In this section we consider the existence and uniqueness of positive solutions for the operator of equation (1.1). Throughout the paper, we assume that E is a real Banach space with a partial order introduced by a normal cone P of E. Take \(h\in E\), \(h>\theta\), \(P_{h}\) is given as in the introduction.
Theorem 3.1
Let
P
be a normal cone in
E. Assume that
\(A, B, C:P\times P\rightarrow P\)
are three mixed monotone operators and satisfy the following conditions:
-
(1)
for any
\(t\in(0,1)\), there exists
\(\varphi(t)\in(t,1]\)
such that
$$ A\bigl(tx,t^{-1}y\bigr)\geq\varphi(t)A(x,y), \quad\forall x,y\in P; $$
(3.1)
-
(2)
for any
\(t\in(0,1)\), \(x,y\in P\),
$$ B\bigl(tx,t^{-1}y\bigr)\geq tB(x,y); $$
(3.2)
-
(3)
for any fixed
\(y\in P\), \(C(\cdot,y):P\rightarrow P\)
is concave; for any fixed
\(x\in P\), \(C(x,\cdot):P\rightarrow P\)
is convex;
-
(4)
there is
\(h\in P\), \(h>\theta\)
such that
\(A(h,h)\in P_{h}\), \(B(h,h)\in P_{h}\), and
\(C(h,h)\in P_{h}\);
-
(5)
there exists
\(\frac{1}{2}\leq c\leq1\), such that
\(C(\theta,lh)\geq cC(lh,\theta)\), for any
\(l\geq1\);
-
(6)
there exists a constant
\(\delta_{0}>0\), such that
\(B(x,y)+C(x,y)\leq\delta_{0}A(x,y)\), \(\forall x,y \in P_{h}\).
Then the operator of equation (1.1) has a unique positive solution
\(x^{\ast}\)
in
P, which satisfies
\(\mu h\leq x^{\ast}\leq\lambda h\), where
\(\lambda >0\), \(\mu>0\)
are two real numbers. And for any initial values
\(x_{0},y_{0}\in P_{h}\), by constructing successively the sequences as follows:
$$\begin{aligned}& x_{n}=A(x_{n-1},y_{n-1})+B(x_{n-1},y_{n-1})+C(x_{n-1},y_{n-1}), \\& y_{n}=A(y_{n-1},x_{n-1})+B(y_{n-1},x_{n-1})+C(y_{n-1},x_{n-1}), \quad n=1,2,\ldots, \end{aligned}$$
we have
\(x_{n}\rightarrow x^{\ast}\)
and
\(y_{n}\rightarrow x^{\ast}\)
in
E, as
\(n\rightarrow\infty\).
Proof
From (3.1) and (3.2), for any \(t\in(0,1)\), we have
$$A\bigl(t^{-1}x,ty\bigr)\leq\frac{1}{\varphi(t)}A(x,y), \quad \forall x,y \in P $$
and
$$ B\bigl(t^{-1}x,ty\bigr)\leq t^{-1}B(x,y), \quad \forall x,y\in P. $$
(3.3)
Since \(A(h,h)\in P_{h}\), \(B(h,h)\in P_{h}\), \(C(h,h)\in P_{h}\), there exist constants \(a_{i}>0\), \(b_{i}>0 \) (\(i=1,2,3\)) such that
$$ a_{1}h\leq A(h,h)\leq b_{1}h, \qquad a_{2}h\leq B(h,h)\leq b_{2}h, \qquad a_{3}h\leq C(h,h)\leq b_{3}h. $$
(3.4)
First of all, we show \(A:P_{h}\times P_{h}\rightarrow P_{h}\). For any \(x,y\in P_{h}\), we can choose two sufficiently small numbers \(\alpha_{1},\alpha_{2}\in(0,1)\) such that
$$\alpha_{1}h\leq x\leq\frac{1}{\alpha_{1}}h, \qquad \alpha_{2}h \leq y\leq \frac{1}{\alpha_{2}}h. $$
Let \(\alpha=\min\{\alpha_{1},\alpha_{2}\}\), then \(\alpha\in(0,1)\), by (3.1), (3.3), and (3.4), we have
$$\begin{aligned}& A(x,y)\leq A \biggl(\frac{1}{\alpha}h,\alpha h \biggr)\leq\frac{1}{\varphi (\alpha)}A(h,h) \leq \frac{1}{\varphi(\alpha)}b_{1}h, \\& A(x,y)\geq A \biggl(\alpha h,\frac{1}{\alpha}h \biggr)\geq\varphi(\alpha) A(h,h)\geq \varphi(\alpha)a_{1}h. \end{aligned}$$
Evidently, \(\frac{1}{\varphi(\alpha)}b_{1}, \varphi(\alpha)a_{1}>0\). Thus \(A(x,y)\in P_{h}\); that is, \(A:P_{h}\times P_{h}\rightarrow P_{h}\).
Second, we show \(B:P_{h}\times P_{h}\rightarrow P_{h}\). For any \(x,y\in P_{h}\), we can choose two sufficiently small numbers \(\beta_{1},\beta_{2}\in(0,1)\) such that
$$\beta_{1}h\leq x\leq\frac{1}{\beta_{1}}h, \qquad \beta_{2}h \leq y\leq \frac{1}{\beta_{2}}h. $$
Let \(\beta=\min\{\beta_{1},\beta_{2}\}\), then \(\beta\in(0,1)\), by (3.2), (3.3), and (3.4), we have
$$\begin{aligned}& B(x,y)\leq B \biggl(\frac{1}{\beta}h,\beta h \biggr)\leq\frac{1}{\beta }B(h,h) \leq \frac{1}{\beta}b_{2}h, \\& B(x,y)\geq B \biggl(\beta h,\frac{1}{\beta}h \biggr)\geq\beta B(h,h)\geq \beta a_{2}h. \end{aligned}$$
Evidently, \(\frac{1}{\beta}b_{2}, \beta a_{2} >0\). Thus \(B(x,y)\in P_{h}\); that is, \(B:P_{h}\times P_{h}\rightarrow P_{h}\).
