\documentclass[reqno]{amsart}
\usepackage{hyperref}

\AtBeginDocument{{\noindent\small
\emph{Electronic Journal of Differential Equations},
Vol. 2012 (2012), No. 235, pp. 1--9.\newline
ISSN: 1072-6691. URL: http://ejde.math.txstate.edu or http://ejde.math.unt.edu
\newline ftp ejde.math.txstate.edu}
\thanks{\copyright 2012 Texas State University - San Marcos.}
\vspace{9mm}}

\begin{document}
\title[\hfilneg EJDE-2012/235\hfil Random differential equations]
{Solutions to fourth-order random differential equations
with periodic boundary conditions}

\author[X. Han, X. Ma, G. Dai \hfil EJDE-2012/235\hfilneg]
{Xiaoling Han, Xuan Ma, Guowei Dai} 

\address{Xiaoling Han\newline
Department of Mathematics,
Northwest Normal University,
Lanzhou, 730070,  China}
\email{hanxiaoling@nwnu.edu.cn}

\address{Xuan Ma  \newline
Department of Mathematics,
Northwest Normal University,
Lanzhou, 730070,  China}
\email{sfsolo@163.com}

\address{Guowei Dai  \newline
Department of Mathematics,
Northwest Normal University,
Lanzhou, 730070,  China}
\email{daiguowei@nwnu.edu.cn}


\thanks{Submitted October 17, 2012. Published December 21, 2012.}
\thanks{Supported by grants 11101335 and 11261052
 from the National Natural
Science Foundation \hfill\break\indent of China}
\subjclass[2000]{47H40, 47N20, 60H25}
\keywords{Random differential equation; periodic boundary conditions;
\hfill\break\indent random solution;  extremal solutions}

\begin{abstract}
 Existence of solutions and of extremal random
 solutions are proved for  periodic boundary-value problems
 of fourth-order ordinary random differential equations.
 Our investigation is done in the space of continuous real-valued
 functions defined  on closed and bounded intervals.
 Also we study the applications of the random version of a nonlinear
 alternative of Leray-Schauder type and an algebraic
 random fixed point theorem by Dhage.
\end{abstract}

\maketitle
\numberwithin{equation}{section}
\newtheorem{theorem}{Theorem}[section]
\newtheorem{lemma}[theorem]{Lemma}
\newtheorem{definition}[theorem]{Definition}
\allowdisplaybreaks

\section{Introduction}

Let $\mathbb{R}$ denote the real line and let $J =[0, 1]$, a closed 
and bounded interval in $\mathbb{R}$.
 Let $C^1(J, \mathbb{R})$ denote the class of real-valued functions 
defined and continuously on $J$. Given a measurable space 
$(\Omega, \mathcal{A})$ and a measurable function 
$x: \Omega \to AC^{3}(J, \mathbb{R})$, we consider a fourth-order periodic 
boundary-value problem of ordinary random differential equations 
(for short PBVP)
\begin{equation}
\begin{gathered}
  x^{(4)}(t,\omega)=f(t,x(t,\omega),x''(t,\omega),\omega) \quad
\text{a.e. } t\in J\\
  x^{(i)}(0,\omega)=x^{(i)}(1,\omega),\quad  i=0,1,2,3
\end{gathered} \label{e1}
\end{equation}
for all $\omega\in \Omega$, where
$f:J\times\mathbb{R}\times\mathbb{R}\times\Omega\to\mathbb{R}$.

  By a \emph{random solution} of equation \eqref{e1} we mean a measurable 
function  $x:\Omega\to AC^{(3)}(J,\mathbb{R})$ that satisfies the
equation \eqref{e1}, where $AC^{(3)}(J,\mathbb{R})$ is the space 
of real-valued functions whose 3rd derivative exists and is 
absolutely continuously differentiable on $J$.

