Research article Special Issues

Generalized variational inclusion: graph convergence and dynamical system approach

  • This work focused on the investigation of a generalized variation inclusion problem. The resolvent operator for generalized η-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 η-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 θH so that

    0(φ+ψ)θ, (1.1)

    where H is a real Hilbert space, ψ:HH is a single-valued monotone operator, and φ:H2H is a maximal monotone operator. We indicate the solution set of the MIP (1.1) by (φ+ψ)1(0). 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 m-accretive mappings [20] as an allied approach for maximal monotone, maximal η-monotone and η-subdifferential mappings. In this sequel, the concept of H-monotone mapping was incepted by Fang and Huang [15] in Hilbert spaces, and later they further coined an analogous notion in Banach spaces named H-accretive mappings [16]. In 2008, Zou and Huang [35] enriched the literature by defining the H(,)-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 H(,)-co-coercive mapping was set forth by Ahmad et al. [3]. This concept was further extended by defining H(,)-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 H(,)-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 H(,)-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 H(,)-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 η-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, H is assumed to be a real Hilbert space endued with norm which induces the metric d and inner product ,. The collection of all closed and bounded subsets of H is signified as CB(H).

    Definition 2.1. Let η:H×HH be a single-valued mapping. A mapping ψ:HH is referred to as

    (i) η-monotone if

    ψ(θ)ψ(ϑ),η(θ,ϑ)0,θ,ϑH;

    (ii) ρ-strongly η-monotone if ρ>0 so that

    ψ(θ)ψ(ϑ),η(θ,ϑ)ρθϑ2,θ,ϑH;

    (iii) ϖ-Lipschitz continuous if ϖ>0 so that

    ψ(θ)ψ(ϑ)ϖθϑ,θ,ϑH;

    (iv) ζ-expansive if ζ>0 so that

    ψ(θ)ψ(ϑ)ζθϑ,θ,ϑH.

    The following lemma is a crucial instrument for carrying out the adopted scheme.

    Lemma 2.1. [34] Let {pk}k=1 be a nonnegative real sequence and {qk}k=1 be a real sequence in [0, 1] with k=0qk= fulfilling the following inequality:

    pk+1(1qk)pk+qkτk,kn0,

    where τk0,k0 and limkτk=0. Then limkpk=0.

    Definition 2.2. Let η,Φ:H×HH and ψ,φ:HH be the single-valued mappings. Then Φ(,) is known as

    (i) m-mixed Lipschitz continuous with respect to ψ and φ if m>0 such that

    Φ(ψ(θ),φ(θ))Φ(ψ(ϑ),φ(ϑ))mθϑ,θ,ϑH;

    (ii) η-co-coercive with respect to ψ if κ>0 such that

    Φ(ψ(θ),a)Φ(ψ(ϑ),a),η(θ,ϑ)κψ(θ)ψ(ϑ)2,θ,ϑH;

    (iii) relaxed η-co-coercive with respect to φ if κ>0 such that

    Φ(b,φ(θ))Φ(b,φ(ϑ)),η(θ,ϑ)(κ)φ(θ)φ(ϑ)2,θ,ϑH;

    (iv) symmetric η-co-coercive with respect to ψ and φ if Φ(,) satisfies (ii) and (iii).

    Definition 2.3. Let η,Φ:H×HH; G,ψ,φ:HH be the single-valued mappings and Ψ:HCB(H) be a set-valued mapping. Then, Φ(,) is known as mixed δ-strongly monotone with respect to G and Ψ, if for some ωΨ(θ),ω¯Ψ(ϑ), δ>0 such that

    Φ(ψ(θ),φ(θ))Φ(ψ(ϑ),φ(ϑ)),η(G(ω),G(ω¯))δθϑ2,θ,ϑH.

    Definition 2.4. Let η:H×HH and f,g:HH be the single-valued mappings. A set-valued mapping M:H×HH is known as

    (i) τ-strongly η-monotone with respect to f if τ>0 so that

    μν,η(θ,ϑ)τθϑ2,θ,ϑ,bH,μM(f(θ),b),νM(f(ϑ),b);

    (ii) τ-relaxed η-monotone with respect to g if τ>0 so that

    μν,η(θ,ϑ)(τ)θϑ2,θ,ϑ,bH,μM(b,g(θ)),νM(b,g(ϑ));

    (iii) M(,) is known as symmetric η-monotone with respect to f and g if M(,) satisfies (i) and (ii).

    Definition 2.5. Let η,Φ:H×HH and ψ,φ,f,g:HH be the single-valued mappings. A set-valued mapping M:H×HH is referred to as generalized η-co-monotone if Φ(,) is symmetric η-co-coercive with respect to ψ and φ, M(,) is symmetric η-monotone with respect to f and g, and

    [Φ(ψ,φ)+ϱM(f,g)](H)=H,ϱ>0. (2.1)

    Note 2.1. Now onward, M is generalized η-co-monotone means, Φ(,) is η-symmetric co-coercive with respect to ψ and φ with constants κ and κ, respectively, and M(,) is symmetric η-monotone with respect to f and g with constants τ and τ, respectively, and satisfies (2.1).