Thirdly, we show \(C:P_{h}\times P_{h}\rightarrow P_{h}\). For any \(t\in(0,1)\), \(x,y\in P_{h}\), we have
$$C(x,y)= C\bigl(x,tt^{-1}y+(1-t)\theta\bigr)\leq tC\bigl(x,t^{-1}y \bigr)+(1-t)C(x,\theta), $$
thus
$$ tC\bigl(x,t^{-1}y\bigr)\geq C(x,y)-(1-t)C(x,\theta). $$
(3.5)
Also, we can find a sufficiently large l such that \(x, y, t^{-1}y\leq lh\) and satisfies (5), so from (5), (3.5), and the concavity and convexity as well as the monotone property of operator C, we have
$$\begin{aligned} C\bigl(tx,t^{-1}y\bigr)&\geq tC\bigl(x,t^{-1}y\bigr)+(1-t)C \bigl(\theta,t^{-1}y\bigr) \\ &\geq C(x,y)-(1-t)C(x,\theta)+(1-t)C(\theta,lh) \\ &\geq C(x,y)+(1-t)\bigl[C(\theta,lh)-C(lh,\theta)\bigr] \\ &\geq C(x,y)+(1-t)\biggl[C(\theta,lh)-\frac{1}{c}C(\theta,lh)\biggr] \\ &= C(x,y)+(1-t) \biggl(1-\frac{1}{c}\biggr)C(\theta,lh) \\ &\geq\biggl[1+(1-t) \biggl(1-\frac{1}{c}\biggr)\biggr]C(x,y) \\ &=\biggl[\biggl(2-\frac{1}{c}\biggr)+\biggl(\frac{1}{c}-1\biggr)t \biggr]C(x,y) \\ &\geq tC(x,y). \end{aligned}$$
That is,
$$ C\bigl(tx,t^{-1}y\bigr)\geq tC(x,y),\quad \forall t\in(0,1), \forall x,y\in P_{h}. $$
(3.6)
And then it is obvious that
$$ C\bigl(t^{-1}x,ty\bigr)\leq\frac{1}{t}C(x,y), \quad \forall t \in(0,1), \forall x,y\in P_{h}. $$
(3.7)
Since \(x,y\in P_{h}\), we can choose two sufficiently small numbers \(\gamma_{1},\gamma_{2}\in(0,1)\) such that
$$\gamma_{1}h\leq x\leq\frac{1}{\gamma_{1}}h, \qquad \gamma_{2}h\leq y\leq\frac{1}{\gamma_{2}}h. $$
Let \(\gamma=\min\{\gamma_{1},\gamma_{2}\}\), then \(\gamma\in(0,1)\), by (3.4), (3.6), and (3.7), we have
$$\begin{aligned}& C(x,y)\leq C \biggl(\frac{1}{\gamma}h,\gamma h \biggr)\leq \frac{1}{\gamma }C(h,h)\leq \frac{1}{\gamma}b_{3}h, \\& C(x,y)\geq C \biggl(\gamma h,\frac{1}{\gamma}h \biggr)\geq\gamma C(h,h)\geq \gamma a_{3}h. \end{aligned}$$
Evidently, \(\frac{1}{\gamma}b_{3}, \gamma a_{3} >0\). Thus \(C(x,y)\in P_{h}\); that is, \(C:P_{h}\times P_{h}\rightarrow P_{h}\).
Now we define an operator \(T=A+B+C: P_{h}\times P_{h}\rightarrow P_{h}\) by
$$T(x,y)=A(x,y)+B(x,y)+C(x,y), \quad x,y\in P_{h}. $$
Then \(T:P_{h}\times P_{h}\rightarrow P_{h}\) is a mixed monotone operator and \(T(h,h)\in P_{h}\).
In the following, we show that for any \(x,y\in P_{h}\), \(t\in(0,1)\), there exists \(\psi(t,x,y)\in (t,1]\) such that \(T(tx,t^{-1}y)\geq\psi(t,x,y)T(x,y)\). From (3.1), (3.2), and (3.6), for any \(t\in(0,1)\) and \(x,y\in P_{h}\), we have
$$\begin{aligned} T\bigl(tx,t^{-1}y\bigr)&=A\bigl(tx,t^{-1}y\bigr)+B \bigl(tx,t^{-1}y\bigr)+C\bigl(tx,t^{-1}y\bigr) \\ &\geq \varphi(t) A(x,y)+tB(x,y)+tC(x,y) \\ &\geq \varphi(t)A(x,y)+t \bigl[B(x,y)+C(x,y) \bigr]. \end{aligned}$$
For any \(x, y\in P_{h}\), since \(A, B, C:P_{h}\times P_{h}\rightarrow P_{h}\), we have \(A(x,y)\in P_{h}\), \(B(x,y)\in P_{h}\), \(C(x,y)\in P_{h}\), and thus we get \(B(x,y)+C(x,y)\sim A(x,y)\). Denote
$$F(x,y)=M \biggl(\frac{B(x,y)+C(x,y)}{A(x,y)} \biggr). $$
Then from (6) we have \(F(x,y)\leq\delta_{0}\). For any \(t\in(0,1)\), \(x,y\in P_{h}\), consider
$$g(s)=\frac{\varphi(t)+F(x,y)t}{(F(x,y)+1)s}, \quad s\in\bigl[t,\varphi(t)\bigr]. $$
It is clear that g is continuous and strictly decreasing with respect to s. Since
$$g \biggl(\frac{\delta_{0}t+\varphi(t)}{\delta_{0}+1} \biggr)= \frac{\varphi(t)+F(x,y)t}{ (F(x,y)+1 )\frac{\delta_{0}t+\varphi (t)}{\delta_{0}+1}}>1 $$
and
$$g\bigl(\varphi(t)\bigr)=\frac{\varphi(t)+F(x,y)t}{(F(x,y)+1)\varphi(t)}< 1, $$
there exists a unique \(\psi(t,x,y)\in (\frac{\delta_{0}t+\varphi(t)}{\delta_{0}+1},\varphi (t) )\) such that
$$g\bigl(\psi(t,x,y)\bigr)=\frac{\varphi(t)+F(x,y)t}{(F(x,y)+1)\psi(t,x,y)}=1. $$
Solving for \(F(x,y)\) in the above inequality leads to
$$F(x,y)=\frac{\varphi(t)-\psi(t,x,y)}{\psi(t,x,y)-t}. $$
From (2.1) we get \(M(x/y)=\inf\{\lambda\in R:x\leq\lambda y\}\). So from the definitions of \(F(x,y)\) and \(M(x/y)\), we can get
$$B(x,y)+C(x,y)\leq\frac{\varphi(t)-\psi(t,x,y)}{\psi(t,x,y)-t}A(x,y). $$
This inequality can be rewritten as
$$\varphi(t)A(x,y)+t\bigl[B(x,y)+C(x,y)\bigr]\geq\psi(t,x,y)\bigl[A(x,y)+B(x,y)+C(x,y) \bigr]. $$
Hence