When the random parameter $\omega$ is absent, the random \eqref{e1} 
reduce to the fourth-order ordinary differential equations,
\begin{equation}
\begin{gathered}
     x^{(4)}(t)=f(t,x(t),x''(t)) \quad\text{a.e. }  t\in J\\
     x^{(i)}(0)=x^{(i)}(1),    \quad  i = 0, 1, 2, 3
\end{gathered}\label{e2}
\end{equation}
where, $f:J\times\mathbb{R}\to\mathbb{R}$.

 Equation \eqref{e2} has been studied  by many authors for different aspects 
of solutions. See for example \cite{j1,j2,l3,l4,m1}.
Only a few authors have studied the random periodic boundary-value problem, 
see \cite{d4,c1,z1}, 
Dhage \cite{d4} studied the periodic boundary-value problems for the
 random differential equation
\begin{gather*}
  -   x''(t,\omega)=f(t,x(t,\omega),\omega) \quad\text{a.e. } t \in J,\\
     x(0,\omega)=x(2\pi,\omega),  \quad x'(0,\omega)=x'(2\pi,\omega)\,.
\end{gather*}

In this article, we study the existence of solutions and the 
existence of extremal solutions for the fourth-order random equation \eqref{e1},
under suitable conditions. Our work relays on the random versions of fixed 
point theorems based on the theorems in \cite{d1,d2}.


\section{Existence result}

Let $E$ denote a Banach space with the norm $\|\cdot\|$ and let $Q:E\to E$. 
We further assume that the Banach space $E$ is separable; i.e., $E$ 
has a countable dense subset and let $\beta_{E}$ be the $\sigma$-algebra 
of Borel subsets of $E$. We say a mapping $x:\Omega\to E$ is measurable
 if for any $B\in\beta_{E}$,
$$
      x^{-1}(B)=\{\omega\in\Omega: x(\omega)\in B\}\in\mathcal{A}.
$$
To define integrals of sample paths of random process, it is necessary 
to define a map is jointly measurable, a mapping $x:\Omega\times E\to E$ 
is called $jointly measurable$, if for any $B\in\beta_{E}$, one has
$$
  x^{-1}(B)=\{(\omega,x)\in\Omega\times E: x(\omega,x)\in B\}
\in\mathcal{A}\times\beta_{E},
$$
where $\mathcal{A}\times\beta_{E}$ is the direct product of the 
$\sigma$-algebras $\mathcal{A}$ and $\beta_{E}$ those defined in 
$\Omega$ and $E$ respectively.

Let $Q:\Omega\times E\to E$ be a mapping. Then $Q$ is called a random 
operator if $Q(\omega,x)$ is measurable in $\omega$ for all $x\in E$ 
and it is expressed as $Q(\omega)x=Q(\omega,x)$. A random operator
$Q(\omega)$ on $E$ is called continuous (resp. compact, totally bounded 
and completely continuous) if $Q(\omega,x)$ is continuous 
(resp. compact, totally bounded and completely continuous) in $x$ 
for all $\omega\in\Omega$. We could get more details of completely 
continuous random operators on Banach spaces and their properties 
in Itoh \cite{i1}. 
In this article, we use the following lemma in proving  
the main result of this paper, that lemma is an immediate 
corollary to the results in \cite{d1,d2}.

\begin{lemma}[\cite{d4}] \label{lem2.1}
 Let $\mathcal{B}_{R}(0)$ and $\bar{\mathcal{B}}_{R}(0)$ be the open and 
closed balls centered at origin of radius $R$ in the separable Banach 
space $E$ and let $Q:\Omega\times\bar{\mathcal{B}}_{R}(0)\to E$ be 
a compact and continuous random operator. Further suppose that 
there does not exists an $u\in E$ with $\| u\|=R$ such that 
$Q(\omega)u=\alpha u$ for all $\alpha\in \Omega$, where $\alpha>1$. 
Then the random equation $Q(\omega)x=x$ has a random solution; i.e., 
there is a measurable function $\xi:\Omega\to \bar{\mathcal{B}}_{R}(0)$ 
such that $Q(\omega)\xi(\omega)=\xi(\omega)$ for all $\omega\in\Omega$.
\end{lemma}

\begin{lemma}[\cite{d4}] \label{lem2.2}
 Let $Q:\Omega\times E\to E$ be a mapping such that $Q(\cdot,x)$ 
is measurable for all $x\in E$ and $Q(\omega,\cdot)$ is continuous 
for all $\omega\in \Omega$. Then the map $(\omega,x)\to Q(\omega,x)$ 
is jointly measurable.
\end{lemma}