    Lemma 2.2. Let η,Φ:H×HH and ψ,φ,f,g:HH be the single-valued mappings. Let M:H×HH be a generalized η-co-monotone mapping. Let ψ be ς-expansive and φ be l-Lipschitz continuous. Then, for all ϱ>0, the mapping [Φ(ψ,φ)+ϱM(f,g)]1 is single-valued.

    Definition 2.6. Let η,Φ:H×HH and ψ,φ,f,g:HH be the single-valued mappings. Let M:H×HH be a generalized η-co-monotone mapping. The resolvent Rϱ,M(,)η,Φ(,):HH is described as

    Rϱ,M(,)η,Φ(,)(θ)=[Φ(ψ,φ)+ϱM(f,g)]1(θ),θH,ϱ>0. (2.2)

    Proposition 2.1. Let η:H×HH be a π-Lipschitz continuous mapping; Φ:H×HH and ψ,φ,f,g:HH be the single-valued mappings such that ψ is ς-expansive and φ is l-Lipschitz continuous. Let M:H×HH be a generalized η-co-monotone mapping. Then, Rϱ,M(,)η,Φ(,):HH is Ξ-Lipschitz continuous, where

    Ξ=π[ϱ(ττ)+(κς2κl2)].

    Proof. For given θ,ϑH, it follows from (2.2) that

    Rϱ,M(,)η,Φ(,)(θ)=[Φ(ψ,φ)+ϱM(f,g)]1(θ), (2.3)
    Rϱ,M(,)η,Φ(,)(ϑ)=[Φ(ψ,φ)+ϱM(f,g)]1(ϑ). (2.4)

    From (2.3) and (2.4), one can write

    1ϱ(θΦ(ψ(Rϱ,M(,)η,Φ(,)(θ)),φ(Rϱ,M(,)η,Φ(,)(θ))))M(f(Rϱ,M(,)η,Φ(,)(θ)),g(Rϱ,M(,)η,Φ(,)(θ))), (2.5)
    1ϱ(ϑΦ(ψ(Rϱ,M(,)η,Φ(,)(ϑ)),φ(Rϱ,M(,)η,Φ(,)(ϑ))))M(f(Rϱ,M(,)η,Φ(,)(ϑ)),g(Rϱ,M(,)η,Φ(,)(ϑ))). (2.6)

    For the sake of simplicity, we indicate Λ(θ)=Rϱ,M(,)η,Φ(,)(θ) and Λ(ϑ)=Rϱ,M(,)η,Φ(,)(ϑ), and since M(,) is symmetric η-monotone, then

    ϱ(ττ)Λ(θ)Λ(ϑ)2θΦ(ψ(Λ(θ)),φ(Λ(θ)))(ϑΦ(ψ(Λ(ϑ)),φ(Λ(ϑ))),η(Λ(θ),Λ(ϑ))θϑ,η(Λ(θ),Λ(ϑ))Φ(ψ(Λ(θ)),φ(Λ(θ)))Φ(ψ(Λ(ϑ)),φ(Λ(ϑ))),η(Λ(θ),Λ(ϑ))=θϑ,η(Λ(θ),Λ(ϑ))Φ(ψ(Λ(θ)),φ(Λ(θ)))Φ(ψ(Λ(ϑ)),φ(Λ(θ))),η(Λ(θ),Λ(ϑ))Φ(ψ(Λ(ϑ)),φ(Λ(θ)))Φ(ψ(Λ(ϑ)),φ(Λ(ϑ))),η(Λ(θ),Λ(ϑ)).

    Invoking symmetric η-co-coercivity of Φ, ς-expansiveness of ψ, l and π-Lipschitz continuities of φ and η, respectively, we attain ϱ(ττ)Λ(θ)Λ(ϑ)2θϑ,η(Λ(θ),Λ(ϑ))(κς2κl2)Λ(θ)Λ(ϑ)2, i.e.,

    [ϱ(ττ)+(κς2κl2)]Λ(θ)Λ(ϑ)2θϑη(Λ(θ),Λ(ϑ))θϑπΛ(θ)Λ(ϑ).

    Thus, for all θ,ϑH, we obtain Λ(θ)Λ(ϑ)Ξθϑ, i.e.,

    Rϱ,M(,)η,Φ(,)(θ)Rϱ,M(,)η,Φ(,)(ϑ)Ξθϑ,θ,ϑH, (2.7)

    where, Ξ=π[ϱ(ττ)+(κς2κl2)].

    Definition 2.7. The graph of a multivalued mapping M:H×HH is expressed as

    Graph(M)={((θ,ϑ),ξ):ξM(θ,ϑ)}.

    Definition 2.8. Let η,Φ:H×HH and ψ,φ,f,g:HH be the single-valued mappings. For n0, let Mn,M:H×HH be generalized η-co-monotone mappings. Then, {Mn}n=1 is known as graph convergent to M, indicated by (MnGM) if for each (f(θ),g(θ),ξ)Graph(M), {(f(θn),g(θn),ξn)}Graph(Mn) so that

    f(θn)f(θ),g(θn)g(θ)andξnξasn.