$$\begin{aligned} T\bigl(tx,t^{-1}y\bigr)&=A\bigl(tx,t^{-1}y\bigr)+B \bigl(tx,t^{-1}y\bigr)+C\bigl(tx,t^{-1}y\bigr) \\ &\geq \varphi(t) A(x,y)+tB(x,y)+tC(x,y) \\ &= \varphi(t)A(x,y)+t\bigl[B(x,y)+C(x,y)\bigr] \\ &\geq \psi(t,x,y)\bigl[A(x,y)+B(x,y)+C(x,y)\bigr] \\ &= \psi(t,x,y)T(x,y). \end{aligned}$$
That is, for any \(x,y\in P_{h}\) and \(t\in(0,1)\), there exists \(\psi(t,x,y)\in (\frac{\delta_{0}t+\varphi(t)}{\delta_{0}+1},\varphi(t) )\subseteq(t,1]\) such that
$$ T\bigl(tx,t^{-1}y\bigr)\geq\psi(t,x,y)T(x,y). $$
(3.8)
Since \(T(h,h)\in P_{h}\), we can choose a sufficiently small number \(s_{0}\in(0,1)\) such that
$$ s_{0}h\leq T(h,h)\leq\frac{1}{s_{0}}h. $$
(3.9)
Noting that \(s_{0}<\psi(s_{0},x,y)\leq1\), we can get \(1<\frac{\psi(s_{0},x,y)}{s_{0}}\leq\frac{1}{s_{0}}\). By the Archimedes principle, we can take a positive integer k such that
$$\biggl(\frac{\psi(s_{0},x,y)}{s_{0}} \biggr)^{k}\geq\frac{1}{s_{0}}, $$
that is,
$$ \frac{\psi(s_{0},x,y)}{s_{0}}\geq \biggl(\frac{1}{s_{0}} \biggr)^{\frac {1}{k}}. $$
(3.10)
Put \(u_{0}=s_{0}^{k}h\), \(v_{0}=s_{0}^{-k}h\). Evidently, \(u_{0},v_{0}\in P_{h}\) and \(u_{0}=s_{0}^{2k}v_{0}< v_{0}\). Take any \(r\in(0,s_{0}^{2k}]\), then \(r\in(0,1)\) and \(u_{0}\geq rv_{0}\). By the mixed monotone properties of T, we have \(T(u_{0},v_{0})\leq T(v_{0},u_{0})\). Further, by combining condition (3.8) with (3.9) and (3.10), we have
$$\begin{aligned} T(u_{0},v_{0})&=T \biggl(s_{0}^{k}h, \frac{1}{s_{0}^{k}}h \biggr) \\ &=T \biggl(s_{0} s_{0}^{k-1}h,\frac{1}{s_{0}} \frac{1}{s_{0}^{k-1}}h \biggr) \\ &\geq \psi \biggl(s_{0},s_{0}^{k-1}h, \frac{1}{s_{0}^{k-1}}h \biggr)T \biggl(s_{0}^{k-1}h, \frac{1}{s_{0}^{k-1}}h \biggr) \\ &=\psi \biggl(s_{0},s_{0}^{k-1}h, \frac{1}{s_{0}^{k-1}}h \biggr)T \biggl(s_{0} s_{0}^{k-2}h, \frac{1}{s_{0}}\frac{1}{s_{0}^{k-2}}h \biggr) \\ &=\psi \biggl(s_{0},s_{0}^{k-1}h, \frac{1}{s_{0}^{k-1}}h \biggr)\psi \biggl(s_{0},s_{0}^{k-2}h, \frac{1}{s_{0}^{k-2}}h \biggr) T \biggl(s_{0}^{k-2}h, \frac{1}{s_{0}^{k-2}}h \biggr) \geq\cdots \\ &\geq \biggl( \biggl(\frac{1}{s_{0}} \biggr)^{\frac{1}{k}} s_{0} \biggr)^{k}T(h,h) \\ &\geq\frac{1}{s_{0}} s_{0}^{k} s_{0}h \\ &\geq s_{0}^{k}h \\ &= u_{0}. \end{aligned}$$
From (3.8), we can get, for all \(t\in(0,1)\), \(x,y\in P\), \(T(t^{-1}x,ty)\leq\frac{1}{\psi(t,x,y)}T(x,y)\). So
$$\begin{aligned} T(v_{0},u_{0})&=T \biggl(\frac{1}{s_{0}^{k}}h,s_{0}^{k}h \biggr) \\ &=T \biggl(\frac{1}{s_{0}}\frac{1}{s_{0}^{k-1}}h,s_{0} s_{0}^{k-1}h \biggr) \\ &\leq\frac{1}{\psi (s_{0},\frac {1}{s_{0}^{k-1}}h,s_{0}^{k-1}h )}T \biggl(\frac {1}{s_{0}^{k-1}}h,s_{0}^{k-1}h \biggr) \\ &=\frac{1}{\psi (s_{0},\frac{1}{s_{0}^{k-1}}h,s_{0}^{k-1}h )}T \biggl(\frac{1}{s_{0}}\frac{1}{s_{0}^{k-2}}h,s_{0} s_{0}^{k-2}h \biggr) \\ &=\frac{1}{\psi (s_{0},\frac{1}{s_{0}^{k-1}}h,s_{0}^{k-1}h )}\frac{1}{\psi (s_{0},\frac{1}{s_{0}^{k-2}}h,s_{0}^{k-2}h )} T \biggl(\frac{1}{s_{0}^{k-2}}h,s_{0}^{k-2}h \biggr) \leq\cdots \\ &\leq \biggl(\frac{1}{s_{0}} s_{0}^{\frac{1}{k}} \biggr)^{k}T(h,h) \\ &\leq\frac{1}{s_{0}^{k}} s_{0} \frac{1}{s_{0}}h \\ &\leq \frac{1}{s_{0}^{k}}h \\ &=v_{0}. \end{aligned}$$
Thus we have
$$u_{0}\leq T(u_{0},v_{0})\leq T(v_{0},u_{0})\leq v_{0}. $$
For \(u_{0}\), \(v_{0}\), construct successively the sequences as follows:
$$u_{n}=T(u_{n-1},v_{n-1}),\qquad v_{n}=T(v_{n-1},u_{n-1}), \quad n=1,2,\ldots. $$
Evidently, \(u_{1}\leq v_{1}\). By the mixed monotone properties of T, we obtain \(u_{n}\leq v_{n} \) (\(n=1,2,\ldots \)) and
$$ u_{0}\leq u_{1} \leq\cdots\leq u_{n}\leq\cdots \leq v_{n}\leq\cdots\leq v_{1}\leq v_{0}. $$
(3.11)
Noting that \(u_{0}\geq rv_{0}\), we can get \(u_{n}\geq u_{0}\geq rv_{0}\geq rv_{n} \) (\(n=1,2,\ldots \)). Let
$$t_{n}=\sup\{t>0\mid u_{n}\geq tv_{n}, n=1,2,\ldots \} . $$
Then we have
$$ u_{n}\geq t_{n}v_{n}, \quad n=1,2, \ldots, $$
(3.12)
and then by (3.11) we have
$$u_{n+1}\geq u_{n}\geq t_{n}v_{n}\geq t_{n}v_{n+1},\quad n=1,2,\ldots. $$