We need the following definitions in the sequel.

\begin{definition} \label{def2.1}\rm
 A function $f:J\times\mathbb{R}\times\mathbb{R}\times\Omega\to\mathbb{R}$ 
is called random Carath\'eodory if
\begin{itemize}
  \item  the map $(t,\omega)\to f(t,x,y,\omega)$ is jointly measurable
for all $(x,y)\in\mathbb{R}^{2}$, and
  \item  the map $(x,y)\to f(t,x,y,\omega)$ is continuous for
almost all $t\in J$ and $\omega\in \Omega$.
\end{itemize}
\end{definition}

\begin{definition} \label{def2.2}\rm
A function $f:J\times\mathbb{R}\times\mathbb{R}\times\Omega\to \mathbb{R}$ 
is called random $L^1$-Carath\'eodory if
\begin{itemize}
  \item %[(3)] 
for each real number $r>0$ there is a measurable and bounded function
 $q_{r}:\Omega\to L^1(J,\mathbb{R})$ such that
  \begin{gather*}
    | f(t,x,y,\omega)| \leq q_{r}(t,\omega) \quad\text{a.e. } t\in J
  \end{gather*}
  whenever $| x|,| y| \leq r$, and for all $\omega\in\Omega$.
\end{itemize}
\end{definition}

 Now we seek the random solutions of \eqref{e1} in the Banach space 
$C(J,\mathbb{R})$ of continuous real-valued functions defined on $J$. 
We equip this space  with the supremum norm
$$
\| x\|=\sup_{t\in J}| x(t)|.
$$
It is know that the Banach space $C(J,\mathbb{R})$ is separable. 
We use $L^1(J,\mathbb{R})$ denote the space of Lebesque measurable 
real-valued functions defined on $J$, and the usual norm in 
$L^1(J,\mathbb{R})$ defined by
$$
       \| x\|_{L^1}=\int_{0}^1| x(t)| dt.
$$
For a given real number $M\in(0,4\pi^{4}), h\in C(J,\mathbb{R})$, 
consider the linear PBVP
\begin{equation}
\begin{gathered}
     x^{(4)}(t)+Mx(t)=h(t) \quad  t\in J\\
     x^{(i)}(0)=x^{(i)}(1), \quad  i = 0, 1, 2, 3.
\end{gathered}
\label{e3}
\end{equation}
By the theorem of \cite{l2}, the unique solution of problem
\begin{equation}
\begin{gathered}
     x^{(4)}(t)+Mx(t)=0    \quad   t\in J\\
     x^{(i)}(0)=x^{(i)}(1),  \quad i = 0, 1, 2\\
     x^{(3)}(0)-x^{(3)}(1)=1
\end{gathered}\label{e4}
\end{equation}
has a unique solution $r(t)\in C^{4}(J,\mathbb{R})$ satisfying $r(t)>0$.
Then  the unique solution of \eqref{e3} is
\begin{equation}
      x(t)=\int^1_{0}G(t,s)h(s)ds,      \label{e5}
\end{equation}
where
\begin{equation}
  G(t,s)= \begin{cases}
                r(t-s), & 0\leq s\leq t\leq1; \\
                r(1+t-s), & 0\leq t<s\leq1.
     \end{cases}     \label{e6}
\end{equation}
We consider the following set of hypotheses:
\begin{itemize}
  \item[(H1)] The function $f$ is random Carath\'{e}odory on
$J\times\mathbb{R}\times\mathbb{R}\times\Omega$.
  \item[(H2)] There exists a measurable and bounded function
$\gamma:\Omega\to L^{2}(J,\mathbb{R})$ and a continuous and nondecreasing
function $\psi:\mathbb{R}_{+}\to(0,\infty)$ such that
$$
 | f(s,x,x'',\omega)+Mx|\leq\gamma(t,\omega)\psi(| x|) \quad\text{a.e. }t\in J
$$
for all $\omega\in\Omega$ and $x\in\mathbb{R}$.
\end{itemize}
Our main existence result is as follows.