    Theorem 2.1. Let η,Φ:H×HH and ψ,φ,f,g:HH be the single-valued mappings such that Φ(,) is m-mixed Lipschitz continuous with respect to ψ and φ, and f,g are continuous mappings so that f is ζ-expansive. For n0, let Mn,M:H×HH be generalized η-co-monotone mappings. Then,

    MnGMRϱ,Mn(,)η,Φ(,)(θ)Rϱ,M(,)η,Φ(,)(θ),θH,ϱ>0.

    Proof. For all θH and ϱ>0, suppose that Rϱ,Mn(,)η,Φ(,)(θ)Rϱ,M(,)η,Φ(,)(θ). Assume that (f(θ),g(θ),ξ)Graph(M), then

    θ=Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))+ϱξ]. (2.8)

    Letting

    θn=Rϱ,Mn(,)η,Φ(,)[Φ(ψ(θ),φ(θ))+ϱξ], (2.9)

    which turns into

    Φ(ψ(θ),φ(θ))+ϱξ[Φ(ψ(θn),φ(θn))+ϱM(f(θn),g(θn))]. (2.10)

    For each n0, take ξnM(f(θn),g(θn)), then (2.10) yields

    Φ(ψ(θ),φ(θ))+ϱξ=Φ(ψ(θn),φ(θn))+ϱξn. (2.11)

    Invoking the m-mixed Lipschitz continuity of Φ, it follows from (2.11) that

    ϱξnϱξ=Φ(ψ(θn),φ(θn))Φ(ψ(θ),φ(θ))(ρ+ρ)θnθ. (2.12)

    Thus, ξnξmϱθnθ. Recalling the hypothesis Rϱ,Mn(,)η,Φ(,)(θ)Rϱ,M(,)η,Φ(,)(θ), it yields from (2.8) and (2.9) that θnθ0 and, hence, from (2.12), we acquire ξnξ0 as n. Accounting the continuity of f and g, we deduce f(θn)f(θ) and g(θn)g(θ), and so MnGM.

    On the contrary, assume that MnGM and choose an arbitrary but fixed eH. Since M(,) is a generalized η-co-monotone mapping, Range[Φ(ψ,φ)+ϱM(f,g)]=H. Then, there exists ((f(θ),g(θ)),ξ)Graph(M) such that e=Φ(ψ(θ),φ(θ))+ϱξ. Since (f(θ),g(θ),ξ)Graph(M) and suppose (f(θn),g(θn),ξn)Graph(Mn),

    θ=Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))+ϱξ]andθn=Rϱ,Mn(,)η,Φ(,)[Φ(ψ(θn),φ(θn))+ϱξn].

    Letting en=Φ(ψ(θn),φ(θn))+ϱξn, for all n0, adducing the m-mixed Lipschitz continuity Φ(,) and making use of (2.7), we acquire

    Rϱ,Mn(,)η,Φ(,)(e)Rϱ,M(,)η,Φ(,)(e) Rϱ,Mn(,)η,Φ(,)(e)Rϱ,Mn(,)η,Φ(,)(en)+Rϱ,Mn(,)η,Φ(,)(en)Rϱ,M(,)η,Φ(,)(e)Ξene+θnθ=ΞΦ(ψ(θn),φ(θn))+ϱξn[Φ(ψ(θ),φ(θ))+ϱξ]+θnθΞΦ(ψ(θn),φ(θn))Φ(ψ(θ),φ(θ))+Ξϱξnξ+θnθ[1+Ξm]θnθ+Ξϱξnξ. (2.13)

    The ζ-expansiveness of f yields

    f(θn)f(θ)ζθnθ0. (2.14)

    Thus, we deduce from (2.14) and the Definition 2.8 that θnθ and ξnξ as n. Thus, from (2.13), we infer that Rϱ,Mn(,)η,Φ(,)(θ)Rϱ,M(,)η,Φ(,)(θ).

    Example 2.1 Let H=R2 with the usual inner product on R2, i.e.,

    (θ1,θ2),(ϑ1,ϑ2)=θ1ϑ1+θ2ϑ2,(θ1,θ2),(ϑ1,ϑ2)R2.

    Define ψ,φ:R2R2 and η,Φ:R2×R2R2 by

    ψ(θ1,θ2)=(θ14,θ22),φ(θ1,θ2)=(θ12,2θ23),(θ1,θ2)R2,Φ(ψ(θ),φ(θ))=ψ(θ)+φ(θ),θR2,η(θ,ϑ)=θϑ2,θ,ϑR2.

    Then, for any fixed ςR2, we find

    Φ(ψ(θ),ς)Φ(ψ(ϑ),ς),η(θ,ϑ)1ψ(θ)ψ(ϑ)2,Φ(ς,φ(θ))Φ(ς,φ(ϑ)),η(θ,ϑ)(1)φ(θ)φ(ϑ)2.

    Thus, Φ(,) is η-co-coercive with respect to ψ and relaxed η-co-coercive with respect to φ, hence Φ(,) is symmetric η-co-coercive. Next, we estimate the symmetric monotonicity of M. Define f,g:R2R2 and M:R2×R2R2 by

    f(θ1,θ2)=(θ13θ2,θ1+θ22),g(θ1,θ2)=(θ13+θ22,θ12+θ24),(θ1,θ2)R2,M(f(θ),g(θ))=f(θ)g(θ),θR2.

