
This work focused on the investigation of a generalized variation inclusion problem. The resolvent operator for generalized -co-monotone mapping was structured, the Lipschitz constant was estimated and its relationship with the graph convergence was accomplished. An Ishikawa type iterative algorithm was designed by incorporating the resolvent operator and total asymptotically non-expansive mapping. By employing the novel implication of graph convergence and analyzing the convergence of the considered iterative method, the common solution of the generalized variational inclusion and the set of fixed points of a total asymptotically non-expansive mapping was obtained. Moreover, a generalized resolvent dynamical system was investigated. Some of its attributes were discussed and implemented to examine the considered generalized variation inclusion problem.
Citation: Doaa Filali, Mohammad Dilshad, Mohammad Akram. Generalized variational inclusion: graph convergence and dynamical system approach[J]. AIMS Mathematics, 2024, 9(9): 24525-24545. doi: 10.3934/math.20241194
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This work focused on the investigation of a generalized variation inclusion problem. The resolvent operator for generalized -co-monotone mapping was structured, the Lipschitz constant was estimated and its relationship with the graph convergence was accomplished. An Ishikawa type iterative algorithm was designed by incorporating the resolvent operator and total asymptotically non-expansive mapping. By employing the novel implication of graph convergence and analyzing the convergence of the considered iterative method, the common solution of the generalized variational inclusion and the set of fixed points of a total asymptotically non-expansive mapping was obtained. Moreover, a generalized resolvent dynamical system was investigated. Some of its attributes were discussed and implemented to examine the considered generalized variation inclusion problem.
The theory of variational inequalities (VIs) was initially originated from variational principles for investigating partial differential equations [31]. It is a dynamic tool for unifying and studying equilibrium problems. It has been recognized as a potential and compelling approach for exploring and analyzing nonlinear problems of science and engineering, complex boundary value problems, models of economics, and transportation and operations research by reformatting them as a VI. Since its rise, this theory has been augmented by diverse techniques and methodologies.
Among the succeeding expansions, one of the prominent, most fruitful and worthwhile generalizations of VI is variational inclusion. The variational inclusion problem plays a crucial role in the formulation of mathematical models of various real-life problems with practical implications across diverse disciplines. The monotone inclusion problem (MIP) is to discern an element so that
(1.1) |
where is a real Hilbert space, is a single-valued monotone operator, and is a maximal monotone operator. We indicate the solution set of the MIP (1.1) by . Variational inclusions have been implemented to tackle numerous equilibrium and optimization problems including image processing, image deblurring, convex minimization, DC programming, split feasibility, fixed point and VI problems; see [1,9,12,17,21,23,27,28,29,33]. Applicability and usefulness of variational inclusions have captivated the attentiveness of numerous scholars in a short span of time. As of now, a number of approaches have been carried out for figuring out the problem. One of the fundamental approaches to deal with these problems is to reduce the inclusion problem into an analogous fixed point problem by employing the technique of resolvent.
In recent times, for the sake of generalizing VIs and inclusions, the researchers have generalized the conception of monotone and accretive mappings such as -accretive mappings [20] as an allied approach for maximal monotone, maximal -monotone and -subdifferential mappings. In this sequel, the concept of -monotone mapping was incepted by Fang and Huang [15] in Hilbert spaces, and later they further coined an analogous notion in Banach spaces named -accretive mappings [16]. In 2008, Zou and Huang [35] enriched the literature by defining the -accretive operator in Banach spaces. Using these generalized monotone and accretive mappings, authors have examined numerous variational inclusions by implementing the resolvent operators. Moreover, the notion of the -co-coercive mapping was set forth by Ahmad et al. [3]. This concept was further extended by defining -co-monotone mapping [4], which is the combination of symmetric co-coercive and monotone mapping. An analogous conception was studied in Banach spaces and named as -co-accretive mapping [5], which is the combination of symmetric co-coercive and accretive mapping. The researchers explored some properties of these operators and applied them to investigate a number of variational inclusions. Subsequently, a great deal of work has gone into examining variational inclusion problems involving generalized monotone and accretive mappings using the graph convergence. Li and Huang [22] brought the idea of graph convergence for -accretive mappings and shown that it is homologous to the resolvent operator convergence Further, Ahmad et al. [2] utilized the conception of graph convergence to examine a system of generalized variational inclusions involving -co-accretive mapping. For a detailed literature on graph convergence, we refer to [6,7,10,32].
