1. Introduction and Preliminaries
In recent years, the interpolation theory for nonlinear operators between Banach spaces has seen significant progress. Although it has been emphasised, a similar development of interpolation theorems for specific kinds of nonlinear operators is far less widely known. In this continuation, the idea of accretive mapping is extremely significant because it enables the treatment of a large number of functional differential equations and partial differential equations, e.g., heat and wave equations from mathematical physics, (see [
1,
2,
3,
4,
5]). The development in the theory of accretive mappings has been shown to be quite useful in the theory of variational inequalities and variational inclusion.
Variational inclusion theory includes a multitude of new ideas and approaches that may be considered as a novel extension and generalization of a variational inequality. It is outstanding that a wide range of unrelated problems can be studied in the cohesive structure of variational inclusions. An efficient and workable iterative technique is developed through the investigation of variational inclusions. To determine the solutions for variational inclusions, a variety of iterative techniques have been proposed and debated. Researchers frequently employ the proximal approach, one of the most intriguing and significant tools, to resolve variational inclusions. Detailed research results can be found in the relevant references [
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33].
In 2014, Sahu et al. [
6] introduced a class of nonlinear implicit variational inclusions with
A-monotone mapping and discussed its existence of solutions in semi-inner product spaces. In 2017, Bhat and Zahoor [
7] introduced a new system of variational inclusions with
-
-monotone mapping and discussed its approximate solution in the semi-inner product spaces. Their outcomes are an extension and improvement of the results of Sahu et al. [
34]. Moreover, they developed the iterative methods by using the resolvent operator approaches to discover an approximate solution to variational inclusion problems.
Recently, Luo and Huang [
35] introduced
-
-monotone mappings in Banach spaces, which provided a cohesive framework for the various classes of monotone (accretive) operators. As applications, they solved the various classes of variational inclusions and showed the convergence of iterative schemes involving proximal mappings (resolvent operators). See the references for further applications [
6,
7,
8,
13,
14,
17,
20,
21,
22,
23,
29,
31,
32,
33,
35].
This work provides further insight into existing research. This research aims to develop a new class of accretive mappings known as generalized
-
-accretive mappings and investigates its associated class of proximal mappings. This class of accretive mappings is a representation of an addition of two
-symmetric mappings. It can be viewed as an extension of the class of accretive mappings, which are the generalized
-
-accretive mapping [
36,
37,
38] and generalized
-accretive mapping [
8]. Some characteristics of the proximal mapping related to generalized
-
-accretive mappings are studied.
Application of the proximal mapping linked with the generalized
-
-accretive mapping leads to set-valued variational-like inclusions (SVVLI, in short) in the semi-inner product spaces. Further, the equivalent fixed point problem for SVVLI is given. With the help of this alternative problem, we provide an iterative scheme for solving SVVLI. Furthermore, we study the convergence analysis of the suggested iterative method. An illustration is built in support of our result. For detailed studies, see the related references [
8,
10,
11,
15,
16,
20,
22,
36].
Before giving necessary definitions for the presentation of this research work, we provide the following well-known definitions and results.
Definition 1 ([
6,
39])
. Let be a vector space over the field of real or complex numbers. A functional is called a semi-inner product if:- (i)
- (ii)
- (iii)
- (iv)
.
Then, the pair is known as a semi-inner product space.
Since
is a norm on vector space
, each semi-inner product space becomes a normed linear space. A semi-inner product in a normed linear space can be generated in infinitely many ways. Giles [
40] proved that the semi-inner product can be obtained uniquely if the considered space
becomes a uniform convex smooth Banach space. A comprehensive analysis and key findings on semi-inner product spaces may be found in [
39,
40,
41].
Example 1 ([
6,
40]).
Let , where is a real Banach space. Then, is a semi-inner product space whose semi-inner product is given by Definition 2 ([
6,
42])
. Let be a real Banach space.- (i)
Then, the modulus of smoothness of Banach space is a function , given as - (ii)
If , then is called uniformly smooth;
- (iii)
If there exists non-negative constant c as then is called q-uniformly smooth;
- (iv)
If there exists non-negative constant c as , then is called 2-uniformly smooth.
Lemma 1 ([
6,
42])
. Let be a real number and be a smooth Banach space. Then, the following statements are equivalent:- (i)
is 2-uniformly smooth;
- (ii)
There is a non-negative constant c such that for each , the following inequality holds:
where and is the normalized duality mapping. Each normed linear space
is a semi-inner product space (see [
39]). In fact, by the Hahn–Banach theorem, for each
, there exists at least one functional
such that
.
Given any such mapping
, we can verify that
defines a semi-inner product. Consequently, we may express the inequality (
1) as
where the constant
c is taken as the best minimum value and known as the smoothness constant.
Example 2 ([
6]).
The functional spaces is 2-uniformly smooth for and is -uniformly smooth for . If , then we have for all :where is the smoothness constant. It is important to remember the fact that the function space , where , is a uniformly convex smooth Banach space, which allows us to provide a unique semi-inner product on the space.