Therefore, \(t_{n+1}\geq t_{n}\), i.e., \(\{t_{n}\}\) is increasing with \(\{t_{n}\}\subset(0,1]\). Suppose \(t_{n}\rightarrow t^{*}\) as \(n\rightarrow\infty\), then \(t^{*}=1\). Otherwise, \(0< t^{*}<1\). Since \(t_{n}\leq t^{*}\) and \(\psi(t,x,y)>t\), by the mixed monotone properties of T and (3.8) as well as (3.12), we have
$$\begin{aligned} u_{n+1}&=T(u_{n},v_{n}) \\ &\geq T \biggl(t_{n}v_{n},\frac{1}{t_{n}}u_{n} \biggr) \\ &=T \biggl(\frac{t_{n}}{t^{\ast}}t^{\ast}v_{n},\frac{t^{\ast}}{t_{n}} \frac {1}{t^{\ast}}u_{n} \biggr) \\ &\geq \frac{t_{n}}{t^{\ast}}T \biggl({t^{\ast}}v_{n}, \frac{1}{t^{\ast}}u_{n} \biggr) \\ &\geq \frac{t_{n}}{t^{\ast}}\psi\bigl(t^{\ast},v_{n},u_{n} \bigr)T(v_{n},u_{n}) \\ &= \frac{t_{n}}{t^{\ast}}\psi\bigl(t^{\ast},v_{n},u_{n} \bigr)v_{n+1}. \end{aligned}$$
By the definition of \(t_{n}\), we have \(t_{n+1}\geq \frac{t_{n}}{t^{\ast}}\psi(t^{\ast},v_{n},u_{n})\), that is, \(\psi(t^{\ast},v_{n},u_{n})\leq\frac{t^{\ast}}{t_{n}}t_{n+1}\). So we get
$$t^{\ast}< \frac{\delta_{0}t^{\ast}+\varphi(t^{\ast})}{\delta_{0}+1}< \psi \bigl(t^{\ast},v_{n},u_{n} \bigr)\leq\frac{t^{\ast}}{t_{n}}t_{n+1}, \quad n=1,2,\ldots. $$
Since \(\lim_{n\rightarrow\infty} \frac{t^{\ast}}{t_{n}}t_{n+1}=t^{\ast}\), we get \(t^{\ast}<\frac{\delta_{0}t^{\ast}+\varphi(t^{\ast})}{\delta_{0}+1}\leq t^{\ast}\), which is a contradiction. Thus, \(\lim_{n\rightarrow\infty} t_{n}=1\). For any natural number p we have
$$\begin{aligned} &\theta\leq u_{n+p}-u_{n}\leq v_{n}-u_{n} \leq v_{n}-t_{n}v_{n}=(1-t_{n})v_{n} \leq(1-t_{n})v_{0}, \\ &\theta\leq v_{n}-v_{n+p}\leq v_{n}-u_{n} \leq(1-t_{n})v_{0}, \quad n=1,2,\ldots. \end{aligned}$$
Since the cone P is normal, we have
$$\| u_{n+p}-u_{n}\|\leq N(1-t_{n})\| v_{0}\|, \qquad \| v_{n}-v_{n+p}\|\leq N(1-t_{n})\| v_{0}\|, \quad n,p=1,2,\ldots, $$
where N is the normality constant of P. So we can claim that \(\{u_{n}\}\) and \(\{v_{n}\}\) are Cauchy sequences. Because E is complete, there exist \(u^{\ast}\), \(v^{\ast}\) such that \(u_{n}\rightarrow u^{\ast}\), \(v_{n}\rightarrow v^{\ast}\) as \(n\rightarrow\infty\). By (3.11), we know that \(u_{n}\leq u^{\ast}\leq v^{\ast}\leq v_{n}\) with \(u^{\ast}, v^{\ast}\in P_{h}\), and
$$\theta\leq v^{\ast}-u^{\ast}\leq v_{n}-u_{n} \leq(1-t_{n})v_{0}. $$
Further, by the normality of cone P, we have
$$\bigl\| v^{\ast}-u^{\ast}\bigr\| \leq N(1-t_{n})\|v_{0} \|\rightarrow0,\quad n\rightarrow\infty, $$
and thus \(u^{\ast}=v^{\ast}\). Let \(x^{\ast}:= u^{\ast}=v^{\ast}\) and then by the mixed monotone properties of T, we obtain
$$u_{n+1}=T(u_{n},v_{n})\leq T\bigl(x^{\ast},x^{\ast}\bigr)\leq T(v_{n},u_{n})=v_{n+1}, \quad n=1,2,3, \ldots. $$
Let \(n\rightarrow\infty\), then we get \(x^{\ast}=T(x^{\ast},x^{\ast})\). That is, \(x^{\ast}\) is a fixed point of T in \(P_{h}\).
In the following, we prove that \(x^{\ast}\) is the unique fixed point of T in \(P_{h}\). In fact, suppose x̅ is another fixed point of T in \(P_{h}\) and \(\overline{x}\neq x^{\ast}\). Since \(x^{\ast},\overline{x}\in P_{h}\), there exist positive numbers \({\mu}_{1},{\mu}_{2},{\lambda}_{1},{\lambda}_{2}>0\) such that
$${\mu}_{1}h\leq x^{\ast}\leq{\lambda}_{1}h ,\qquad { \mu}_{2}h\leq\overline{x}\leq{\lambda}_{2}h. $$
Then we obtain
$$\overline{x}\leq{\lambda}_{2}h=\frac{{\lambda}_{2}}{{\mu}_{1}}{\mu}_{1}h \leq \frac{{\lambda}_{2}}{{\mu}_{1}}x^{\ast},\qquad \overline{x}\geq \overline{ \mu}_{2}h=\frac{{\mu}_{2}}{{\lambda}_{1}}{\lambda}_{1}h\geq \frac{{\mu}_{2}}{{\lambda}_{1}}x^{\ast}. $$
Let
$$e_{1}=\sup\bigl\{ t>0 \mid tx^{\ast}\leq\overline{x}\leq t^{-1}x^{\ast}\bigr\} . $$
Evidently, \(0< e_{1}\leq1\), \(e_{1}x^{\ast}\leq\overline{x}\leq\frac{1}{e_{1}}x^{\ast}\). Next we prove \(e_{1}=1\). If \(0< e_{1}<1\), then by the mixed monotone properties of T and (3.8), we would get
$$\overline{x}=T(\overline{x},\overline{x})\geq T\biggl(e_{1}x^{\ast}, \frac {1}{e_{1}}x^{\ast}\biggr)\geq\psi\bigl(e_{1},x^{\ast},x^{\ast}\bigr)T\bigl(x^{\ast},x^{\ast}\bigr)=\psi \bigl(e_{1},x^{\ast},x^{\ast}\bigr)x^{\ast}. $$
Since \(\psi(e_{1},x^{\ast},x^{\ast})>e_{1}\), this contradicts the definition of \(e_{1}\), so we get \(e_{1}=1\). Thus \(\overline{x}= x^{\ast}\). Therefore, A has a unique fixed point \(x^{\ast}\) in \(P_{h}\).