Since the equilibrium point of the dynamical system leads to the solution of the corresponding VI and inclusion problem, dynamical systems represent cohesive, all-encompassing frameworks of VIs and inclusions as their equilibrium points serve as solutions to these problems. Thus, all the problems whose mathematical models can be solved using VIs can also be examined in the general framework of the dynamical systems. This characteristic has drawn the attention of researchers to study dynamical systems associated with VI and inclusion problems. One can transform the model of VI or inclusion problems into a fixed point problem by implementing the novel resolvent or projection operator, and such transformations allow us to suggest dynamical systems. Dynamical systems directly or indirectly appear in several useful areas encompassing celestial mechanics, environmental studies, financial forecasting, modeling of neuroscience, etc., and allow us to describe the trajectories of physical process and real-world problems before achieving the steady state. For further applications of the dynamical systems, see [13,14,18,24,25,26].
Inspired and persuaded by the above stated work, in this study, we investigate a generalized variation inclusion problem. We define the resolvent operator for generalized -co-monotone mapping and estimate its Lipschitz constant. Further, its relationship with the graph convergence is accomplished. An Ishikawa type iterative algorithm is structured and analyzed to obtain the common solution of the generalized variational inclusion and the set of fixed points of a total asymptotically non-expansive mapping by employing the novel implication of graph convergence. Moreover, we construct a generalized resolvent dynamical system associated to the generalized variational inclusion and discuss some of its attributes. Further, we investigated the considered generalized variation inclusion problem by implementing the generalized resolvent dynamical system. Also, the theoretical results are verified by illustrative examples.
Now onward, is assumed to be a real Hilbert space endued with norm which induces the metric and inner product . The collection of all closed and bounded subsets of is signified as .
Definition 2.1. Let be a single-valued mapping. A mapping is referred to as
(i) -monotone if
(ii) -strongly -monotone if so that
(iii) -Lipschitz continuous if so that
(iv) -expansive if so that
The following lemma is a crucial instrument for carrying out the adopted scheme.
Lemma 2.1. [34] Let be a nonnegative real sequence and be a real sequence in [0, 1] with fulfilling the following inequality:
where and . Then .
Definition 2.2. Let and be the single-valued mappings. Then is known as
(i) -mixed Lipschitz continuous with respect to and if such that
(ii) -co-coercive with respect to if such that
(iii) relaxed -co-coercive with respect to if such that
(iv) symmetric -co-coercive with respect to and if satisfies (ii) and (iii).
Definition 2.3. Let ; be the single-valued mappings and be a set-valued mapping. Then, is known as mixed -strongly monotone with respect to and , if for some , such that
Definition 2.4. Let and be the single-valued mappings. A set-valued mapping is known as
(i) -strongly -monotone with respect to if so that
(ii) -relaxed -monotone with respect to if so that
(iii) is known as symmetric -monotone with respect to and if satisfies (i) and (ii).
Definition 2.5. Let and be the single-valued mappings. A set-valued mapping is referred to as generalized -co-monotone if is symmetric -co-coercive with respect to and , is symmetric -monotone with respect to and , and
(2.1) |
Note 2.1. Now onward, is generalized -co-monotone means, is -symmetric co-coercive with respect to and with constants and , respectively, and is symmetric -monotone with respect to and with constants and , respectively, and satisfies (2.1).
Lemma 2.2. Let and be the single-valued mappings. Let be a generalized -co-monotone mapping. Let be -expansive and be -Lipschitz continuous. Then, for all , the mapping is single-valued.
