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Online scheduling on a single machine with one restart for all jobs to minimize the weighted makespan

  • In this paper, we consider the online scheduling problem on a single machine to minimize the weighted makespan. In this problem, all jobs arrive over time and they are allowed to be restarted only once. For the general case when the processing times of all jobs are arbitrary, we show that there is no online algorithm with a competitive ratio of less than 2, which matches the lower bound of the problem without restart. That is, only one restart for all jobs is invalid for improving the competitive ratio in the general case. For the special case when all jobs have the same processing time, we present the best possible online algorithm with a competitive ratio of 1.4656, which improves the competitive ratio of 1+521.618 for the problem without restart.

    Citation: Xiaoxiao Liang, Lingfa Lu, Xueke Sun, Xue Yu, Lili Zuo. Online scheduling on a single machine with one restart for all jobs to minimize the weighted makespan[J]. AIMS Mathematics, 2024, 9(1): 2518-2529. doi: 10.3934/math.2024124

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  • In this paper, we consider the online scheduling problem on a single machine to minimize the weighted makespan. In this problem, all jobs arrive over time and they are allowed to be restarted only once. For the general case when the processing times of all jobs are arbitrary, we show that there is no online algorithm with a competitive ratio of less than 2, which matches the lower bound of the problem without restart. That is, only one restart for all jobs is invalid for improving the competitive ratio in the general case. For the special case when all jobs have the same processing time, we present the best possible online algorithm with a competitive ratio of 1.4656, which improves the competitive ratio of 1+521.618 for the problem without restart.



    The scientific world is now paying more and more attention to fractional calculus, which has an expanding variety of applications in fields including astronomy, electricity, life sciences, viscosity, medical science, control theory, data processing, etc. Due to the vast range of domains that fractional concepts are applied to, including physics, mechanics, chemistry, and engineering, fractional differential equations (FDEs), have become incredibly important. The study of ordinary and partial differential equations containing fractional derivatives has advanced significantly in recent years. We recommend the reader to read some books and articles published by Kilbas et al. [1], Diethelm [2], Zhou [3], Podulbny [4], Miller and Ross [5], Lakshmikantham et al. [6], and a series of papers [7,8,9,10] and the references cited therein.

    The Caputo and Riemann-Liouville (R-L) fractional derivatives were among the initial fractional order derivatives that Hilfer [11] presented in his new operator named the Hilfer fractional derivative (HFD). Additionally, conceptual simulations of dielectric relaxation in glass components, polymers, rheological permanent simulation, and other domains have revealed the significance and usefulness of the HFD. To study the existence of an integral solution related to an evolution boundary value problem (BVP) equipped with the HFD, Gu and Trujillo [12], recently, employed the measure of noncompactness technique. Along with this article, other numerous academic articles have addressed the HFD in their theorems; see [13,14,15,16]. According to the methods used in [17,18,19,20,21], some researchers used almost sectorial operators to find a mild solution for some BVPs in the framework of the HFD systems.

    Neutral differential equations have gained a lot of attention lately because of their many applications in a variety of domains, such as biological models, chemical kinetics, electronics, and fluid dynamics. We refer to the works on the theory and applications of neutral partial differential equations (PDEs) with non-local and classical situations as [21,22,23,24,25,26] and the references therein. We observe that there has been a recent surge in interest in neutral structures due to their prevalence in many applications of applied mathematics.

    Since the above differential equations were originally used to numerically mimic a variety of occurrences in the humanities and natural sciences [27], stochastic PDEs have also attracted a lot of interest. Rather than focusing on deterministic models, more research should be done on stochastic models, as unpredictability and uncontrollable fluctuations are intrinsic to both manmade and natural systems. Stochastic differential equations (SDEs) represent a specific event mathematically by including irrationality. The research community has recently shown a great deal of interest in the use of SDEs in finite and infinite dimensions to represent a variety of processes in population fluctuations, mathematics, mechanical engineering, physical location, behavioral science, life sciences, and several other science and technology domains. See [13,23,28,29] for a comprehensive introduction to SDEs and their applications.