Now we construct successively the sequences
$$x_{n}=T(x_{n-1},y_{n-1}), \qquad y_{n}=T(y_{n-1},x_{n-1}), \quad n=1,2,\ldots, $$
for any initial points \(x_{0},y_{0}\in P_{h}\). Since \(x_{0},y_{0}\in P_{h}\), we can choose small numbers \(e_{2},e_{3}\in(0,1)\) such that
$$e_{2}h\leq x_{0}\leq\frac{1}{e_{2}}h, \qquad e_{3}h\leq y_{0}\leq \frac{1}{e_{3}}h. $$
Let \(e_{\ast}=\min\{e_{2},e_{3}\}\). Then \(e_{\ast}\in(0,1)\) and
$$e_{\ast} h\leq x_{0} , y_{0}\leq \frac{1}{e_{\ast}}h. $$
Since \(e_{\ast}<\psi(e_{\ast},x,y)\leq1\), we can get \(1<\frac{\psi(e_{\ast},x,y)}{e_{\ast}}\leq\frac{1}{e_{\ast}}\). By the Archimedes principle, we can choose a sufficiently large positive integer m such that
$$\frac{\psi(e_{\ast},x,y)}{e_{\ast}}\geq \biggl(\frac{1}{e_{\ast}} \biggr)^{\frac{1}{m}}. $$
Put \(\overline{u}_{0}=e_{\ast}^{m}h\), \(\overline{v}_{0}=\frac{1}{e_{\ast}^{m}}h\). It is easy to see that \(\overline{u}_{0},\overline{v}_{0}\in P_{h}\), and \(\overline{u}_{0}< x_{0},y_{0}<\overline{v}_{0}\). Let
$$\overline{u}_{n}=T(\overline{u}_{n-1},\overline{v}_{n-1}), \qquad \overline {v}_{n}=T(\overline{v}_{n-1}, \overline{u}_{n-1}),\quad n=1,2,\ldots. $$
Similarly, it follows that there exists \(y^{*}\in P_{h}\) such that
$$T\bigl(y^{\ast},y^{\ast}\bigr)=y^{\ast},\qquad \lim _{n\rightarrow\infty}\overline{u}_{n}=\lim_{n\rightarrow\infty } \overline{v}_{n}=y^{\ast}. $$
By the uniqueness of the fixed points of the operator T in \(P_{h}\), we get \(x^{\ast}=y^{\ast}\). And by induction, \(\overline{u}_{n}\leq x_{n}\), \(y_{n}\leq\overline{v}_{n} \) (\(n=1,2,\ldots \)). Since the cone P is normal, we have \(\lim_{n\rightarrow\infty} x_{n}=\lim_{n\rightarrow\infty} y_{n}=x^{\ast}\). □
Remark 3.1
Theorem 3.1 is a fixed point theorem for the sum of three classes of mixed monotone operators, which extends the results in [11–14].
Taking \(B, C=\theta\) in Theorem 3.1, we get the following corollary.
Corollary 3.1
Let
P
be a normal cone in
E. Assume that
\(T:P\times P\rightarrow P\)
is a mixed monotone operator and satisfies the following conditions:
- (A1):
-
There exists
\(h\in P\)
with
\(h>\theta\)
such that
\(T(h,h) \in P_{h}\).
- (A2):
-
For any
\(t\in(0,1)\), there exists
\(\varphi(t)\in (t,1]\)
such that
$$T\bigl(tx,t^{-1}y\bigr)\geq\varphi(t)T(x,y), \quad \forall x,y\in P. $$
Then the operator
\(T(x,x)=x\)
has a unique solution
\(x^{\ast}\)
in
P, which satisfies
\(\mu h\leq x^{\ast}\leq\lambda h\), where
\(\lambda >0\), \(\mu>0\)
are two real numbers. Moreover, for any initial values
\(x_{0},y_{0}\in P_{h}\), by constructing successively the sequences as follows:
$$x_{n}=T(x_{n-1},y_{n-1}),\qquad y_{n}=T(y_{n-1},x_{n-1}), \quad n=1,2,\ldots, $$
we have
\(x_{n}\rightarrow x^{\ast}\)
and
\(y_{n}\rightarrow x^{\ast}\)
in
E, as
\(n\rightarrow\infty\).
Proof
Since X is a uniformly convex Banach space and A is bounded, we see that \(A_{0}\) is non-empty and \(\{(PT)^{n}(x)\}\) is bounded for any \(x\in A_{0}\). By Theorem 3.1, T has at least one best proximity point. □
Remark 3.2
Under the conditions (A1), (A2), this corollary not only guarantees the existence of upper-lower solutions for the operator T and the existence of a unique fixed point, but also it constructs successively some sequences for approximating the fixed point.
Taking \(A, B=\theta\) and \(\frac{1}{2}< c\leq1\) in Theorem 3.1, from the proof of Theorem 3.1 we get the following corollary.
Corollary 3.2
Let
P
be a normal cone in
E. Assume that
\(C:P\times P\rightarrow P\)
is a mixed monotone operator and satisfies the following conditions:
-
(1)
for any fixed
\(y\in P\), \(C(\cdot,y):P\rightarrow P\)
is concave; for any fixed
\(x\in P\), \(C(x,\cdot):P\rightarrow P\)
is convex;
-
(2)
there is
\(h\in P\), \(h>\theta\)
such that
\(C(h,h)\in P_{h}\);
-
(3)
there exists
\(\frac{1}{2}< c\leq1\), such that
\(C(\theta,lh)\geq cC(lh,\theta)\), \(l\geq1\).
Then the operator
\(C(x,x)=x\)
has a unique solution
\(x^{\ast}\)
in
P, which satisfies
\(\mu h\leq x^{\ast}\leq\lambda h\), where
\(\lambda >0\), \(\mu>0\)
are two real numbers. Furthermore, for any initial values
\(x_{0},y_{0}\in P_{h}\), by constructing successively the sequences as follows:
$$x_{n}=C(x_{n-1},y_{n-1}), \qquad y_{n}=C(y_{n-1},x_{n-1}), \quad n=1,2,\ldots, $$
we have
\(x_{n}\rightarrow x^{\ast}\)
and
\(y_{n}\rightarrow x^{\ast}\)
in
E, as
\(n\rightarrow\infty\).
Remark 3.3
In the above corollary we do not need to require the operator C to satisfy \(0< C(\theta,v)\leq v\), which extends the result in [12].