Definition 2.6. Let and be the single-valued mappings. Let be a generalized -co-monotone mapping. The resolvent is described as
(2.2) |
Proposition 2.1. Let be a -Lipschitz continuous mapping; and be the single-valued mappings such that is -expansive and is -Lipschitz continuous. Let be a generalized -co-monotone mapping. Then, is -Lipschitz continuous, where
Proof. For given , it follows from (2.2) that
(2.3) |
(2.4) |
From (2.3) and (2.4), one can write
(2.5) |
(2.6) |
For the sake of simplicity, we indicate and , and since is symmetric -monotone, then
Invoking symmetric -co-coercivity of , -expansiveness of , and -Lipschitz continuities of and , respectively, we attain i.e.,
Thus, for all , we obtain , i.e.,
(2.7) |
where, .
Definition 2.7. The graph of a multivalued mapping is expressed as
Definition 2.8. Let and be the single-valued mappings. For , let be generalized -co-monotone mappings. Then, is known as graph convergent to , indicated by if for each , so that
Theorem 2.1. Let and be the single-valued mappings such that is -mixed Lipschitz continuous with respect to and , and are continuous mappings so that is -expansive. For , let be generalized -co-monotone mappings. Then,
Proof. For all and , suppose that Assume that , then
(2.8) |
Letting
(2.9) |
which turns into
(2.10) |
For each , take , then (2.10) yields
(2.11) |
Invoking the -mixed Lipschitz continuity of , it follows from (2.11) that
(2.12) |
Thus, . Recalling the hypothesis , it yields from (2.8) and (2.9) that and, hence, from (2.12), we acquire as . Accounting the continuity of and , we deduce and , and so .
On the contrary, assume that and choose an arbitrary but fixed . Since is a generalized -co-monotone mapping, . Then, there exists such that . Since and suppose ,
Letting , for all , adducing the -mixed Lipschitz continuity and making use of (2.7), we acquire
(2.13) |
The -expansiveness of yields
(2.14) |
Thus, we deduce from (2.14) and the Definition 2.8 that and as . Thus, from (2.13), we infer that .
Example 2.1 Let with the usual inner product on , i.e.,
Define and by
Then, for any fixed , we find
Thus, is -co-coercive with respect to and relaxed -co-coercive with respect to , hence is symmetric -co-coercive. Next, we estimate the symmetric monotonicity of . Define and by
Then for any fixed , we find
i.e., is -monotone with respect to and relaxed -monotone with respect to , hence is symmetric -monotone. Also, for any and ,
i.e., . Thus, is a generalized -co-monotone mapping. Further, we show that . Let
and . One can observe that
and .
Thus, we acquire that and and . Hence, . Finally, it remains to manifest that Now, for , the associated resolvent operators are estimated as:
and
which yields
Thus, we obtain
In this section, we employ a generalized -co-monotone mapping for investigating a general variational inclusion (GVIP). We examine the problem of discerning so that
(3.1) |
where and are single-valued and multivalued mappings, respectively. We signify the Problem (3.1) as GVIP and its solution set by .
Lemma 3.1. Let and be the single-valued mappings and a multivalued mapping. Let be a generalized -co-monotone mapping. Then, , where solves GVIP (3.1) if, and only if,
(3.2) |
Proof. One can obtain the conclusion immediately by implementing (2.2).
A mapping is referred to as non-expansive (NM) if . In [19], the authors defined a generalized NM referred to as asymptotically nonexpansive (ANM) which properly includes the class of NM.
Definition 3.1. [19] A mapping is known as ANM if is a sequence with and ,
In an attempt to obtain extension of NM and ANM, Sahu [30] introduced nearly asymptotically non-expansive mapping (NANM). The class of NANM is an intermediate class which contains the class of ANM and is contained in the class of mappings of asymptotically non-expansive type.
Definition 3.2. A mapping is known as NANM, if and with , ,
Further, Alber et al. [8] made an attempt to unify some classes of generalized NMs by introducing total asymptotically non-expansive mapping (TANM).