    Almost sectorial operators are being used by researchers to advance the existence concepts in fractional calculus. In this direction, for a system under study, researchers have created a unique way of identifying mild solutions. In addition, a theory has been developed to predict different requirements of linked semigroups formed by almost sectorial operators using multivalued maps, the Wright function, fractional calculus, semigroup operators, the MNC, and the fixed-point approach. For more details, refer to [18,25,30,31,32,33]. Some researchers in [17,18,19] analyzed their results via the almost sectorial operators by employing the Schauder's fixed-point theorem. The authors in [34,35,36,37] conducted an analysis of fractional evolution equations (FEEs) via a similar method with the sectorial operators. Further, Zhou [38] established the attractivity for FEEs with almost sectorial operators by using the Ascoli-Arzela theorem. Later, Zhou et al. [39] discussed the existence theorems related to the attractive solutions of the Hilfer FEEs with almost sectorial operators. Very recently, Yang et al. [40] established the HF stochastic evolution equations on infinite intervals via the fixed-point method.

    To our knowledge, no work has been reported on the attractive solution for HF neutral stochastic evolution integro-differential equations on an infinite interval via almost sectorial operators. To fill this gap, by taking inspiration from the previous studies, this research intends to address this subject completely. In other words, the goal of this publication is to prove an attractive solution using the almost sectorial operators in the following form for HF neutral stochastic evolution integro-differential equations on an infinite interval:

    {HDλ,μ0+[g(s)ϖ(s,g(s))]=A[g(s)ϖ(s,g(s))]+F(s,g(s))+s0G(l,g(l))dW(l),I(1λ)(1μ)0+g(0)=g0,s(0,), (1.1)

    where HDλ,μ0+ is the HFD of order 0<μ<1 and type 0λ1, I(1λ)(1μ)0+ is a R-L integral of the fractional order (1λ)(1μ), and A denotes an almost sectorial operator in the Hilbert space Y. F:(0,)×YY, G:[0,)×YL02(K,Y), and ϖ:(0,)×YY are the given functions. {W(s)}s0 specifies a one-dimensional K-valued Wiener process along with a finite trace nuclear covariance operator Q0 formulated on a filtered complete probability space (Ξ,E,{Es}s0,P), and g0L02(Ξ,Y).

    The following is a summary of this article's primary contributions:

    (1) In this work, we investigate the attractive solution for HF neutral stochastic evolution integro-differential equations on an infinite interval via almost sectorial operators.

    (2) This work applies some concepts of functional analysis, like the Wright function, the Ascoli-Arzela theorem, Kuratowski's measure of noncompactness, and Schauder's fixed point theorem, to prove the main results.

    (3) The Ascoli-Arzela theorem, which is effectively employed to establish the new results, is the foundation of our method in the present research.

    (4) The proved theorems are validated via a theoretical example.

    The structure of this manuscript is as follows: Section 2 covers fractional calculus, MNC, and semigroup operators as a reminder. In Section 3, we establish the global existence and attractivity results of mild solutions for HF neutral stochastic evolution integro-differential equation (1.1). We present conceptual applications in Section 4 to assist us in making our discussion more successful.

    We present a few foundational definitions in this section. We require certain fundamental notations of fractional calculus and measures of noncompactness as a reminder.

    Denote by L2(Ξ,Y), the collection of all strongly measurable square-integrable Y-valued random variables, which is a Banach space for the norm g()L2(Ξ,Y)=(Eg(,W)2)12 for each gL2(Ξ,Y). Moreover, L02(Ξ,Y)={gL2(Ξ,Y): g is an subspace of L2(Ξ,Y) and is E0-measurable}.

    Let C((0,),L2(Ξ,Y)):(0,)L2(Ξ,Y) be a Banach space of all continuous functions. For each gC((0,),L2(Ξ,Y)), define

    gC((0,),L2(Ξ,Y))=(sups(0,)Eg(s)2)12<.

    Suppose that (Ξ,E,P) denotes the complete probability space defined with a complete family of right continuous increasing sub-σ-algebras {Es,s(0,)} fulfilling EsE, so that Y,K denote two real separable Hilbert spaces, and {W(s)}s0 denotes a Q-Wiener process defined on (Ξ,E,P) with values in K. Let L(K,Y):KY be the space of all operators with boundedness property, and LQ(K,Y):KY stands for the space of all Q-Hilbert-Schmidt operators.

    Furthermore, we suppose that O(s) is continuous in the uniform operator topology for s>0, and also, O(s) has uniform boundedness, i.e., there exists K>1 such that sups(0,)O(s)<K, throughout this paper.