Taking \(\varphi(t)=t^{\alpha}\), \(\alpha\in(0,1)\), we get the following corollary, which generalizes and improves Theorem 2.1 in [21].
Corollary 3.3
Let
P
be a normal cone in
E, \(\alpha\in(0,1)\). Assume that
\(A, B, C:P\times P\rightarrow P\)
are three mixed monotone operators and satisfy the following conditions:
-
(1)
for any
\(t\in(0,1)\), \(x,y\in P\), we have
\(A(tx,t^{-1}y)\geq t^{\alpha}A(x,y)\);
-
(2)
for any
\(t\in(0,1)\), \(x,y\in P\), we have
\(B(tx,t^{-1}y)\geq tB(x,y)\);
-
(3)
for any fixed
\(y\in P\), \(C(\cdot,y):P\rightarrow P\)
is concave; for any fixed
\(x\in P\), \(C(x,\cdot):P\rightarrow P\)
is convex;
-
(4)
there is
\(h\in P\), \(h>\theta\)
such that
\(A(h,h)\in P_{h}\), \(B(h,h)\in P_{h}\), and
\(C(h,h)\in P_{h}\);
-
(5)
there exists
\(\frac{1}{2}\leq c\leq1\), such that
\(C(\theta,lh)\geq cC(lh,\theta)\), for any
\(l\geq1\);
-
(6)
there exists a constant
\(\delta_{0}>0\), such that
\(B(x,y)+C(x,y)\leq\delta_{0}A(x,y)\), \(\forall x,y \in P_{h}\).
Then the operator equation (1.1) has a unique solution
\(x^{\ast}\)
in
P, which satisfies
\(\mu h\leq x^{\ast}\leq\lambda h\), where
\(\lambda >0\), \(\mu>0\)
are two real numbers. Furthermore, for any initial values
\(x_{0},y_{0}\in P_{h}\), by constructing successively the sequences as follows:
$$\begin{aligned}& x_{n}=A(x_{n-1},y_{n-1})+B(x_{n-1},y_{n-1})+C(x_{n-1},y_{n-1}), \\& y_{n}=A(y_{n-1},x_{n-1})+B(y_{n-1},x_{n-1})+C(y_{n-1},x_{n-1}), \quad n=1,2,\ldots, \end{aligned}$$
we have
\(x_{n}\rightarrow x^{\ast}\)
and
\(y_{n}\rightarrow x^{\ast}\)
as
\(n\rightarrow\infty\).
Corollary 3.4
Let
P
be a normal cone in
E. Let
\(h>0\)
and
\(A, B, C:P_{h}\times P_{h}\rightarrow P_{h}\)
are three mixed monotone operators and satisfy the following conditions:
-
(1)
for any
\(t\in(0,1)\), there exists
\(\varphi(t)\in(t,1]\)
such that
$$A\bigl(tx,t^{-1}y\bigr)\geq\varphi(t)A(x,y), \quad \forall x,y \in P_{h}; $$
-
(2)
for any
\(t\in(0,1)\), \(x,y \in P_{h}\), \(B(tx,t^{-1}y)\geq tB(x,y)\);
-
(3)
for any fixed
\(y\in P_{h}\), \(C(\cdot,y):P_{h}\rightarrow P_{h}\)
is concave; for any fixed
\(x\in P_{h}\), \(C(x,\cdot):P_{h}\rightarrow P_{h}\)
is convex;
-
(4)
there exists
\(\frac{1}{2}\leq c\leq1\), such that
\(C(\theta,lh)\geq cC(lh,\theta)\), \(l\geq1\);
-
(5)
there exists a constant
\(\delta_{0}>0\), such that
\(B(x,y)+C(x,y)\leq\delta_{0}A(x,y)\), \(\forall x,y \in P_{h}\).
Then the operator of equation (1.1) has a unique solution
\(x^{\ast}\)
in
P, which satisfies
\(\mu h\leq x^{\ast}\leq\lambda h\), where
\(\lambda >0\), \(\mu>0\)
are two real numbers. And for any initial values
\(x_{0},y_{0}\in P_{h}\), by constructing successively the sequences as follows:
$$\begin{aligned}& x_{n}=A(x_{n-1},y_{n-1})+B(x_{n-1},y_{n-1})+C(x_{n-1},y_{n-1}), \\& y_{n}=A(y_{n-1},x_{n-1})+B(y_{n-1},x_{n-1})+C(y_{n-1},x_{n-1}), \quad n=1,2,\ldots, \end{aligned}$$
we have
\(x_{n}\rightarrow x^{\ast}\)
and
\(y_{n}\rightarrow x^{\ast}\)
as
\(n\rightarrow\infty\).
Remark 3.4
If P is a solid cone, \(h\in\overset{\circ }{P}\). If we suppose that the operators \(A, B, C:P_{h}\times P_{h}\rightarrow P_{h}\) or \(A, B, C:\overset{\circ}{P}\times\overset{\circ}{P}\rightarrow \overset{\circ}{P}\), then \(A(h,h)\in P_{h}\), \(B(h,h)\in P_{h}\), and \(C(h,h)\in P_{h}\) are automatically satisfied in Corollary 3.4.
Theorem 3.2
Let
P
be a normal cone in
E. \(A, B, C:P\times P\rightarrow P\)
are three mixed monotone operators and satisfy the following conditions:
-
(1)
for any
\(t\in(0,1)\), there exists
\(\varphi(t)\in(t,1]\)
such that
$$A\bigl(tx,t^{-1}y\bigr)\geq\varphi(t)A(x,y), \quad\forall x,y\in P; $$
-
(2)
for any
\(t\in(0,1)\), \(x,y\in P\), \(B(tx,t^{-1}y)\geq tB(x,y)\);
-
(3)
for any fixed
\(y\in P\), \(A(\cdot,y):P\rightarrow P\)
is concave; for any fixed
\(x\in P\), \(A(x,\cdot):P\rightarrow P\)
is convex;
-
(4)
there is
\(h\in P\), \(h>\theta\)
such that
\(A(h,h)\in P_{h}\), \(B(h,h)\in P_{h}\), and
\(C(h,h)\in P_{h}\);
-
(5)
there exists
\(\frac{1}{2}\leq c\leq1\), such that
\(C(\theta,lh)\geq cC(lh,\theta)\), \(l\geq1\);
-
(6)
there exists a constant
\(\delta_{0}>0\), such that
\(B(x,y)+C(x,y)\leq\delta_{0}A(x,y)\), \(\forall x,y \in P_{h}\).