\begin{theorem} \label{thm2.1}
 Assume that  {\rm (H1)--(H2)} hold. Suppose that there exists 
a real number $R>0$ such that
\begin{equation}
R>r_{M}\| \gamma(\omega)\|_{L^1}\psi(R)\label{e7}
\end{equation}
for all $t\in J$ and $\omega\in \Omega$,
where $r_{M}=\max_{t\in[0,1]}r(t), r(t)$ is in the Green's function
\eqref{e6}. Then  \eqref{e1} has a random solution defined on $J$.
\end{theorem}

\begin{proof} 
Set $E=C(J,\mathbb{R})$ and define a mapping $Q:\Omega\times E\to E$ by
\begin{equation}
  Q(\omega)x(t)=\int_{0}^1G(t,s)(f(s,x(s,\omega),
x''(s,\omega),\omega)+Mx(s,\omega))ds \label{e8}
\end{equation}
for all $t\in J$, $\omega\in\Omega$.
Then the solutions of \eqref{e1} are fixed points of operator $Q$.

Define a closed ball $\bar{\mathcal{B}}_{R}(0)$ in $E$ 
centered at origin 0 of radius $R$, where the real number $R$ 
satisfies the inequality \eqref{e7}. We show that $Q$ satisfies all the 
conditions of Lemma2.1 on $\bar{\mathcal{B}}_{R}(0)$.

First we show that $Q$ is a random operator in 
$\bar{\mathcal{B}}_{R}(0)$, since $f(t,x,x'',\omega)$ is random 
Carath\'{e}odory and $x(t,\omega)$ is measurable,  
the map $\omega\to f(t,x,x'',\omega)+Mx$ is measurable. 
Similarly, the production 
$G(t,s)[f(s,x(s,\omega),x''(s,\omega),\omega)+Mx(s,\omega)]$ 
of a continuous and measurable function is again measurable. 
Further, the integral is a limit of a finite sum of measurable functions, 
therefore, the map
$$
     \omega\mapsto\int_{0}^1G(t,s)(f(s,x(s,\omega),x''(s,\omega),\omega)
+Mx(s,\omega))ds=Q(\omega)x(t)
$$
is measurable. As a result, $Q$ is a random operator on 
$\Omega\times\bar{\mathcal{B}}_{R}(0)$ into $E$.

Next we show that the random operator $Q(\omega)$ is continuous 
on $\bar{\mathcal{B}}_{R}(0)$. Let ${x_{n}}$ be a sequence of points 
in $\bar{\mathcal{B}}_{R}(0)$ converging to the point $x$ in
 $\bar{\mathcal{B}}_{R}(0)$. Then it is sufficiente to prove that
$$
\lim_{n\to\infty}Q(\omega)x_{n}(t)=Q(\omega)x(t) \quad\text{for all }
t\in J, \omega\in\Omega.
$$ 
By the dominated convergence theorem, we obtain
\begin{align*}
    \lim_{n\to\infty}Q(\omega)x_{n}(t)  
&= \lim_{n\to\infty}\int_{0}^1G(t,s)(f(s,x_{n}(s,\omega),x_{n}''(s,\omega),\omega)
 +Mx_{n}(s,\omega))ds\\
&= \int_{0}^1G(t,s)\lim_{n\to\infty}[f(s,x_{n}(x,\omega),x''_{n}(s,\omega),\omega)
 +Mx_{n}(s,\omega)]ds\\
&= \int_{0}^1G(t,s)[f(s,x(s,\omega),x''(s,\omega),\omega)+Mx_{n}(s,\omega)]ds\\
&= Q(\omega)x(t)
\end{align*}
for all $t\in J,  \omega\in\Omega$. This shows that  $Q(\omega)$ 
is a continuous random operator on $\bar{\mathcal{B}}_{r}(0)$.