    Definition 2.1. [31] For 0<κ<1,0<φ<π2, we define that Ψκφ is a family of all closed linear operators with the sector Sφ={vC{0}:|arg v|φ} and let A:D(A)YY be such that

    (a)σ(A)Sφ;

    (b) for all ω<λ<π, there exists a constant Rλ>0 such that (vIA)1Rλ|v|κ.

    Then, AΨκφ is called an almost sectorial operator on Y.

    Define the semigroup operator {T(s)}s0 as

    T(s)=esv(A)=12πiΓϱesvR(v;A)dv,sS0π2φ,

    where Γϱ={R+eiϱ}{R+eiϱ} with φ<ϱ<δ<π2|args| is oriented counter-clockwise.

    Proposition 2.2. [31] Let T(s) be the compact semigroup and AΨκφ for 0<κ<1 and 0<φ<π2. Then, we have the following:

    (1) T(s+ν)=T(s)T(ν), for all ν,sSπ2φ.

    (2) T(s)L(Y)K0sκ1, s>0 (K0>0 is a constant).

    (3) R(T(s)) belongs to T(s) for sSπ2φD(A), where R(T) is the range of T. Also, R(T(s))D(Aθ), for any θC with Re(θ)>0, and

    AθT(s)g=12πiΓμvθesvR(v;A)gdv, for all gY.

    Hence, there exists a constant C=C(γ,θ)>0 such that

    AθT(s)L(Y)CsγRe(θ)1, for all s>0.

    (4) If ΣT={gY:lims0+T(s)g=g}, then D(Aθ)ΣTfor θ>1+κ.

    (5) (vIA)1=0evνT(ν)dν, vC, and Re(v)>0.

    Definition 2.3. [41] The fractional integral of order μ for the function G:[0,)R is defined as

    Iμ0+G(s)=1Γ(μ)s0G(l)(sl)1μdl,s>0;μ>0,

    provided the R.H.S. is point-wise convergent.

    Definition 2.4. [11] Let 0<μ<1 and 0λ1. The HFD of order μ and type λ for G:[0,)R is

    HDλ,μ0+G(s)=[Iλ(1μ)0+D(I(1λ)(1μ)0+G)](s).

    For a Banach space Y, let P be a non-empty subset in Y. The Kuratowski's MNC α is introduced as

    α(P)=inf{c>0:Pnı=1Mı,  diam(Mı)c}.

    Here, the diameter of Mı is provided by diam(Mı)=sup{|xy|: x,yMı}, ı=1,2,,n.

    Lemma 2.5. [42] Let V1 and V2 be two bounded sets in the Banach space E. Then, we have the follwoing

    (i) α(V1)=0 if and only if V1 is relatively compact;

    (ii) α(V1)α(V2) if V1V2;

    (iii) α(V1+V2)α(V1)+α(V2), where V1+V2={g+v:gV1,vV2};

    (iv) α{{g}V}=α(V) for all gE and every non-empty subset VE;

    (v) α{V1V2}max{α(V1),α(V2)};

    (vi) α(γV)|γ|α(V).

    Lemma 2.6. [43] Assume that Y is a Hilbert space, and the sequence gn(s):[0,)Y, (n=1,2,) includes all continuous functions. If there exists ϱL1[0,) such that

    xn(s)ϱ(s),s[0,), n=1,2,,

    then α({xn}n=1) is integrable on [0,), and

    α({0xn(s)ds:n=1,2,})20α({xn(s):n=1,2,})ds.

    Definition 2.7. [44] The Wright function Mλ(ϑ) is formulated as

    Mλ(ϑ)=nN(ϑ)n1(n1)!Γ(1ϑn), ϑC,

    with

    0ϑιMλ(ϑ)dϑ=Γ(1+ι)Γ(1+λι),for ι0.

    Lemma 2.8. The system (1.1) has a solution in the form of the integral equation

    g(s)=[g0ϖ(0,g(0))]Γ(λ(1μ)+μ)s(λ1)(1μ)+ϖ(s,g(s))+1Γ(μ)s0(sl)μ1Ag(l)dl+1Γ(μ)s0(sl)μ1F(l,g(l))dl+1Γ(μ)s0(sl)μ1l0G(ω,g(ω))dW(ω)dl, s(0,). (2.1)

    Proof. This proof is similar to that of [14]; therefore, we do not repeat it.