    Then for any fixed ϖR2, we find

    M(f(θ),ϖ)M(f(ϑ),ϖ),η(θ,ϑ)16θϑ2,M(ϖ,g(θ))M(ϖ,g(ϑ)),η(θ,ϑ)16θϑ2,

    i.e., M(,) is η-monotone with respect to f and relaxed η-monotone with respect to g, hence M(,) is symmetric η-monotone. Also, for any θR2 and ϱ>0,

    [Φ(ψ,φ)+ϱM(f,g)](θ)=ψ(θ)+φ(θ)+ϱ(f(θ)g(θ))=[θ143ϱ2θ2,3ϱ2θ1+(ϱ416)θ2],

    i.e., [Φ(ψ,φ)+ϱM(f,g)](R2)=R2,ϱ>0. Thus, M(,) is a generalized η-co-monotone mapping. Further, we show that MnGM. Let

    f(θn)=(θ13θ2+2n,θ1+θ22+1n),g(θn)=(θ13+θ22+2n2,θ12+θ24+1n2),

    and ξn=Mn(f(θn),g(θn))=f(θn)g(θn)=(32θ2+2n2n2,32θ1+14θ2+1n1n2). One can observe that

    limnf(θn)=limn(θ13θ2+2n,θ1+θ22+1n)=(θ13θ2,θ1+θ22),limng(θn)=limn(θ13+θ22+2n2,θ12+θ24+1n2)=(θ13+θ22,θ12+θ24),

    and limnξn=limn(32θ2+2n2n2,32θ1+14θ2+1n1n2)=f(θ)g(θ)=M(f(θ),g(θ))=ξ.

    Thus, we acquire that limnf(θn)=f(θ) and limng(θn)=g(θ) and limnξn=ξ. Hence, MnGM. Finally, it remains to manifest that MnGMRϱ,Mn(,)η,Φ(,)(θ)Rϱ,M(,)η,Φ(,)(θ),θH,ϱ>0. Now, for ϱ=1, the associated resolvent operators are estimated as:

    Rϱ,Mn(,)η,Φ(,)(θ)=[Φ(ψ,φ)+Mn(f,g)]1(θ)=(14θ132θ2+2n2n2,32θ1+112θ2+1n1n2)1=1107(4θ1+72θ280n+80n2,72θ112θ2+156n156n2)

    and

    Rϱ,M(,)η,Φ(,)(θ)=[Φ(ψ,φ)+M(f,g)]1(θ)=(14θ132θ2,32θ1+112θ2)1=1107(4θ1+72θ2,72θ112θ2),

    which yields

    Rϱ,Mn(,)η,Φ(,)(θ)Rϱ,(,)η,Φ(,)(θ)0asn.

    Thus, we obtain

    Rϱ,Mn(,)η,Φ(,)(θ)Rϱ,(,)η,Φ(,)(θ)asMnGM.

    In this section, we employ a generalized η-co-monotone mapping for investigating a general variational inclusion (GVIP). We examine the problem of discerning θH,ωΨ(θ) so that

    0G(ω)+M(f(θ),g(θ)), (3.1)

    where G,f,g:HH and M:H×HH;Ψ:HCB(H) are single-valued and multivalued mappings, respectively. We signify the Problem (3.1) as GVIP and its solution set by Ω(H,M,Φ,G,η).

    Lemma 3.1. Let η,Φ:H×HH and G,ψ,φ,f,g:HH be the single-valued mappings and Ψ:HCB(H) a multivalued mapping. Let M:H×HH be a generalized η-co-monotone mapping. Then, (θ,ω), where θH,ωΨ(θ) solves GVIP (3.1) if, and only if,

    θ=Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]. (3.2)

    Proof. One can obtain the conclusion immediately by implementing (2.2).

    A mapping F:HH is referred to as non-expansive (NM) if F(θ)F(ϑ)θϑ,θ,ϑH. 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 F:HH is known as ANM if is a sequence {εn}[1,) with limnεn=1 and nN,

    Fn(θ)Fn(ϑ)εnθϑ,θ,ϑH.

    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 F:HH is known as NANM, if {εn}[1,) and {υn}[0,) with limnεn=1,limnυn=0, nN,

    Fn(θ)Fn(ϑ)εnθϑ+υn,θ,ϑH.

    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 F:HH is known as TANM if nonnegative sequences of real numbers {εn},{υn} with limnεn=0=limnυn and a strictly increasing continuous function γ:R+R+ such that γ(0)=0 and nN,

    Fn(θ)Fn(ϑ)θϑ+μnγ(θϑ)+νn,θ,ϑH.

    Let F:HH be a TANM and presume that the mappings η,Φ,G,ψ,φ,f,g,Ψ, and M are identical as in Lemma 3.1. Suppose that θFix(F)Ω(H,M,Φ,G,η), then from (3.2), one can achieve the following formulation:

    θ=Fnθ=Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]=FnRϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)], (3.3)

    where ϱ>0 and ωΨ(θ). By the virtue of formulation (3.3), we design the following Ishikawa type resolvent iterative scheme to explore a common element of Fix(F) and Ω(H,M,Φ,G,η). Here, Fix(F) indicates the set of fixed points of TANM F and Ω(H,M,Φ,G,η) indicates the solution set of GVIP (3.1).