Elsewhere in the paper, unless otherwise indicated, we consider that is a 2-uniformly smooth Banach space and .
We remind some prerequisites which will be used throughout this paper.
Definition 3. Let and be single-valued mappings. Then, is called
- (i)
- (ii)
μ-strongly accretive if there exists as - (iii)
γ-relaxed accretive if there exists as - (iv)
- (v)
-strongly accretive if there exists as - (vi)
-relaxed accretive if there exists as - (vii)
λ-Lipschitz continuous if there exists as
Lemma 2 ([
9]).
Let and be non-negative real sequences, satisfying with and . Then, as . Definition 4. For every , let , and be the single-valued mappings. Then, is called
- (i)
-strongly accretive with if there exists as - (ii)
-relaxed accretive with if there exists as - (iii)
-Lipschitz continuous with if there exists as - (iv)
-symmetric accretive with iff for , is -strongly accretive with and for , is -relaxed accretive with , when k is even, satisfyingand iff
- (v)
-symmetric accretive with iff for , is -strongly accretive with and for , is -relaxed accretive with when k is odd, satisfyingand iff
Definition 5 ([
7]).
Let be a mapping and be the set-valued mappings, then:- (i)
- (ii)
- (iii)
- (iv)
Inverse of is given as: - (v)
Set , and for any real number β are given as:
Definition 6. For every , let be single-valued mappings and be a set-valued mapping. Then, is called
- (i)
-strongly accretive with if there exists as - (ii)
-relaxed accretive with if there exists as - (iii)
-symmetric accretive with iff for , is -strongly accretive with and for , is -relaxed accretive with , when k is even, satisfying
and
- (iv)
-symmetric accretive with iff for , is -strongly accretive with and for , is -relaxed accretive with , when k is odd, satisfying
and
iff
Definition 7. A single-valued mapping is called -Lipschitz continuous in the -component if there exists as 2. Generalized --Accretive Mappings
For every , let be a set-valued mapping and , and be single-valued mappings. Now, we present and study the following new class of accretive mappings.
Definition 8. Let , then is called generalized -η-accretive mapping with mappings and
- (i)
Iff is -symmetric accretive with and if k is even;
- (ii)
Iff is -symmetric accretive with and if k is odd.
Remark 1. (i) Let and , where .
Then, Definition 8 coincides with the definition of the generalized -accretive mapping considered by Gupta and Khan [36,37,38]. - (ii)
In addition to the above case (i), let and .
Then, Definition 8 coincides with the definition of the generalized -accretive mapping considered by Kazmi et al. [8]. - (iii)
In addition to the above case (ii), let
Then, Definition 8 coincides with the definition of -accretive considered by Zou and Huang [10]. - (iv)
In addition to the above case (iii) except .
Then, Definition 8 coincides with the definition of the --accretive mapping considered by Zou and Huang [43]. - (v)
In addition to the above case (iv) except .
Then, Definition 8 coincides with the definition of the generalized -accretive mapping considered by Ahmad and Dilshad and Mishra and Diwan [11,12]. - (vi)
In addition to the case (i) excluding and , let , .
Then, Definition 8 coincides with the definition of the -η-accretive mapping considered by Bhat and Zahoor [7] and Lou and Huang [35]. - (vii)
Let , and .
Then, Definition 8 coincides with the definition of the -accretive mapping considered in [13,14]. Thus, the class of -η-accretive mapping in Banach spaces is given a unifying framework for the various classes of accretive mappings (monotone operators). For details, see [6,18,19,20,21,22,23,29,31,32,33]. Now, we are illustrating an example to show that is an --accretive mapping with and .
Example 3. Let and with the usual semi-inner product Let mapping for each be defined as Assume that mapping is defined by Let for any , Thus, is -strongly accretive with . Similarly, we can check for each .
Let for any , Thus, is -relaxed accretive with . Similarly, we can check for each .
Assume that the mapping for each is given as Let set-valued mapping be defined asLet for any : Thus, is -strongly accretive with . Similarly, we can check for each .
Let for any : Thus,
is
-accretive with
. Similarly, we can check for each
:
It is easy to show that the whole
is generated by the right-hand side of (
3).
To discuss various aspects of generalized --accretive mappings and move on to the subsequent sections, let us take into account the following assumptions –.
If k is even:
: Mapping is -symmetric accretive with .
: Mapping is -symmetric accretive with .
If k is odd:
: Mapping is -symmetric accretive with .
: Mapping is (-symmetric accretive with .
: Let be ℏ-Lipschitz continuous.
Theorem 1. If assumptions – are true for , , and is a generalized -η-accretive mapping with mappings and , then is single-valued.
Proof. For any given
, let
. It follows that
If k is even: Since
is
-symmetric accretive with
and
is
-symmetric accretive with
, we obtain:
Since , , we have . It implies that . Thus, is single-valued. Similarly, if k is odd, we can demonstrate the outcome. □
Next, we use the Theorem 1 to define the following proximal mapping .