    Lemma 2.9. Suppose that g(s) fulfills the integral equation (2.1). Then,

    g(s)=Oλ,μ[g0ϖ(0,g(0))]+ϖ(s,g(s))+s0Pμ(sl)F(l,g(l))dl+s0Pμ(sl)l0G(ω,g(ω))dW(ω)dl,s(0,),

    where Oλ,μ=Iλ(1μ)0+Pμ(s), Pμ(s)=sμ1Qμ(s), and Qμ(s)=0μϑMμ(ϑ)T(sμϑ)dϑ.

    Proof. This proof is similar to that of [14]; therefore, we do not repeat it.

    In relation to Lemma 2.8, we have a definition.

    Definition 2.10. An Es-adapted stochastic process g(s):(0,)Y is called a mild solution of the given system (1.1), if I(1λ)(1μ)0+g(0)=g0, g0L02(Ξ,Y), and for each s(0,), the function G(ω,g(ω)) is integrable, and the stochastic integral equation

    g(s)=Oλ,μ[g0ϖ(0,g(0))]+ϖ(s,g(s))+s0Pμ(sl)F(l,g(l))dl+s0Pμ(sl)l0G(ω,g(ω))dW(ω)dl,s(0,),

    holds.

    Definition 2.11. The mild solution g(s) of the system (1.1) is said to be attractive if g(s)0 as s.

    Lemma 2.12. [18] For any fixed s>0, {Qμ(s)}s>0, {Pμ(s)}s>0, and {Oλ,μ(s)}s>0 are linear operators, and for every gY,

    Qμ(s)gK1sμ(κ1)g, Pμ(s)gK1s1+μκg, and Oλ,μ(s)gK2s1+λλμ+μκg,

    where

    K1=μK0Γ(1+κ)Γ(1+μκ) and K2=K1Γ(μκ)Γ(λ(1μ)+μκ).

    Lemma 2.13. [18] Assume that O(s) is equicontinuous for s>0. Then, {Qμ(s)}s>0, {Pμ(s)}s>0 and {Oλ,μ(s)}s>0 are strongly continuous, i.e., for any gY and s>s>0, we have

    Qμ(s)gQμ(s)g0, Pμ(s)gPμ(s)g0, and Oλ,μ(s)gOλ,μ(s)g0,

    as ss.

    Let

    C([0,),L2(Ξ,Y))={x:xC([0,),L2(Ξ,Y)):limsEx(s)1+s2=0}.

    Clearly, (C([0,),L2(Ξ,Y)),) is a Banach space with

    x=(sups[0,)Ex(s)1+s2)12<,for any xC([0,),(Ξ,Y)).

    We provide the generalized Ascoli-Arzela theorem below.

    Lemma 2.14. [45] The set ΥC([0,),L2(Ξ,Y)) is relatively compact iff:

    (i) for any f>0, the set I={u:u(s)=y(s)1+s, yΥ} is equicontinuous on [0,f];

    (ii) limsEy(s)1+s2=0 uniformly for yΥ;

    (iii) for all s[0,), I(s)={u:u(s)=y(s)1+s, yΥ} is relatively compact in L2(Ξ,Y).

    Now, the main theorems will be proved in this section. Some assumptions are required to prove these theorems. We list them as follows:

    (H1) For any gY, F(,g) is measurable on (0,), and for any s(0,), F(s,) is continuous.

    (H2) There exists a function p:(0,)(0,) such that for all gY and all s(0,),

    (Iμ0+p)(s)C((0,),(0,)),EF(s,g)2p(s),

    and

    lims0s2(1λ+λμμκ)+μ(Iμ0+p)(s)=0,limss2(1λ+λμμκ)+μ(1+s2)(Iμ0+p)(s)=0.

    (H3) For every gY, G(,g) is Es-measurable on (0,), and for all s(0,), G(s,) is continuous.

    (H4) There exists a function q:(0,)(0,) such that for all gY and all s(0,),

    (I2μ10+q)(s)C((0,),(0,)),Es0G(l,g(l))dl2q(s),

    and

    lims0s2(1λ+λμμκ)(I2μ10+q)(s)=0,limss2(1λ+λμμκ)(1+s2)(I2μ10+q)(s)=0.