Then for any given
\(\lambda>0\), the operator equation
$$A(x,x)+B(x,x)+C(x,x)=\lambda x $$
has a unique solution
\(x_{\lambda}\)
in
P, which satisfies
\(\mu h\leq x_{\lambda}\leq\lambda h\), where
\(\lambda >0\), \(\mu>0\)
are two real numbers. Furthermore, we have the following conclusions:
-
(R1)
if
\(\varphi(t)>t^{\frac{1}{2}}(\delta_{0}+1)-\delta_{0}t\)
for
\(t\in(0,1)\), then
\(x_{\lambda}\)
is strictly decreasing in
λ, that is, \(0<\lambda_{1}<\lambda_{2}\)
implies
\(x_{\lambda_{1}}> x_{\lambda_{2}}\);
-
(R2)
if there exists
\(\beta\in(0,1)\)
such that
\(\varphi(t)\geq t^{\beta}(\delta_{0}+1)-\delta_{0}t\)
for
\(t\in(0,1)\), then
\(x_{\lambda}\)
is continuous in
λ, that is, \(\lambda\rightarrow\lambda_{0} \) (\(\lambda_{0}>0\)) implies
\(\| x_{\lambda}-x_{\lambda_{0}}\|\rightarrow0\);
-
(R3)
if there exists
\(\beta\in(0,\frac{1}{2})\)
such that
\(\varphi(t)\geq t^{\beta}(\delta_{0}+1)-\delta_{0}t\)
for
\(t\in (0,1)\), then
\(\lim_{\lambda\rightarrow\infty} \| x_{\lambda}\|=0\), \(\lim_{\lambda\rightarrow0^{+}} \| x_{\lambda}\|=\infty\).
Proof
For fixed \(\lambda>0\), by Theorem 3.1, \(\frac{1}{\lambda}T: P_{h}\times P_{h}\rightarrow P_{h}\) is mixed monotone and satisfies
$$\biggl(\frac{1}{\lambda}T \biggr) \bigl(tx,t^{-1}y \bigr)= \frac{1}{\lambda }T \bigl(tx,t^{-1}y \bigr)\geq \frac{1}{\lambda} \psi(t,x,y)T(x,y)=\psi(t,x,y) \biggl(\frac{1}{\lambda }T \biggr) (x,y), $$
for any \(x,y\in P_{h}\), \(t\in(0,1)\). So it follows from Theorem 3.1 that \(\frac{1}{\lambda}T\) has a unique fixed point \(x_{\lambda}\) in \(P_{h}\). That is, \(T(x_{\lambda},x_{\lambda})=\lambda x_{\lambda}\). For convenience of proof, we let
$$\alpha(t,x,y)=\frac{\ln\psi(t,x,y)}{\ln t}, \quad \forall t\in(0,1). $$
Then \(\alpha(t,x,y)\in[0,1)\) and \(\psi(t,x,y)=t^{\alpha(t,x,y)}\). Thus \(T(tx,t^{-1}y)\geq t^{\alpha(t,x,y)}T(x,y)\), for any \(x,y\in P_{h}\), \(t\in(0,1)\).
(1) Proof of (R1). Suppose \(0<\lambda_{1}<\lambda_{2}\) and let
$$t_{0}=\sup\{t>0\mid x_{\lambda_{1}}\geq tx_{\lambda_{2}}, x_{\lambda_{2}}\geq tx_{\lambda_{1}}\}, $$
then we have \(0< t_{0}<1\) and
$$ x_{\lambda_{1}}\geq t_{0}x_{\lambda_{2}},\qquad x_{\lambda_{2}}\geq t_{0}x_{\lambda_{1}}. $$
(3.13)
By the mixed monotone properties of T,
$$\begin{aligned}& \lambda_{1}x_{\lambda_{1}}=T (x_{\lambda_{1}},x_{\lambda_{1}} ) \geq T \bigl(t_{0}x_{\lambda_{2}},t_{0}^{-1}x_{\lambda_{2}} \bigr)\geq t_{0}^{\alpha (t_{0},x_{\lambda_{2}},x_{\lambda_{2}} )}T(x_{\lambda_{2}},x_{\lambda_{2}}) =t_{0}^{\alpha (t_{0},x_{\lambda_{2}},x_{\lambda_{2}} )}\lambda _{2}x_{\lambda_{2}}, \\& \lambda_{2}x_{\lambda_{2}}=T(x_{\lambda_{2}},x_{\lambda_{2}})\geq T\bigl(t_{0}x_{\lambda_{1}},t_{0}^{-1}x_{\lambda_{1}} \bigr)\geq t_{0}^{\alpha (t_{0},x_{\lambda_{1}},x_{\lambda_{1}} )}T(x_{\lambda_{1}},x_{\lambda_{1}}) =t_{0}^{\alpha (t_{0},x_{\lambda_{1}},x_{\lambda_{1}} )}\lambda _{1}x_{\lambda_{1}}. \end{aligned}$$
Further
$$ x_{\lambda_{1}}\geq \lambda_{1}^{-1}\lambda_{2}t_{0}^{\alpha (t_{0},x_{\lambda _{2}},x_{\lambda_{2}} )}x_{\lambda_{2}}, \qquad x_{\lambda_{2}}\geq \lambda_{2}^{-1} \lambda_{1}t_{0}^{\alpha (t_{0},x_{\lambda _{1}},x_{\lambda_{1}} )}x_{\lambda_{1}}. $$
(3.14)
Noting that \(\lambda_{1}^{-1}\lambda_{2}t_{0}^{\alpha (t_{0},x_{\lambda _{2}},x_{\lambda_{2}} )}>t_{0}\), from the definition of \(t_{0}\) and (3.14), we get
$$\lambda_{2}^{-1}\lambda_{1}t_{0}^{\alpha (t_{0},x_{\lambda _{1}},x_{\lambda_{1}} )} \leq t_{0}, $$
which in turn yields
$$ t_{0}\geq \biggl(\frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac{1}{1-\alpha (t_{0},x_{\lambda_{1}},x_{\lambda_{1}} )}}. $$
(3.15)
Hence
$$ x_{\lambda_{1}}\geq \lambda_{1}^{-1}\lambda_{2} \biggl(\frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac{\alpha (t_{0},x_{\lambda_{2}},x_{\lambda_{2}} )}{1-\alpha (t_{0}, x_{\lambda_{1}},x_{\lambda_{1}} )}}x_{\lambda_{2}} = \biggl( \frac{\lambda_{2}}{\lambda_{1}} \biggr)^{\frac{1-2\alpha (t_{0},x_{\lambda_{1}},x_{\lambda_{1}} )}{1-\alpha (t_{0}, x_{\lambda_{2}},x_{\lambda_{2}} )}}x_{\lambda_{2}}. $$
(3.16)
Noting that \(\varphi(t_{0})>t_{0}^{\frac{1}{2}}(\delta_{0}+1)-\delta_{0}t_{0}\), we have \(\psi (t_{0},x,y )>\frac{\varphi(t_{0})+\delta_{0}t_{0}}{\delta _{0}+1}>t_{0}^{\frac{1}{2}}\), and thus we have \(\alpha (t_{0},x,y )<\frac{1}{2}\) and consequently,
$$\biggl(\frac{\lambda_{2}}{\lambda_{1}} \biggr)^{\frac{1-2\alpha (t_{0},x_{\lambda_{1}},x_{\lambda_{1}} )}{1-\alpha (t_{0}, x_{\lambda_{2}},x_{\lambda_{2}} )}}>1. $$
Thus, \(x_{\lambda_{1}}> x_{\lambda_{2}}\).