    Algorithm 3.1. Let η,Φ:H×HH and G,ψ,φ,f,g:HH be the single-valued mappings. Let Ψ:HCB(H) be a multivalued mapping; Mn,M:H×HH be generalized η-co-monotone mappings, and F:HH be a TANM. For initial points θ0,ϑ0H,ω0Ψ(θ0), estimate the sequences {θn},{ωn} by the following procedure:

    θn+1=(1αn)θn+αnFnRϱ,Mn(,)η,Φ(,)[Φ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)], (3.4)
    ϑn=(1βn)θn+βnFnRϱ,Mn(,)η,Φ(,)[Φ(ψ(θn),φ(θn))ϱG(ωn)], (3.5)

    for n=0,1,2,, ωnΨ(θn),ω¯nΨ(ϑn), 0αn,βn1,n=0αn=, and ϱ>0.

    Theorem 3.1. Let η:H×HH be a π-Lipschitz continuous mapping; Φ:H×HH and ψ,φ,f,g:HH be the single-valued mappings such that Φ(,) is m-mixed Lipschitz continuous with respect to ψ and φ and ι-mixed strongly monotone with respect to G and Ψ, G is t-Lipschitz continuous, Ψ is D-Lipschitz continuous with constant r, ψ is ς-expansive, and φ is l-Lipschitz continuous. Let Mn,M:H×HH be generalized η-co-monotone mappings. Let F:HH be a ({μn},{νn},ϕ)-TANM so that Fix(F)Ω(H,M,Φ,G,η). If ϱ>0 obeys the following relation:

    m22ϱι+ϱ2t2r2<[ϱ(ττ)+(κς2κl2)]π. (3.6)

    (i) Then Ω(H,M,Φ,G,η) is singleton.

    (ii) If MnGM, then the sequence {θn} induced by (3.4)-(3.5) converges strongly to θFix(F)Ω(H,M,Φ,G,η).

    Proof. (i) Define G:HH as

    G(θ)=Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)],θH. (3.7)

    By making use of Proposition 2.1 and (3.7), for all θ,ϑH, we acquire

    G(θ)G(ϑ)=Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]Rϱ,M(,)η,Φ(,)[Φ(ψ(ϑ),φ(ϑ))ϱG(ω¯)]ΞΦ(ψ(θ),φ(θ))Φ(ψ(ϑ),φ(ϑ))ϱ(G(ω)ϱG(ω¯)). (3.8)

    Utilizing the m-mixed Lipschitz continuity and ι-mixed strong monotonicity of Φ and Lipschitz continuities of G and Ψ, we acquire

    Φ(ψ(θ),φ(θ))Φ(ψ(ϑ),φ(ϑ))ϱ(G(ω)ϱG(ω¯))2=Φ(ψ(θ),φ(θ))Φ(ψ(ϑ),φ(ϑ))22ϱΦ(ψ(θ),φ(θ))Φ(ψ(ϑ),φ(ϑ)),G(ω)G(ω¯)+ϱ2G(ω)G(ω¯)2(m22ϱι+ϱ2t2r2)θϑ2. (3.9)

    After simplification, the above inequality turns into

    Φ(ψ(θ),φ(θ))Φ(ψ(ϑ),φ(ϑ))ϱ(G(ω)ϱG(ω¯))m22ϱι+ϱ2t2r2θϑ. (3.10)

    Thus, (3.10) and (3.8) yield

    G(θ)G(ϑ)Θθϑ, (3.11)

    where Θ=Ξm22ϱι+ϱ2t2r2 and Ξ=π[ϱ(ττ)+(κς2κl2)]. Taking the premise (3.6) into consideration, we see that 0Θ<1. Thus, G being a contraction mapping owns a unique fixed point, i.e., a unique θH so that Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]=θ. Consequently, Lemma 3.1 guarantees that Ω(H,M,Φ,G,η) is singleton.

    (ii) By the assumption that Fix(F)Ω(H,M,Φ,G,η) and in (i), we confirmed that Ω(H,M,Φ,G,η) is singleton. Suppose that Ω(H,M,Φ,G,η)={θ}, then we deduce that θFix(F) and consequently, by (3.3), one can express

    θ=(1αn)θ+αnFnRϱ,M(,)η,Φ(,)[Φ(ψ(ϑ),φ(ϑ))ϱG(ω¯)]]=(1βn)θ+βnFnRϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]. (3.12)

    Utilizing the Proposition 2.1, we get

    Rϱ,Mn(,)η,Φ(,)[Φ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)]Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]Rϱ,Mn(,)η,Φ(,)[Φ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)]Rϱ,Mn(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]+Rϱ,Mn(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]ΞΦ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)[Φ(ψ(θ),φ(θ))ϱG(ω)]+Σn=ΞΦ(ψ(ϑn),φ(ϑn))Φ(ψ(θ),φ(θ))ϱ[G(ω¯n)G(ω)]+Σn, (3.13)

    where Σn=Rϱ,Mn(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]. Utilizing the Lipschtz continuities of Ψ and G, we acquire