    (H5) ϖ:(0,)×YY is a continuous function, and there exists Kϖ>0 such that ϖ is a Y-valued function and satisfies

    Eϖ(s,g(s))2Kϖs1λ+λμμκ(1+g2), gY, s(0,).

    Define Cμ((0,),L2(Ξ,Y))={gC((0,),L2(Ξ,Y)):lims0+s(1λ)(1μ)g(s) exists and is finite, limsEs(1λ)(1μ)g(s)(1+s)2=0}, equipped with norm

    g(s)2μ=(sups[0,)Es1λ+λμμκg(s)1+s2)12.

    Thus, (Cμ((0,),L2(Ξ,Y)),2μ) is a Hilbert space. For each gCμ((0,),L2(Ξ,Y)) and for any s(0,), define the operator Σ by

    (Σg)(s)=(Σ1g)(s)+(Σ2g)(s),

    where

    (Σ1g)(s)=Oλ,μ[g0ϖ(0,g(0))]+ϖ(s,g(s)),(Σ2g)(s)=s0Pμ(sl)F(l,g(l))dl+s0Pμ(sl)l0G(ω,g(ω))dW(ω)dl.

    Clearly, the neutral stochastic HF-system (1.1) has a mild solution gCμ((0,),L2(Ξ,Y)) if and only if Σ has a fixed-point gCμ((0,),L2(Ξ,Y)).

    For each xCμ((0,),L2(Ξ,Y)), we set

    g(s)=s1λ+λμμκx(s),s(0,).

    Clearly, gCμ((0,),L2(Ξ,Y)).

    We now define the operator by

    (x)(s)=(1x)(s)+(2x)(s),

    where

    (1x)(s)={s1λ+λμμκ(Σ1g)(s),for s(0,),0,s=0,

    and

    (2x)(s)={s1λ+λμμκ(Σ2g)(s),for s(0,),0,s=0.

    By using (H2) and (H4), we claim that there exists r>0 such that the inequality

    sups(0,){8K22(1+s)2[Eg02+K2ϖ(1+g02)]+4K2ϖ(1+s)2s2(1λ+λμμκ)(1+g2)+4K21μκ(1+s)2s2(1λ+λμμκ)+μκs0(sl)μκ1p(l)dl+4Tr(Q)K21s2(1λ+λμμκ)(1+s)2s0(sl)2(μκ1)q(l)dl}r

    holds.

    Let g(s)=s1λ+λμμκx(s). Define

    Φ1={x:xC([0,),L2(Ξ,Y)), Ex2r},ˆΦ1={g:gCμ((0,),L2(Ξ,Y)), Eg2r}.

    It is clear that Φ1 is a non-empty, closed, and convex subset of C([0,),L2(Ξ,Y)). ˆΦ1 is a closed, convex and non-empty set of Cμ((0,),L2(Ξ,Y), and gˆΦ1 whenever xΦ1.

    Let

    D:={z:z(s)=(x)(s)1+s, xΦ1}.

    We must establish the next lemmas in order to establish the main theorems of this paper.

    Lemma 3.1. If (H1)(H5) are satisfied, then, D is equicontinuous.

    Proof. We follow some steps.

    Step 1: We prove D1:={z:z(s)=(1x)(s)1+s, xΦ1} is equicontinuous.

    We have,

    s1λ+λμμκOλ,μ(s)[g0ϖ(0,g(0))]+ϖ(s,g(s))=s1λ+λμμκΓ(λ(1μ))s0(sl)λ(1μ)1lμ1Qμ(l)[g0ϖ(0,g(0))]dl+ϖ(s,g(s))=10(1v)λ(1μ)1vμ1sμ(1κ)Qμ(sv)[g0ϖ(0,g(0))]dv+ϖ(s,g(s)).

    Noting that lims0+sμ(1κ)Qμ(sv)[g0ϖ(0,g(0))]+ϖ(s,g(s)) and 10(1v)λ(1μ)1vμ1dv are finite, we have

    lims0+s1λ+λμμκOλ,μ(s)[g0ϖ(0,g(0))]+ϖ(s,g(s))=0.

    Thus, from the aforesaid equality, when s1=0,s2(0,), it follows that

    E(1x)(s2)1+s2(1x)(0)2E11+s2s1λ+λμμκ2Oλ,μ(s2)[g0ϖ(0,g(0))]+ϖ(s,g(s))020,

    as s20.