(2) Proof of (R2). Since \(\varphi(t)\geq t^{\beta}(\delta_{0}+1)-\delta_{0}t\) for \(t\in(0,1)\), we have \(\psi(t,x,y)>\frac{\varphi(t_{0})+\delta_{0}t_{0}}{\delta_{0}+1}\geq t^{\beta}\) for \(t\in(0,1)\), and thus we get \(\alpha(t,x,y)\leq\beta\) for \(t\in(0,1)\). By (3.13) and (3.15), we have
$$\begin{aligned}& \begin{aligned}[b] \biggl(\frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac{1}{1-\beta }}x_{\lambda_{2}} &\leq \biggl(\frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac{1}{1-\alpha (t_{0},x_{\lambda_{1}},x_{\lambda_{1}} )}}x_{\lambda_{2}} \leq x_{\lambda_{1}} \\ &\leq\frac{1}{t_{0}}x_{\lambda_{2}} \leq \biggl(\frac{\lambda_{2}}{\lambda_{1}} \biggr)^{\frac{1}{1-\alpha (t_{0},x_{\lambda_{1}},x_{\lambda_{1}} )}}x_{\lambda_{2}} \leq \biggl(\frac{\lambda_{2}}{\lambda_{1}} \biggr)^{\frac{1}{1-\beta }}x_{\lambda_{2}}, \end{aligned} \end{aligned}$$
(3.17)
$$\begin{aligned}& \begin{aligned}[b] \biggl(\frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac{1}{1-\beta }}x_{\lambda_{1}} &\leq \biggl(\frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac{1}{1-\alpha (t_{0},x_{\lambda_{1}},x_{\lambda_{1}} )}}x_{\lambda_{1}} \leq x_{\lambda_{2}} \leq\frac{1}{t_{0}}x_{\lambda_{1}} \\ &\leq \biggl(\frac{\lambda_{2}}{\lambda_{1}} \biggr)^{\frac{1}{1-\alpha (t_{0},x_{\lambda_{1}},x_{\lambda_{1}} )}}x_{\lambda_{1}} \leq \biggl(\frac{\lambda_{2}}{\lambda_{1}} \biggr)^{\frac{1}{1-\beta }}x_{\lambda_{1}}. \end{aligned} \end{aligned}$$
(3.18)
Further
$$\theta\leq x_{\lambda_{1}}- \biggl(\frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac {1}{1-\beta}}x_{\lambda_{2}} \leq \biggl[ \biggl(\frac{\lambda_{2}}{\lambda_{1}} \biggr)^{\frac{1}{1-\beta}}- \biggl( \frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac{1}{1-\beta}} \biggr]x_{\lambda_{2}}. $$
Consequently, from the normality of cone P and (3.17), we get
$$\begin{aligned} \Vert x_{\lambda_{1}}-x_{\lambda_{2}}\Vert &\leq \biggl\Vert x_{\lambda_{1}}- \biggl(\frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac {1}{1-\beta}}x_{\lambda_{2}} \biggr\Vert +\biggl\Vert \biggl(\frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac{1}{1-\beta }}x_{\lambda_{2}}-x_{\lambda_{2}} \biggr\Vert \\ &\leq N \biggl[ \biggl(\frac{\lambda_{2}}{\lambda_{1}} \biggr)^{\frac{1}{1-\beta }}- \biggl( \frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac{1}{1-\beta }} \biggr] \| x_{\lambda_{2}}\|+\biggl\vert \biggl(\frac{\lambda_{1}}{\lambda_{2}} \biggr)^{\frac{1}{1-\beta}}-1\biggr\vert \| x_{\lambda_{2}}\|, \end{aligned}$$
where N is the normality constant. Let \(\lambda_{1}\rightarrow\lambda_{2}^{-}\), we have \(\|x_{\lambda_{1}}-x_{\lambda_{2}}\|\rightarrow0\). Similarly, let \(\lambda_{2}\rightarrow\lambda_{1}^{+}\), from (3.18) we can also prove \(\| x_{\lambda_{2}}-x_{\lambda_{1}}\|\rightarrow0\). So the conclusion (R2) holds.
(3) Proof of (R3). Since \(\varphi(t)\geq t^{\beta}(\delta_{0}+1)-\delta_{0}t\) for \(t\in(0,1)\), we have \(\psi(t,x,y)>\frac{\varphi(t_{0})+\delta_{0}t_{0}}{\delta_{0}+1}\geq t^{\beta}\) for \(t\in(0,1)\), and thus we have \(\alpha(t,x,y)\leq\beta<\frac{1}{2}\) for \(t\in(0,1)\). Let \(\lambda_{1}=1\), \(\lambda_{2}=\lambda\) in (3.16), then we have
$$x_{1}\geq \lambda^{\frac{1-2\alpha (t_{0},x_{1},x_{1} )}{1-\alpha (t_{0},x_{\lambda},x_{\lambda} )}}x_{\lambda} \geq \lambda^{\frac{1-2\beta}{1-\beta}}x_{\lambda},\quad \forall\lambda>1. $$
Thus we can easily obtain
$$\| x_{\lambda}\|\leq\frac{N}{\lambda^{\frac{1-2\beta}{1-\beta}}}\| x_{1}\|, \quad \forall \lambda>1, $$
where N is the normality constant. Let \(\lambda\rightarrow\infty\), then \(\| x_{\lambda}\|\rightarrow0\). Similarly, let \(\lambda_{1}=\lambda\), \(\lambda_{2}=1\) in (3.16), then
$$x_{\lambda}\geq \lambda^{-\frac{1-2\alpha (t_{0},x_{\lambda},x_{\lambda} )}{1-\alpha (t_{0},x_{1},x_{1} )}}x_{1} \geq \lambda^{-\frac{1-2\beta}{1-\beta}}x_{1},\quad \forall0< \lambda< 1. $$
Thus
$$\| x_{\lambda}\|\geq N^{-1}\lambda^{-\frac{1-2\beta}{1-\beta}}\| x_{1}\|,\quad \forall0< \lambda< 1, $$
where N is the normality constant. Let \(\lambda\rightarrow0^{+}\), then we have \(\| x_{\lambda}\|\rightarrow\infty\). □