    G(ω¯n)G(ω)tω¯nωtD(Ψ(ω¯n),Ψ(ω))trϑnθ. (3.14)

    Also, utilizing m-mixed Lipschitz continuity of Φ regarding ψ and φ, ι-mixed strong monotonicity with respect to G and Ψ and combining (3.14), we acquire

    Φ(ψ(ϑn),φ(ϑn))Φ(ψ(θ),φ(θ))ϱ[G(ω¯n)G(ω)]2=Φ(ψ(ϑn),φ(ϑn))Φ(ψ(θ),φ(θ))22ϱΦ(ψ(ϑn),φ(ϑn))Φ(ψ(θ),φ(θ)),G(ω¯n)G(ω)+ϱ2G(ω¯n)G(ω)2m2ϑnθ22ϱιϑnθ2+ϱ2t2r2ϑnθ2=(m22ϱι+ϱ2t2r2)ϑnθ2,

    which yields

    Φ(ψ(ϑn),φ(ϑn))Φ(ψ(θ),φ(θ))ϱ[G(ω¯n)G(ω)]m22ϱι+ϱ2t2r2ϑnθ. (3.15)

    After substituting (3.15) into (3.13), we obtain

    Rϱ,Mn(,)η,Φ(,)[Φ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)]Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]Θϑnθ+Σn, (3.16)

    where Θ=Ξm22ϱι+ϱ2t2r2. Now, recalling that F is ({μn},{νn},ϕ)-total asymptotically non-expansive and applying (3.4) and (3.12), we get

    θn+1θ=(1αn)θn+αnFnRϱ,Mn(,)η,Φ(,)[Φ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)][(1αn)θ+αnFnRϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]](1αn)θnθ+αnFnRϱ,Mn(,)η,Φ(,)[Φ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)]FnRϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)](1αn)θnθ+αn[Rϱ,Mn(,)η,Φ(,)[Φ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)]Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]+μnϕ[Rϱ,Mn(,)η,Φ(,)[Φ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)]Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]]+νn]. (3.17)

    By substituting (3.16) in (3.17), we acquire

    θn+1θ(1αn)θnθ+αn[(Θϑnθ+Σn)+μnϕ(Θϑnθ+Σn)+νn]. (3.18)

    Following the same steps and employing the same facts as in (3.17), it follows from (3.5) and (3.12) that

    ϑnθ=(1βn)θn+βnFnRϱ,Mn(,)η,Φ(,)[Φ(ψ(θn),φ(θn))ϱG(ωn)][(1βn)θ+βnFnRϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]](1βn)θnθ+βnFnRϱ,Mn(,)η,Φ(,)[Φ(ψ(θn),φ(θn))ϱG(ωn)]FnRϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)](1βn)θnθ+βn[Rϱ,Mn(,)η,Φ(,)[Φ(ψ(θn),φ(θn))ϱG(ωn)]Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]+μnϕ[Rϱ,Mn(,)η,Φ(,)[Φ(ψ(θn),φ(θn))ϱG(ωn)]Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]]+νn](1βn)θnθ+βn[(Θθnθ+Σn)+μnϕ(Θθnθ+Σn)+νn]. (3.19)

    By the hypothesis MnGM, we obtain Σn0, thus from (3.18) and (3.19), we deduce that

    θn+1θ(1αn)θnθ+αn[Θϑnθ+μnϕ(Θϑnθ)+νn]. (3.20)
    ϑnθ(1βn)θnθ+βn[Θθnθ+μnϕ(Θθnθ)+νn]. (3.21)

    Substituting (3.21) into (3.20), we acquire

    θn+1θ(1αn)θnθ+αn[Θ{(1βn)θnθ+βn[Θθnθ+μnϕ(Θθnθ)+νn]}+μnϕ(Θ{(1βn)θnθ+βn[Θθnθ+μnϕ(Θθnθ)+νn]})+νn]=[(1αn)+αnΘ[1βn(1Θ)]]θnθ+αn[βnΘ{μnϕ(Θθnθ)+νn}+μnϕ{Θ{[1βn(1Θ)]θnθ+μnϕ(Θθnθ)+νn}}+νn][1αn(1Θ)]θnθ+αn(1Θ)[βnΘ{μnϕ(Ψn)+νn}+μnϕ{Θ{Γn+μnϕ(Ψn)+νn}}+νn](1Θ), (3.22)

    where Ψn=Θθnθ and Γn=[1βn(1Θ)]θnθ. For each nn0, setting pn=θnθ,qn=αn(1Θ) and τn=βnΘ[μnϕ(Ψn)+νn]+μnϕ[Θ{Γn+μnϕ(Ψn)+νn}]+νn(1Θ). Clearly, n=0qn= because of n=0αn=. In fact, μn,νn0 as n yields τn=0. Thus, we deduce from Lemma 2.1 that limnpn=0 and, hence, limnθn=θ.

    Example 3.1. Let H=[0,) with inner product θ,ϑ=θϑ and norm ||. Define F(θ)=sinθ,θ[0,). Then, clearly 0Fix(F) for all θ,ϑ[0,), and we express

    F(θ)F(ϑ)=sinθsinϑ=2sin(θϑ)2cos(θ+ϑ)2θϑ.