    Furthermore, for any 0<s1<s2<, using the elementary inequality, we get

    E(1x)(s2)1+s2(1x)(s1)1+s12Es1λ+λμμκ2Oλ,μ(s2)[g0ϖ(0,g(0))]+ϖ(s,g(s))1+s2s1λ+λμμκ1Oλ,μ(s1)[g0ϖ(0,g(0))]+ϖ(s,g(s))1+s122Es1λ+λμμκ2Oλ,μ(s2)[g0ϖ(0,g(0))]+ϖ(s,g(s))1+s2s1λ+λμμκ2Oλ,μ(s2)[g0ϖ(0,g(0))]+ϖ(s,g(s))1+s12+2Es1λ+λμμκ2Oλ,μ(s2)[g0ϖ(0,g(0))]+ϖ(s,g(s))1+s1s1λ+λμμκ2Oλ,μ(s2)[g0ϖ(0,g(0))]+ϖ(s,g(s))1+s122Es1λ+λμμκ1Oλ,μ(s1)[g0ϖ(0,g(0))]+ϖ(s,g(s))2(s2s1(1+s2)(1+s1))2+2Es1λ+λμμκ2Oλ,μ(s2)[g0ϖ(0,g(0))]+ϖ(s,g(s))s1λ+λμμκ1Oλ,μ(s1)[g0ϖ(0,g(0))]+ϖ(s,g(s))2(11+s1)22Es1λ+λμμκ2Oλ,μ(s2)[g0ϖ(0,g(0))]+ϖ(s,g(s))2(s2s1(1+s2)(1+s1))2+4Es1λ+λμμκ2[Oλ,μ(s2)[g0ϖ(0,g(0))]+ϖ(s,g(s))Oλ,μ(s1)[g0ϖ(0,g(0))]+ϖ(s,g(s))]2(s2s1(1+s2)(1+s1))2+4E[s1λ+λμμκ2s1λ+λμμκ1]Oλ,μ(s2)[g0ϖ(0,g(0))]+ϖ(s,g(s))2(s2s1(1+s2)(1+s1))20, as s2s1.

    Thus, D1:={z:z(s)=(1x)(s)1+s, xΦ1} is equicontinuous.

    Step 2: Next we prove that D2:={z:z(s)=(2x)(s)1+s, xΦ1} is equicontinuous.

    For every ϵ>0, one may write

    E(2x)(s2)1+s2(2x)(s1)1+s124Es1λ+λμμκ21+s2s20Pμ(s2l)F(l,g(l))dl2+4Es1λ+λμμκ21+s2s20Pμ(s2l)l0G(ω,g(ω))dW(ω)dl2+4Es1λ+λμμκ11+s1s10Pμ(s1l)F(l,g(l))dl2+4Es1λ+λμμκ11+s1s10Pμ(s1l)l0G(ω,g(ω))dW(ω)dl24(K1s1λ+λμμκ21+s2)2s20(s2l)2(μκ1)p(l)dl+4Tr(Q)(K1s1λ+λμμκ21+s2)2s20(s2l)2(μκ1)q(l)dl+4(K1s1λ+λμμκ11+s1)2s10(s1l)2(μκ1)p(l)dl+4Tr(Q)(K1s1λ+λμμκ11+s1)2s10(s1l)2(μκ1)q(l)dl<ϵ.

    When s1=0, 0<s2T, by using the hypotheses (H2) and (H4), we have

    E(2x)(s2)1+s2(2x)(0)22Es1λ+λμμκ21+s2s20Pμ(s2l)F(l,g(l))dl2+2Es1λ+λμμκ21+s2s20Pμ(s2l)l0G(ω,g(ω))dW(ω)dl24(K1s1λ+λμμκ21+s2)2s20(s2l)2(μκ1)p(l)dl+4Tr(Q)(K1s1λ+λμμκ21+s2)2s20(s2l)2(μκ1)q(l)dl0, as s20.