Now we show that $Q(\omega)$ is compact random operator on 
$\bar{\mathcal{B}}_{R}(0)$. To finish it, we should prove that
$Q(\omega)(\bar{\mathcal{B}}_{r}(0))$ is uniformly bounded and 
equi-continuous set in $E$ for each $\omega\in \Omega$. 
Since the map $\omega\to \gamma(t,\omega)$ is bounded and 
$L^{2}(J,\mathbb{R})\subset L^1(J,\mathbb{R})$, by (H$_2$),
there is a constant $c$ such that $\| \gamma(\omega)\|_{L^1}\leq c$ 
for all $\omega\in\Omega$. Let $\omega\in \Omega$ be fixed, 
then for any $x:\Omega\to\bar{\mathcal{B}}_{R}(0)$, one has
\begin{align*}
    | Q(\omega)x(t)| 
&\leq \int_{0}^1G(t,s)| (f(s,x(s,\omega),x''(s,\omega),\omega)+Mx(s,\omega))| ds\\
&\leq \int_{0}^1G(t,s) \gamma(s,\omega)\psi(| x(s,\omega)|)ds\\
&\leq r_{M}c\psi(R)
= K
\end{align*}
for all $t\in J$ and each $\omega \in \Omega$. This shows that 
$Q(\omega)(\bar{\mathcal{B}}_{R}(0))$ is a uniformly bounded subset 
of $E$ for each $\omega\in \Omega$.

Next we show $Q(\omega)(\bar{\mathcal{B}}_{R}(0))$ is an equi-continuous
 set in $E$. For  any $x\in\bar{\mathcal{B}}_{R}(0)$, $t_1,t_2\in J$,
we have
\begin{align*}
    | Q(\omega)x(t_1)-Q(\omega)x(t_2)|  
&\leq \int_{0}^1| (G(t_1,s)-G(t_2,s)) | \gamma(s,\omega)\psi(| x(s,\omega)|)ds\\
&\leq \int_{0}^1| (G(t_1,s)-G(t_2,s))| \gamma(s,\omega) \psi(R)ds,
\end{align*}
by h\"{o}lder inequality,
\begin{align*}
&| Q(\omega)x(t_1)-Q(\omega)x(t_2)| \\
&\leq \Big(\int_{0}^1| G(t_1,s)-G(t_2,s)|^{2}ds\Big)^{1/2}
\Big(\int_{0}^1| \gamma(s,\omega)|^{2}ds\Big)^{1/2}\psi(R).
\end{align*}
Hence for all $t_1,t_2\in J$,
$$
| Q(w)x(t_1)-Q(\omega)x(t_2)|\to 0  \quad\text{as } t_1\to t_2
$$ 
uniformly for all $x\in\bar{\mathcal{B}}_{R}(0)$. 
Therefore, $Q(\omega)\bar{\mathcal{B}}_{R}(0)$ is an equi-continuous 
set in $E$, then we know it is compact by Arzel\'{a}-Ascoli theorem 
for each $\omega\in \Omega$. Consequently, $Q(\omega)$ is a completely 
continuous random operator on $\bar{\mathcal{B}}_{R}(0)$.