Definition 3.3. A mapping is known as TANM if nonnegative sequences of real numbers with and a strictly increasing continuous function such that and ,
Let be a TANM and presume that the mappings , and are identical as in Lemma 3.1. Suppose that , then from (3.2), one can achieve the following formulation:
(3.3) |
where and . By the virtue of formulation (3.3), we design the following Ishikawa type resolvent iterative scheme to explore a common element of and . Here, indicates the set of fixed points of TANM and indicates the solution set of GVIP (3.1).
Algorithm 3.1. Let and be the single-valued mappings. Let be a multivalued mapping; be generalized -co-monotone mappings, and be a TANM. For initial points , estimate the sequences by the following procedure:
(3.4) |
(3.5) |
for , , , and .
Theorem 3.1. Let be a -Lipschitz continuous mapping; and be the single-valued mappings such that is -mixed Lipschitz continuous with respect to and and -mixed strongly monotone with respect to and , is -Lipschitz continuous, is -Lipschitz continuous with constant , is -expansive, and is -Lipschitz continuous. Let be generalized -co-monotone mappings. Let be a -TANM so that . If obeys the following relation:
(3.6) |
(i) Then is singleton.
(ii) If , then the sequence induced by (3.4)-(3.5) converges strongly to .
Proof. Define as
(3.7) |
By making use of Proposition 2.1 and (3.7), for all , we acquire
(3.8) |
Utilizing the -mixed Lipschitz continuity and -mixed strong monotonicity of and Lipschitz continuities of and , we acquire
(3.9) |
After simplification, the above inequality turns into
(3.10) |
Thus, (3.10) and (3.8) yield
(3.11) |
where and . Taking the premise (3.6) into consideration, we see that . Thus, being a contraction mapping owns a unique fixed point, i.e., a unique so that . Consequently, Lemma 3.1 guarantees that is singleton.
By the assumption that and in , we confirmed that is singleton. Suppose that , then we deduce that and consequently, by (3.3), one can express
(3.12) |
Utilizing the Proposition 2.1, we get
(3.13) |
where . Utilizing the Lipschtz continuities of and , we acquire
(3.14) |
Also, utilizing -mixed Lipschitz continuity of regarding and , -mixed strong monotonicity with respect to and and combining (3.14), we acquire
which yields
(3.15) |
After substituting (3.15) into (3.13), we obtain
(3.16) |
where . Now, recalling that is -total asymptotically non-expansive and applying (3.4) and (3.12), we get
(3.17) |
By substituting (3.16) in (3.17), we acquire
(3.18) |
Following the same steps and employing the same facts as in (3.17), it follows from (3.5) and (3.12) that
(3.19) |
By the hypothesis , we obtain , thus from (3.18) and (3.19), we deduce that
(3.20) |
(3.21) |
Substituting (3.21) into (3.20), we acquire
(3.22) |
where and . For each setting and . Clearly, because of . In fact, as yields . Thus, we deduce from Lemma 2.1 that and, hence, .
Example 3.1. Let with inner product and norm . Define . Then, clearly for all , and we express
Thus, is non-expansive, hence is TANM with and . Define the mappings and by
It can be easily observed that , and are Lipschitz continuous with constants , and , respectively, and is -expansive. Also,
i.e., is -mixed Lipschitz continuous, -mixed strongly monotone, and symmetric -co-coercive with respect to and with constants and , respectively. Define and by Then, is -Lipschitz continuous and
i.e., is symmetric -monotone with respect to and with constants and , respectively. Thus, is a generalized -co-monotone mapping. Also, and the estimated constants satisfy (3.6), that is, . Therefore, is a unique fixed point of . Thus, we have . Next, we compute the sequence by employing Algorithm 3.1. Let and . Then
For different initial points: and , the sequence and and the convergence behavior of is shown in Figure 1.