    When 0<s1<s2T, we obtain

    E(2x)(s2)1+s2(2x)(s1)1+s128Es1λ+λμμκ11+s1s2s1(s2l)μ1Qμ(s2l)F(l,g(l))dl2+8Es1λ+λμμκ11+s1s10[(s2l)μ1(s1l)μ1]Qμ(s2l)F(l,g(l))dl2+8Es1λ+λμμκ11+s1s10(s1l)μ1[Qμ(s2l)Qμ(s1l)]F(l,g(l))dl2+8E[s1λ+λμμκ21+s2s1λ+λμμκ11+s1]s20(s2l)μ1Qμ(s2l)F(l,g(l))dl2+8Es1λ+λμμκ11+s1s2s1(s2l)μ1Qμ(s2l)l0G(ω,g(ω))dW(ω)dl2+8Es1λ+λμμκ11+s1s10[(s2l)μ1(s1l)μ1]Qμ(s2l)l0G(ω,g(ω))dW(ω)dl2+8Es1λ+λμμκ11+s1s10(s1l)μ1[Qμ(s2l)Qμ(s1l)]l0G(ω,g(ω))dW(ω)dl2+8E[s1λ+λμμκ21+s2s1λ+λμμκ11+s1]s20(s2l)μ1Qμ(s2l)l0G(ω,g(ω))dW(ω)dl288j=1Sj,

    where

    S1=K21(s1λ+λμμκ11+s1)2s2s1(s2l)2(μκ1)p(l)dl,S2=K21(s1λ+λμμκ11+s1)2s20(s2l)μ1(s1l)μ12(s2l)2μ(κ1)p(l)dl,S3=(s1λ+λμμκ11+s1)2s10(s1l)μ1Qμ(s2l)Qμ(s1l)2EF(l,g(l))2dl,S4=K21[s1λ+λμμκ21+s2s1λ+λμμκ11+s1]2s20(s2l)2(μκ1)p(l)dl,S5=Tr(Q)K21(s1λ+λμμκ11+s1)2s2s1(s2l)2(μκ1)q(l)dl,S6=Tr(Q)K21(s1λ+λμμκ11+s1)2s20(s2l)μ1(s1l)μ12(s2l)2μ(κ1)q(l)dl,S7=Tr(Q)(s1λ+λμμκ11+s1)2s10(s1l)μ1Qμ(s2l)Qμ(s1l)2El0G(l,g(l))dω2dl,S8=Tr(Q)K21[s1λ+λμμκ21+s2s1λ+λμμκ11+s1]2s20(s2l)2(μκ1)q(l)dl.

    By a straightforward calculation, we obtain

    S10 as s2s1.

    Since, (s2l)μ1(s1l)μ12(s2l)2μ(κ1)(s2l)2(μκ1), by using the Lebesgue dominated convergence theorem (LDCT), we obtain

    \int_0^{\mathfrak{s}_2}\|(\mathfrak{s}_2-\mathfrak{l})^{\mu-1}-(\mathfrak{s}_1-\mathfrak{l})^{\mu-1}\|^2\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\rightarrow 0\ \text{as}\ \mathfrak{s}_2\rightarrow \mathfrak{s}_1.

    Thus, S_2\rightarrow 0 as \mathfrak{s}_2\rightarrow \mathfrak{s}_1 .

    By (H_2) , for \epsilon > 0 , we have

    \begin{align*} S_3&\leq \bigg(\frac{\mathfrak{s}_1^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}_1}\bigg)^2\int_{0}^{\mathfrak{s}_1-\epsilon}(\mathfrak{s}_1-\mathfrak{l})^{\mu-1}\|\mathscr{Q}_{\mu}(\mathfrak{s}_2-\mathfrak{l})-\mathscr{Q}_{\mu}(\mathfrak{s}_1-\mathfrak{l})\|^2E\|\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))\|^2d\mathfrak{l}\\[0.3cm] & \quad +\bigg(\frac{\mathfrak{s}_1^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}_1}\bigg)^2\frac{\epsilon^{\mu}}{\mu}\int_{\mathfrak{s}_1-\epsilon}^{\mathfrak{s}_1}(\mathfrak{s}_1-\mathfrak{l})^{\mu-1}\|\mathscr{Q}_{\mu}(\mathfrak{s}_2-\mathfrak{l})-\mathscr{Q}_{\mu}(\mathfrak{s}_1-\mathfrak{l})\|^2E\|\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))\|^2d\mathfrak{l}\\[0.3cm] &\leq \bigg(\frac{\mathfrak{s}_1^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}_1}\bigg)^2\frac{\mathfrak{s}_1^{\mu}-\epsilon^{\mu}}{\mu}\int_{0}^{\mathfrak{s}_1-\epsilon}(\mathfrak{s}_1-\mathfrak{l})^{\mu-1}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\sup\limits_{\mathfrak{l}\in [0,\mathfrak{s}_1-\epsilon]}\|\mathscr{Q}_{\mu}(\mathfrak{s}_2-\mathfrak{l})-\mathscr{Q}_{\mu}(\mathfrak{s}_1-\mathfrak{l})\|^2\\[0.3cm] & \quad +2\mathcal{K}_1\bigg(\frac{\mathfrak{s}_1^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}_1}\bigg)^2\frac{\epsilon^{\mu}}{\mu}\int_{\mathfrak{s}_1-\epsilon}^{\mathfrak{s}_1}(\mathfrak{s}_1-\mathfrak{l})^{\mu\kappa-1}\mathfrak{p}(\mathfrak{l})d\mathfrak{l},\\[0.3cm] &\leq S_{31}+S_{32}+S_{33}, \end{align*}