    Thus, F is non-expansive, hence F is TANM with μn=1n2 and νn=1n3,n1. Define the mappings η,Φ:H×HH and G,ψ,φ,f,g:HH by

    η(θ,ϑ)=θϑ4,Φ(ψ(θ),φ(θ))=ψ(θ)+φ(θ),G(θ)=θ12,ψ(θ)=3θ+14,φ(θ)=θ14,f(θ)=4θ+1,g(θ)=2θ+12.

    It can be easily observed that η,G, and φ are Lipschitz continuous with constants π=14,t=12, and φ=14, respectively, and ψ is 34-expansive. Also,

    Φ(ψ(θ),φ(θ))Φ(ψ(ϑ),φ(ϑ))12θϑ,θ,ϑH,Φ(ψ(θ),φ(θ))Φ(ψ(ϑ),φ(ϑ)),η(θ,ϑ)18θϑ2,θ,ϑH,Φ(ψ(θ),k)Φ(ψ(ϑ),k),η(θ,ϑ)13ψ(θ)ψ(ϑ)2,θ,ϑ,kH,Φ(k,φ(θ))Φ(k,φ(ϑ)),η(θ,ϑ)(1)φ(θ)φ(ϑ)2,θ,ϑ,kH,

    i.e., Φ(,) is 1/2-mixed Lipschitz continuous, 1/8-mixed strongly monotone, and symmetric η-co-coercive with respect to ψ and φ with constants 1/3 and 1, respectively. Define M:H×HH and Ψ:HCB(H) by M(f(θ),g(θ))=f(θ)+g(θ)3andΨ(θ)={θ5+1}. Then, Ψ is 1/5-Lipschitz continuous and

    M(f(θ),k)M(f(ϑ),k),η(θ,ϑ)1/3θϑ2,θ,ϑ,kH,M(k,g(θ))M(k,g(ϑ)),η(θ,ϑ)(1/6)θϑ2,θ,ϑ,kH,

    i.e., M(,) is symmetric η-monotone with respect to f and g with constants 1/3 and 1/6, respectively. Thus, M(,) is a generalized η-co-monotone mapping. Also, G(θ)=Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]=52θ and the estimated constants satisfy (3.6), that is, m22ϱι+ϱ2t2r2<[ϱ(ττ)+(κς2κl2)]π. Therefore, θ=0H is a unique fixed point of G. Thus, we have θ=0Fix(F)Ω(H,M,Φ,G,η). Next, we compute the sequence {θn} by employing Algorithm 3.1. Let αn=n2n+1 and βn=1n+1. Then

    θn+1=(1αn)θn+αnRϱ,M(,)η,Φ(,)[Φ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)],θn+1=(n+12n+1)θn+(3n5(2n+1))ϑn,ϑn=(1βn)θn+βnRϱ,M(,)η,Φ(,)[Φ(ψ(θn),φ(θn))ϱG(ωn)],ϑn=(nn+1)θn+(35(n+1))θn.

    For different initial points: θ0=10.5 and θ0=1.5, the sequence θn0 and 0Fix(F)Ω(H,M,Φ,G,η) and the convergence behavior of {θn} is shown in Figure 1.

    Figure 1.  Convergence behavior of {θn} for Example 3.1 and Example 3.2 with initial values θ0=10.5,θ0=1.5, and θ0=6,θ0=1, respectively.

    Example 3.2. Let H=R with inner product θ,ϑ=θϑ and norm ||. Define F(θ)=sinθ,θR. Then, clearly F is TANM with μn=1n2 and νn=1n3,n1 and 0Fix(F). Define the mappings η,Φ:H×HH and G,ψ,φ,f,g:HH by

    η(θ,ϑ)=θϑ3,Φ(ψ(θ),φ(θ))=ψ(θ)+φ(θ)2,G(θ)=θ3,ψ(θ)=θ2,φ(θ)=θ4,f(θ)=2θ,g(θ)=θ.

    Then η,G, and φ are Lipschitz continuous with constants π=t=13 and l=14, respectively, and ψ is 12-expansive. Also, Φ(,) is 1/8-mixed Lipschitz continuous, 1/16-mixed strongly monotone, and symmetric η-co-coercive with respect to ψ and φ with constants 1/3 and 2/3, respectively. Define M:H×HH and Ψ:HCB(H) by M(f(θ),g(θ))=f(θ)+g(θ)3andΨ(θ)={θ}. Then, Ψ is 1-Lipschitz continuous and M(,) is symmetric η-monotone with respect to f and g with constants 2/9 and 1/9, respectively. Thus, M(,) is a generalized η-co-monotone mapping. Also, for ϱ=1, the estimated constants satisfy (3.6), that is, m22ϱι+ϱ2t2r2<[ϱ(ττ)+(κς2κl2)]π and Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]=511θ. Therefore, 0R is a unique fixed point of Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)]. Thus, we have 0Fix(F)Ω(H,M,Φ,G,η). Now for αn=n2n+1 and βn=1n+1, we compute the sequence {θn} by employing Algorithm 3.1 as under:

    θn+1=(1αn)θn+αnRϱ,M(,)η,Φ(,)[Φ(ψ(ϑn),φ(ϑn))ϱG(ω¯n)],θn+1=(n+12n+1)θn(5n11(2n+1))ϑn,ϑn=(1βn)θn+βnRϱ,M(,)η,Φ(,)[Φ(ψ(θn),φ(θn))ϱG(ωn)],ϑn=(nn+1)θn(511(n+1))θn.