Example 3.2. Let with inner product and norm . Define . Then, clearly is TANM with and and . Define the mappings and by
Then , and are Lipschitz continuous with constants and , respectively, and is -expansive. Also, is -mixed Lipschitz continuous, -mixed strongly monotone, and symmetric -co-coercive with respect to and with constants and , respectively. Define and by Then, is -Lipschitz continuous and is symmetric -monotone with respect to and with constants and , respectively. Thus, is a generalized -co-monotone mapping. Also, for , the estimated constants satisfy (3.6), that is, and Therefore, is a unique fixed point of . Thus, we have . Now for and , we compute the sequence by employing Algorithm 3.1 as under:
For different initial points: and , the sequence and and the convergence is shown by the graph (Figure 1) below.
Herein, we employ the technique of the dynamical system to explore the solution of GVIP (3.1). By utilizing Lemma 3.1, the generalized resolvent dynamical system (GRDS) that we examine is as under:
(4.1) |
where , and is a parameter.
Definition 4.1. [24] It is stated that the GRDS (4.1) converges to the solution set of GVIP (3.1) if the trajectory of the dynamical system, irrespective of the initial point, satisfies
where
If is a unique point of , then
Definition 4.2. [25] The dynamical system is referred to as globally exponentially stable with degree at if the trajectory of the dynamical system, irrespective of the initial point, satisfies
where positive constants and do not depend on the initial point.
Lemma 4.1. [26] Let and be real-valued nonnegative continuous functions with domain and let where is a monotonic increasing function. If for all ,
then
Next, by utilizing Lemma 4.1 and Theorem 3.1, we investigate the unique solution of GRDS (4.1).
Theorem 4.1. Assume that the Theorem 3.1 holds. Then, for each with , there exists a unique continuous solution with of GRDS (4.1) over .
Proof. Define
Invoking the arguments as for (3.8), we obtain
(4.2) |
Invoking the arguments as employed to (3.9), we obtain
(4.3) |
(4.2) and (4.3) together yields
(4.4) |
which proves that is locally Lipschitz continuous in . Thus, for each a unique continuous solution of GRDS (4.1) with in the interval . Let the maximal interval of its existence be . Next, we substantiate that . Now, for any , we have
(4.5) |
Employing the integral on (4.5) over and utilizing Lemma 4.1, we get
(4.6) |
where and . Hence the solution is bounded on , so
In the next theorem, we shall examine GVIP (3.1) by the convergence of the trajectory of the solution of considered GRDS (4.1).
Theorem 4.2. Assume Theorem 3.1 is true. Then, GRDS (4.1) converges globally exponentially to the unique solution .
Proof. It is evident from the Theorem 4.1 that GRDS (4.1) owns a unique solution. Assume that is a solution of GRDS (4.1) with . Define the Lyapunov function on by
(4.7) |
We obtained the relation from the Lemma 3.1 and, utilizing (3.8)–(3.11), we acquire
which yields
(4.8) |
where and . Thus, we acquire
(4.9) |
From (3.6), we know that . As a result, the trajectory of the solution of GRDS (4.1) converges globally exponentially to the unique solution of GVIP (3.1).
In this work, we investigate a generalized variation inclusion problem. The resolvent operator for generalized -co-monotone mapping is structured, the Lipschitz constant is estimated and its relationship with the graph convergence is accomplished. An Ishikawa type iterative algorithm is designed and employed to explore the common solution of the generalized variational inclusion and the set of fixed points of a TANM by using the novel implication of graph convergence. Moreover, a generalized resolvent dynamical system is considered and implemented to examine the considered generalized variation inclusion problem.
DF: funding, writing review and editing, supervision; MD: conceptualization, writing review and editing; MA: conceptualization, writing original draft preparation, writing review and editing, supervision. All authors have read and approved the final version of the manuscript for publication.
The authors declare they have not used AI tools in the creation of this article.
The first author acknowledges the Princess Nourah bint Abdulrahman University Researchers Supporting Project, project number PNURSP2024R174, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Authors declare no conflicts of interest in this paper.
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