1. Introduction
In the process of mathematical modeling for solving problems, the initial data or parameter values are often uncertain due to measurement error. People often express these data and parameters as an interval number or fuzzy number. 1979, Markov proposed the interval-valued calculus [
1]. This paper remained essentially un-cited for more than 30 years and was “rediscovered” after the publication of [
2,
3,
4]. Stefanini considered a generalization of the Hukuhara difference and division for interval arithmetic and generalized Hukuhara differentiability of interval-valued functions and interval differential equations.
Recently, the interest for this topic increased significantly, in particular after the implementation of specific tools and classes in the C++ and Julia (among others) programming languages, or in computational systems, such as MATLAB or Mathematica [
5]. The research activity in the calculus for interval-valued or set-valued functions is now very extended, particularly in connection with the more general calculus for fuzzy-valued functions with applications to almost all fields of applied mathematics [
6,
7,
8].
Interval-valued differential equations are introduced as a good tool to study non-probabilistic uncertainty in real world phenomena. 2009, Stefanini and Bede studied several kinds of derivatives of an interval-valued function, and provided some properties of solutions to interval-valued differential equations under the gH-derivative [
4]. 2011, Chalco-Cano et al. revisited the expression of the gH-derivative of an interval-valued function in terms of the endpoints functions [
9]. In 2013, Lupulescu discussed the gH-differentiability of interval-valued functions, and studied interval differential equations on time-scales [
10]. In 2017, by using a Krasnoselskii–Krein-type condition, Hoa, Lupulescu and O’Regan studied the existence and uniqueness of the solutions to initial value problems of fractional interval-valued differential equations [
11].
In 2018, by applying the monotone iterative technique, Hoa considered the extremal solutions to initial value problems of fractional interval-valued integro-differential equations [
12]. These studies expanded the scope of the research on interval-valued differential equations.
It is well known that the upper and lower solution method is a powerful tool for the solvability of differential equation [
13]. Rodríguez-López applied the upper and lower solution method to develop a monotone iterative technique to approximate extremal solutions for the initial value problem relative to a fuzzy differential equation in a fuzzy functional interval [
14]. Motivated by this idea, in order to solve the nonlinear interval boundary value problem
where
we propose an upper and lower solution method and obtain at least four solutions similar to linear fuzzy boundary value problems.
In what follows, we introduce some preliminaries, in
Section 3, we study a class of linear interval boundary value problems and give conditions that ensure that linear interval boundary value problems have solutions, and, in
Section 4, we propose an upper and lower solution method for a class of nonlinear interval boundary value problems. In the last section, we give a example to illustrate the effectiveness of the results in this paper.
2. Preliminaries
In this section, we introduce some preliminaries that can be found in [
7].
We denote by
the family of all bounded closed intervals in
i.e.,
The well-known midpoint-radius representation is very useful: for
and we define the midpoints
and
respectively, by
so that
and
We will denote the interval by
or, in midpoint notation, by
thus,
The gH-difference of two intervals always exists and, in midpoint notation, is given by
the gH-addition for intervals is defined by
Endowed with the Pompeiu–Hausdorff distance
defined by
with
and given also as
(here, for
the metric space
is complete.
Definition 1. ([7]) Given two intervals and and ), we define the following order relation, denoted The space
is a lattice. The reverse order is defined by
i.e.,
An interval-valued function is defined to be any
with
and
for all
In midpoint representation, we write
where
is the midpoint value of interval
and
is the nonnegative half-length of
so that
Limits and continuity can be characterized, in the Pompeiu–Hausdorff metric
for intervals, by the gH-difference. For a function
an interval
and an accumulation point
we have
where the limits are in the metric
If, in addition,
we have
In midpoint notation, let
and
then, the limits and continuity can be expressed, respectively, as
and
Let be the set of all continuous interval-value functions.
Theorem 1. Let and Then, there exists an interval such that Proof. Let
Since
we have
It follows that
when
when
Hence, there exist
and
such that
Let
It is clear that
□
Theorem 2. Let be interval-value functions. Then, Proof. It is similar to prove that
□
Definition 2. Given two interval-value functions and , we define the distance of and as Theorem 3. Let be interval-value functions and Proof. Let
It follows that
and
are two continuous functions. Similar to the proof of Theorem 1, it is easy obtain that
and
are uniformly bounded. Hence,
□
Definition 3. Let and h be such that and then the gH-derivative of a function at is defined asif the limit exists. The interval is called the generalized Hukuhara derivative of F (gH-derivative for short) at For a gH-differentiable function, higher-order gH-derivatives are defined analogously to the ordinary case using the gH-differences applied to the gH-derivatives of previous order.
Definition 4. Let be gH-differentiable on and and h be such that The second order gH-derivative of at is defined asif the limit exists. The interval is called the second order gH-derivative of F at Remark 1. In the case of an interval-valued function in the form with where and have derivatives for we have that has all the gH-derivatives Let be the set of all i order continuous differentiable interval-value functions,
3. The Linear Interval Boundary Problems
In this section, we consider a class of linear interval boundary problems under the gH-derivative. Let
where
Definition 5. If and satisfies Problem then we say that is a solution of Problem
The following theorems concern the existence of solutions of a two-point boundary value problem of linear interval differential equation under the gH-derivative.
Theorem 4. Let Then, Problem has at least four solutionswhereororor Proof. Let
is a solution of Problem
where
By Definition 4 and Remark 1, Problem
is equivalent to the following problems:
By
and
it is easy to find that
that is to say
By
and
we have
and
If
then
If
then
If
then
If
then
Therefore, Problem
has at least four solutions
where
or
or
or
□
Theorem 5. Let be a solution of Problem and define operator T as Then, operator T is a continuous operator.
Proof. For convenience, assume a solution of Problem (1) is
where
It is clear that operator T is a continuous operator. □
4. The Nonlinear Interval Boundary Value Problems
In what follows, we consider a class of nonlinear interval boundary problems
where
Definition 6. If and satisfy Problem then we say that is a solution of Problem
We present the concept of upper and lower solution of a two-point boundary value problem of nonlinear interval differential equation under the gH-derivative in the following definition.
Definition 7. is said to be an upper solution of Problem if is said to be a lower solution of Problem if is said to be a solution of Problem if is an upper solution and is also a lower solution of Problem
The following theorems concern the existence of solutions of a two-point boundary value problem of a nonlinear interval differential equation under the gH-derivative.
Theorem 6. Let be an upper solution and a lower solution of Problem and If and when then Problem exists at least two solutions.
Proof. Since
is a lower solution of Problem
then
By Theorem
we know that there exists
, which is the solution of the linear interval boundary value problem
Similarly, we also find
i.e.,
By similar reasoning, if
is an upper solution of Problem
and
is a solution of the linear fuzzy boundary value problem
Assume
let
be a solution of the linear interval boundary value problem
Therefore, T is a monotone operator.
Since,
we obtain
and let
we have
A similar argument for
we have
In addition, from
we conclude that
and
By Theorem 1, there exist two interval-value functions
such that
and
By Theorem 3 and Theorem 5, we have
i.e., Problem
exists at least two solutions. □
5. Example
In this section, we will give a example to illustrate the effectiveness of the results.
Example 1. If letwhere It is easy to check that and when if
Clearly, is a lower solution of Problem when
is an upper solution of Problem when
Therefore, in this case, the conclusion of Theorem 6 holds.
Remark 2. is a lower solution of Problem In fact, sincewe have is an upper solution of Problem In fact, sincewe have