Finally, we suppose there exists such an element $u$ in $E$ 
with $\| u\|=R$ satisfying $Q(\omega)u(t)=\alpha u(t,\omega)$ 
for some $\omega\in \Omega$, where $\alpha>1$. 
Now for this $\omega\in\Omega$, we have
\begin{align*}
    | u(t,\omega)| &\leq \frac{1}{\alpha}| Q(\omega)u(t)|\\
&\leq \int_{0}^1G(t,s)| f(s,u(s,\omega),u''(s,\omega),\omega)+Mu(s,\omega)| ds\\
&\leq r_{M}\int_{0}^1 \gamma(s,\omega)\psi(| u(s,\omega)|)ds\\
&\leq r_{M}\| \gamma(\omega)\|_{L^1}\psi(\| u(\omega)\|) \quad
\text{for all }t\in J.
\end{align*}
Taking supremum over $t$ in the above inequality yields
$$
     R = \| u(\omega)\| \leq r_{M}\| \gamma(\omega)\|_{L^1}\psi(R)
$$
for some $\omega\in \Omega$. This contradicts to condition \eqref{e7}.

Thus, all the conditions of Lemma2.1 are satisfied. Hence the random equation
$$
Q(\omega)x(t)=x(t,\omega)
$$
has a random solution in $\bar{\mathcal{B}}_{R}(0)$; i.e.,
 there is a measurable function $\xi:\Omega\to\bar{\mathcal{B}}_{R}(0)$ 
such that $Q(\omega)\xi(t)=\xi(t,\omega)$ for all $t\in J, \omega\in\Omega$. 
As a result, the random \eqref{e1} has a random solution defined on $J$. 
This completes the proof.
\end{proof}

\section{Extremal random solutions}

It is sometimes desirable to know the realistic behavior of random 
solutions of a given dynamical system. Therefore, we prove the 
existence of extremal positive random solution of \eqref{e1} 
defined on $\Omega\times J$.

We introduce an order relation $\leq$ in $C(J,\mathbb{R})$ with the
 help of a cone $K$  defined by
$$
        K=\{x\in C(J,\mathbb{R}): x(t)\geq 0 \text{ on } J\}.
$$
Let $x,y\in X$, then $x\leq y$ if and only if $y-x\in K$. Thus, we have
$$
        x\leq y\; \Leftrightarrow\; x(t)\leq y(t)\text{ for all } t\in J.
$$
It is known that the cone $K$ is normal in $C(J,\mathbb{R})$.
For any function $a,b:\Omega\to C(J,\mathbb{R})$ we define a random 
interval $[a,b]$ in $C(J,\mathbb{R})$ by
\[
    [a,b] = \{x\in C(J,\mathbb{R}): a(\omega)\leq x\leq b(\omega)\,
 \forall \omega\in\Omega\}
          = \cap_{\omega\in\Omega}[a(\omega),b(\omega)].
\]

\begin{definition} \label{def3.1}\rm
 An operator $Q:\Omega\times E\to E$ is called nondecreasing if 
$Q(\omega)x\leq Q(\omega)y$ for all $\omega\in\Omega$, and for all
 $x,y\in E$ for which $x\leq y$.
\end{definition}

We use the following random fixed point theorem of Dhage in what follows.

\begin{lemma}[{Dhage \cite{d1}}] \label{lem3.1}
 Let $(\Omega,\mathcal{A})$ be a measurable space and let $[a,b]$ 
be a random order interval in the separable Banach space $E$. 
Let $Q:\Omega\times[a,b]\to[a,b]$ be a completely continuous and 
nondecreasing random operator. Then $Q$ has a minimal fixed point $x_{*}$ 
and a maximal random fixed point $y^{*}$ in $[a,b]$. 
Moreover, the sequences $\{Q(\omega)x_{n}\}$ with $x_{0}=a$ and 
$\{Q(\omega)y_{n}\}$ with $y_{0}=b$ converge to $x_{*}$ and $y^{*}$ respectively.
\end{lemma}

We need the following definitions in the sequel.