    For different initial points: θ0=6, and θ0=1, the sequence θn0 and 0Fix(F)Ω(H,M,Φ,G,η) 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:

    dθds=ξ{Rϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]θ},θ(s0)=θ0H, (4.1)

    where θH,ωΨ(θ), and ξ>0 is a parameter.

    Definition 4.1. [24] It is stated that the GRDS (4.1) converges to the solution set Ω(H,M,Φ,G,η) of GVIP (3.1) if the trajectory of the dynamical system, irrespective of the initial point, satisfies

    limsdist(θ(s),Ω)=0,

    where

    dist(θ(s),Ω)=infϑΩθϑ.

    If θ is a unique point of Ω, then limtθ(s)=θ.

    Definition 4.2. [25] The dynamical system is referred to as globally exponentially stable with degree k at θ if the trajectory of the dynamical system, irrespective of the initial point, satisfies

    θ(s)θc0θ(s0)θexp(k(ss0)),ss0,

    where positive constants k and c0 do not depend on the initial point.

    Lemma 4.1. [26] Let θ~ and ϑ~ be real-valued nonnegative continuous functions with domain {s:ss0} and let α(s)=α0(|ss0|) where α0 is a monotonic increasing function. If for all ss0,

    θ~(s)α(s)+s0sθ~(t)ϑ~(t)dt,

    then

    θ~(s)α(s).exp(s0sϑ~(t)dt).

    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 θ0H with ω0Ψ(θ0), there exists a unique continuous solution θ(s) with θ(s0)=θ0 of GRDS (4.1) over [s0,).

    Proof. Define

    G(θ)=ξ{Rϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]θ},θH.

    Invoking the arguments as for (3.8), we obtain

    G(θ)G(ϑ)=ξRϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]θ{Rϱ,M(,)η,Φ(,)[Φ(ψϑ,φϑ)ϱG(ω¯)]ϑ}ξΞΦ(ψθ,φθ)Φ(ψϑ,φϑ)ϱ(G(ω)G(ω¯))+ξθϑ. (4.2)

    Invoking the arguments as employed to (3.9), we obtain

    Φ(ψθ,φθ)Φ(ψϑ,φϑ)ϱ(G(ω)G(ω¯))m22ϱι+ϱ2t2r2θϑ. (4.3)

    (4.2) and (4.3) together yields

    G(θ)G(ϑ)ξ(1+Θ)θϑ, (4.4)

    which proves that G is locally Lipschitz continuous in H. Thus, for each θ0H, a unique continuous solution θ(s) of GRDS (4.1) with θ(s0)=θ0 in the interval s0s<S. Let the maximal interval of its existence be [s0,S). Next, we substantiate that S=. Now, for any θH,ωΨ(θ), we have

    G(θ)=ξRϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]θξRϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]θ+ξθθ=ξRϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]Rϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]+ξθθξΞΦ(ψθ,φθ)Φ(ψθ,φθ)ϱ(G(ω)G(ω))]+ξθθξ(1+Θ)θθξ(1+Θ)θ+ξ(1+Θ)θ. (4.5)

    Employing the integral on (4.5) over [s0,s] and utilizing Lemma 4.1, we get

    θ(s)θ0+s0sG(θ(τ))dτ{θ0+k5(ss0)}+k6s0sθ(τ)dτ,s[s0,S){θ0+k5(ss0)}exp{k6(ss0)},s[s0,S), (4.6)

    where k5=ξ(1+Θ)θ and k6=ξ(1+Θ). Hence the solution is bounded on [s0,S), so S=.

    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 θΩ(H,M,Φ,G,η).

    Proof. It is evident from the Theorem 4.1 that GRDS (4.1) owns a unique solution. Assume that θ(s)=(s,s0;θ0) is a solution of GRDS (4.1) with θ(s0)=θ0. Define the Lyapunov function L on H by

    L(θ)=12θθ2,θH. (4.7)

    We obtained the relation θ=Rϱ,M(,)η,Φ(,)[Φ(ψ(θ),φ(θ))ϱG(ω)] from the Lemma 3.1 and, utilizing (3.8)–(3.11), we acquire

    dLds=θ(s)θ,dθds=ξθ(s)θ,Rϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]θ=ξθ(s)θ,θ(s)θ+ξRϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]θξθ(s)θ2+ξθ(s)θ,Rϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]Rϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]ξθ(s)θ2+ξθ(s)θRϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]Rϱ,M(,)η,Φ(,)[Φ(ψθ,φθ)ϱG(ω)]ξθ(s)θ2+ξΘθ(s)θ2,

    which yields

    dds12θθ2=ξ(1Θ)θ(s)θ2, (4.8)

    where Θ=Ξm22ϱι+ϱ2t2r2 and Ξ=π[ϱ(ττ)+(κς2κl2)]. Thus, we acquire

    θθθ0θeξ(1Θ)(ss0). (4.9)

    From (3.6), we know that 1Θ>0. 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 η-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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