\to\infty}\|x_{n}-Tx_{n}\|=0. $$

Then there exists a subsequence \(\{x_{n_{k}}\}\subset\{x_{n}\}\) such that \(\{x_{n_{k}}\}\) weakly converges to a point \(x^{*}\in K\). Following Lemma 3.8, we have \(x_{1}\leq x_{n_{k}}\leq x^{*}\) (or \(x^{*}\leq x_{n_{k}}\leq x_{1}\)) for all \(k\geq1\). In particular, we have

$$\lim_{k\to\infty}\|x_{n_{k}}-Tx_{n_{k}}\|=0. $$

Now, we claim \(x^{*}=Tx^{*}\). In fact, suppose that this is not true. Then, from the nonexpansiveness of T and Opial’s condition, it follows that

$$\begin{aligned} \limsup_{k\rightarrow\infty}\bigl\Vert x_{n_{k}}-x^{*}\bigr\Vert &< \limsup_{k\rightarrow \infty}\bigl\Vert x_{n_{k}}-Tx^{*}\bigr\Vert \\ &\leq\limsup_{k\rightarrow\infty}\bigl(\Vert x_{n_{k}}-Tx_{n_{k}} \Vert +\bigl\Vert Tx_{n_{k}}-Tx^{*}\bigr\Vert \bigr) \\ &\leq\limsup_{k\rightarrow\infty}\bigl\Vert x_{n_{k}}-x^{*}\bigr\Vert , \end{aligned}$$

which is a contradiction. Thus, by Lemma 3.8(2), it follows that the limit \(\lim_{n\to\infty}\|x_{n}-x^{*}\|\) exists.

Now, we show that \(\{x_{n}\}\) weakly converges to the point \(x^{*}\). Suppose that this is not true. Then there exists a subsequence \(\{x_{n_{j}}\}\) that converges weakly to a point \(z\in K\) and \(z\ne x^{*}\). Similarly, it follows that \(z=Tz\) and \(\lim_{n\to\infty}\|x_{n}-z\|\) exists. It follows from Opial’s condition that

$$\lim_{n\to\infty} \Vert x_{n}-z\Vert < \lim _{n\to\infty}\bigl\Vert x_{n}-x^{*}\bigr\Vert =\limsup _{i\rightarrow\infty}\bigl\Vert x_{n_{i}}-x^{*}\bigr\Vert < \lim _{n\to\infty} \Vert x_{n}-z\Vert . $$

This is a contradiction and hence \(x^{*}=z\). This completes the proof. □