Definition 9. If assumptions – are true for , , and is a generalized -η-accretive mapping with mappings and , then a proximal mapping is defined as Now, we discuss the Lipschitz continuity.
Theorem 2. If assumptions – are true for , , and is a generalized -η-accretive mapping with mappings and , then, the proximal mapping is -Lipschitz continuous, whereand Proof. Let
and from (
5), we have
It follows that
Let and
If k is even: Since
is
-symmetric accretive with
, we have
Using the fact that
is
-symmetric accretive with
and
is
ℏ Lipschitz continuous in the above inequality, we have
or
That is,
If k is odd: Similarly, we can demonstrate that
is
-Lipschitz continuous, where
□
3. An Application
For every , let , , and be single-valued mappings, be set-valued mappings. Let set-valued mapping be a generalized --accretive mapping with mappings and .
We study the set-valued variational-like inclusions problem (SVVLIP, in short): for any
find
such that
SVVLIP (
6) coincides with the following general variational inclusion (GVIP): find
such that
when
,
,
,
,
,
for each
.
GVIP (
7) was studied by Zou and Huang [
10] if
M is a
-accretive mapping in Banach spaces.
In addition to the above case, let
be a Hilbert space
X and
is a
H-monotone mapping, then GVIP (
7) was studied by Fang and Huang in [
15]. GVIP (
7) contains complementarity problems and some variational inclusions (inequalities) as special cases; see the references [
44,
45].
Note: For a given appropriate selection of
,
, and the spaces
, the SGVLIP (
6) coincides with different classes of variational inclusions and variational inequalities. See the relevant references [
13,
16,
36].
Definition 10. A set-valued mapping
is called
-
Lipschitz continuous with
, if
Lemma 3. Let be a mapping with and , where . For any , where , is a solution of SVVLIP (6) iff satisfies:where . Proof. The proof of the above lemma is a direct consequence of the generalized --accretive mapping; therefore, the proof is omitted. □
In order to obtain an approximate solution to the SVVLIP (
6), we now propose the iterative scheme based on Lemma 3.
Here, we provide sufficient convergence criteria for iterative sequences developed by Algorithm 1.
Algorithm 1 |
For any given , select and obtain , , ,..., , by the following iterative scheme:
and is the Hausdorff metric on .
|
Theorem 3. For every , , let , , be single-valued mappings, be a -Lipschitz continuous with and be a δ-relaxed accretive and -Lipschitz continuous mapping. Let be a -Lipschitz continuous, and for every , be --Lipschitz continuous. Let be a mapping with and , where such that is -Lipschitz continuous in the -component. The set-valued mapping is a generalized -η-accretive mapping with mappings and . In addition, the following conditions are satisfied:Then, iterative sequences constructed from Algorithm 1 converge strongly to , a solution of SVVLIP (6). Proof. We now argue that
strongly converges to
t. From Theorem 2 and Algorithm 1, we have
As
is
-Lipschitz continuous with
, we have
Using the
-Lipschitz continuity of
and
-
-Lipschitz continuity of
, we have
We compute the following by using the
-Lipschitz continuity of
:
Using the
-relaxed accretivity, the
Lipschitz continuity of
p, and Lemma 1, we have
Using (
11)–(
15) in (
10), we obtain
where
We can obtain
as
, where
It follows from (
9) that
. Thus,
is a Cauchy sequence. Then,
exists in such a way that
as
. Next, we show that
. From Algorithm 1 and the Lipschitz continuity of
, we have
It shows that
is a Cauchy sequence. Similarly, we can prove that
are Cauchy sequences. Then, there exist
such that
as
. Now, we argue that
. Since
, we have
Since
is closed, thus
. Through the same procedure, we can show that
. By the continuity of
,
and Algorithm 1, it follows that
satisfies:
By Lemma 3, SVVLIP (
6) has a solution
. □
Remark 2. (i) Theorem 3 coincides with Theorem 4.1 in [10] if , , , , for each , for each each .
- (ii)
In addition to the above case, let is a H-monotone mapping, and be a Hilbert space X. Then, Theorem 3 coincides with Theorem 3.1 in [15].
The functional space is a 2-uniformly smooth space when is as given in Example 2. Let , where . Then, Theorem 3 yields the following outcome:
Corollary 1. For every , , let , , be single-valued mappings, be a -Lipschitz continuous with and be a δ-relaxed accretive and -Lipschitz continuous mapping. Let be a -Lipschitz continuous, and for every , be --Lipschitz continuous. Let be a mapping with and , where such that is -Lipschitz continuous in the -component. The set-valued mapping is a generalized -η-accretive mapping with mappings and . In addition, the following conditions are satisfied:where is the smoothness constant. Then, iterative sequences constructed from Algorithm 1 converge strongly to , a solution of SVVLIP (6).