\begin{definition} \label{def3.2}\rm 
A measurable function $\alpha:\Omega\to C(J,\mathbb{R})$ is called a 
lower random solution of \eqref{e1} if
\begin{gather*}
 \alpha ^{(4)}(t,\omega)\leq f(t,\alpha(t,\omega),\alpha(t,\omega),\omega)
\quad\text{a.e. } t \in J.\\
 \alpha^{(i)}(0,\omega)= \alpha^{(i)}(1,\omega), \quad   i=0,1,2.\\
  \alpha^{(3)}(0,\omega)\leq \alpha^{(3)}(1,\omega)
\end{gather*}
for all $\omega\in\Omega$. Similarly, a measurable function 
$\beta:\Omega\to C(J,\mathbb{R})$ is called an upper random solution of
 \eqref{e1} if
\begin{gather*}
\beta^{(4)}(t,\omega)\geq f(t,\alpha(t,\omega),\alpha(t,\omega),\omega)
\quad\text{a.e. } t \in J.\\
\beta^{(i)}(0,\omega)= \beta^{(i)}(1,\omega), \quad i=0,1,2.\\
\beta^{(3)}(0,\omega)\geq \beta^{(3)}(1,\omega)
\end{gather*}
for all $t\in J$ and $ \omega\in\Omega$.
\end{definition}

\begin{definition} \label{def3.3}\rm
A random solution $\theta$ of \eqref{e1} is called maximal
 if for all random solutions of  \eqref{e1}, one 
has $x(t,\omega)\leq \theta(t,\omega)$ for all $t\in J$ and 
$\omega\in\Omega$. 

A minimal random solution of \eqref{e1} on $J$ is defined
similarly, 
\end{definition}


We consider the following set of assumptions:
\begin{itemize}
\item[(H3)] Problem \eqref{e1} has a lower random solution
 $\alpha$ and upper random solution $\beta$ with $\alpha\leq\beta$ on $J$.

\item[(H4)] For any $u_2,u_1\in[\alpha,\beta]$ and $u_2>u_1$
 $$
 f(t,u_2,v,\omega)-f(t,u_1,v,\omega)\geq -M(u_1-u_2)
 $$
for a.e. $t\in[0,1]$ and $\omega\in\Omega$.

\item[(H5)] The function $q:J\times\Omega\to\mathbb{R}_{+}$ defined by
$$
q(t,\omega)=| f(t,\alpha(t,\omega),\alpha''(t,\omega),\omega)
+M\alpha(t,\omega)|+| f(t,\beta(t,\omega),\beta''(t,\omega),\omega)
+M\beta(t,\omega)|
$$
is Lebesgue integrable in $t$ for all $\omega\in\Omega$.
\end{itemize}

Hypotheses (H3) holds, in particular, when there exist measurable functions 
$u,v:\Omega\to C(J,\mathbb{R})$ such that for each $\omega\in\Omega$,
$$
    u(t,\omega)\leq f(t,x,y,\omega)+Mx\leq v(t,\omega)
$$
for all $t\in J$ and $x\in \mathbb{R}$. 
In this case, the lower and upper random solutions of \eqref{e1} are given by
$$
     \alpha(t,\omega)=\int_{0}^1G(t,s)u(s,\omega)ds
$$
and
$$
     \beta(t,\omega)=\int_{0}^1G(t,s)v(s,\omega)ds
$$
respectively. The details about the lower and upper random solutions 
for different types of random differential equations could be 
found in \cite{l1}. 
Hypotheses  (H4) is natural and used in several research papers. 
 Finally, if  $f$ is $L^1$-Carath\'{e}odory on
 $\mathbb{R}\times\Omega$, then (H5) remains valid.

\begin{theorem} \label{thm3.1}
 Assume that {\rm (H), (H3)--(H5)} hold, then  \eqref{e1} has a minimal 
random solution $x_{*}(\omega)$ and a maximal random solution 
$y^{*}(\omega)$ defined on $J$. Moreover,
\[
x_{*}(t,\omega)=\lim_{n\to\infty}x_{n}(t,\omega) ,\quad
y^{*}(t,\omega)=\lim_{n\to\infty}y_{n}(t,\omega)
\]
for all $t\in J$ and $\omega\in\Omega$, where the random 
sequences $\{x_{n}(\omega)\}$ and $\{y_{n}(\omega)\}$ are given by
\[
 x_{n+1}(t,\omega) = \int_{0}^1G(t,s)(f(s,x_{n}(s,\omega),x_{n}''(s,\omega)
,\omega)+Mx_{n}(s,\omega))ds\]
for $n\geq 0$  with $x_{0}=\alpha$, and
\[
 y_{n+1}(t,\omega) = \int_{0}^1G(t,s)(f(s,y_{n}(s,\omega),y_{n}''(s,\omega),
\omega)+My_{n}(s,\omega))ds
\]
for $n\geq 0$ with $y_{0}=\beta$,
for all $t\in J$ and $\omega\in\Omega$.
\end{theorem}

\begin{proof} We Set $E=C(J,\mathbb{R})$ and define an operator 
$Q:\Omega\times[\alpha,\beta]\to E$ by \eqref{e8}. 
We show that $Q$ satisfies all the conditions of Lemma3.1 
on $[\alpha,\beta]$.

It can be shown as in the proof of Theorem 2.1 that $Q$ is a 
random operator on $\Omega\times[\alpha,\beta]$. 
We show that it is nondecreasing random operator on $[\alpha,\beta]$.
Let $x,y:\Omega\to[\alpha,\beta]$ be arbitrary such that 
$x\leq y$ on $\Omega$. Then
\begin{align*}
&Q(\omega)y(t)-Q(\omega)x(t)\\
&=\int_{0}^1 G(t,s)\Big[\big(f(s,y(s,\omega),y''(s,\omega),\omega)
-f(s,x(s,\omega),x''(s,\omega),\omega)\big)\\
& \quad  +M(y(s,\omega)-x(s,\omega))\Big]ds\\
&\geq \int_{0}^1G(t,s)[(-M(y(s,\omega)-x(s,\omega))
 +M(y(s,\omega)-x(s,\omega)]ds=0
\end{align*}
for all $t\in J$ and $\omega\in\Omega$. As a result, 
$Q(\omega)x\leq Q(\omega)y$ for all $\omega\in\Omega$ and that $Q$ 
is nondecreasing random operator on $[\alpha,\beta]$.

Now, by (H4),
\begin{align*}
    \alpha(t,\omega) 
&\leq Q(\omega)\alpha(t)\\
&= \int_{0}^1G(t,s)[f(\alpha(s,\alpha'(s,\omega),
 \alpha''(s,\omega),\omega),\omega)+M\alpha(s,\omega)]ds\\
&\leq \int_{0}^1G(t,s)f(s,x'(s,\omega),x''(s,\omega),\omega)+Mx(s,\omega)ds\\
&= Q(\omega)x(t)\\
&\leq Q(\omega)\beta(t)\\
&= \int_{0}^1G(t,s)[f(\beta(s,\beta'(s,\omega),\beta''(s,\omega),\omega),\omega)
 +M\beta(s,\omega)]ds\\
&\leq \beta(t,\omega)
\end{align*}
for all $t\in J$ and $\omega\in\Omega$. As a result $Q$ defines a random 
operator $Q:\Omega\times[\alpha,\beta]\to[\alpha,\beta]$.

Then, since (H5) holds, we replace $\gamma(t,\omega)$ and $\psi(r)$
 with $\gamma(t,\omega)=q(t,\omega)$ for all $(t,\omega)\in J\times\Omega$ 
and $\psi(R)=1$ for all real number $R\geq 0$. 
Now it can be show as in the proof of Theorem 2.1 that the random 
operator $Q(\omega)$ satisfies all the conditions of Lemma 3.1 and 
so the random operator equation $Q(\omega)x=x(\omega)$ has a 
least and a greatest random solution in $[\alpha,\beta]$. Consequently, 
\eqref{e1} has a minimal and a maximal random solution defined on $J$. 
The proof is complete. 
\end{proof}


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\end{document}