    where

    \begin{align*} S_{31}& = \bigg(\frac{\mathfrak{s}_1^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}_1}\bigg)^2\frac{\mathfrak{s}_1^{\mu}-\epsilon^{\mu}}{\mu}\int_{0}^{\mathfrak{s}_1-\epsilon}(\mathfrak{s}_1-\mathfrak{l})^{\mu-1}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\sup\limits_{\mathfrak{l}\in [0,\mathfrak{s}_1-\epsilon]}\|\mathscr{Q}_{\mu}(\mathfrak{s}_2-\mathfrak{l})-\mathscr{Q}_{\mu}(\mathfrak{s}_1-\mathfrak{l})\|^2\\[0.3cm] S_{32}& = 2\mathcal{K}_1\bigg(\frac{\mathfrak{s}_1^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}_1}\bigg)^2\frac{\epsilon^{\mu}}{\mu}\bigg\|\int_0^{\mathfrak{s}_1}(\mathfrak{s}_1-\mathfrak{l})^{\mu\kappa-1}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}-\int_0^{\mathfrak{s}_1-\epsilon}(\mathfrak{s}_1-\epsilon-\mathfrak{l})^{\mu\kappa-1}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\bigg\|,\\[0.3cm] S_{33}& = 2\mathcal{K}_1\bigg(\frac{\mathfrak{s}_1^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}_1}\bigg)^2\frac{\epsilon^{\mu}}{\mu}\int_0^{\mathfrak{s}_1-\epsilon}\|(\mathfrak{s}_1-\epsilon-\mathfrak{l})^{\mu\kappa-1}-(\mathfrak{s}_1-\mathfrak{l})^{\mu\kappa-1}\|\mathfrak{p}(\mathfrak{l})d\mathfrak{l}. \end{align*}

    From Lemma 2.13, we conclude that S_{31}\rightarrow 0 as \mathfrak{s}_2\rightarrow \mathfrak{s}_1 . Using the corresponding deductions in relation to the proofs of S_1, S_2\rightarrow 0 , we obtain S_{32}\rightarrow 0 and S_{33}\rightarrow 0 as \epsilon\rightarrow 0 . Hence, S_3\rightarrow 0 as \mathfrak{s}_2\rightarrow \mathfrak{s}_1 . We can also derive that S_4\rightarrow 0 as \mathfrak{s}_2\rightarrow \mathfrak{s}_1 by the continuity of \bigg(\frac{\mathfrak{s}_1^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}_1}\bigg)^2 with respect to \mathfrak{s} . For the terms S_5, \cdots, S_8 , we can show that S_5, \cdots, S_8\rightarrow 0 as \mathfrak{s}_2\rightarrow \mathfrak{s}_1 by the similar proofs of S_1, \cdots, S_4\rightarrow 0 as \mathfrak{s}_2\rightarrow \mathfrak{s}_1 , respectively.

    Let 0\leq \mathfrak{s}_1 < T < \mathfrak{s}_2 . When \mathfrak{s}_2\rightarrow \mathfrak{s}_1 , then \mathfrak{s}_2\rightarrow T and \mathfrak{s}_1\rightarrow T hold, simultaneously. So, for any \mathsf{x}\in \Phi_1 ,

    \begin{align*} E\bigg\|\frac{(\mho_2\mathsf{x})(\mathfrak{s}_2)}{1+\mathfrak{s}_2}-\frac{(\mho_2\mathsf{x})(\mathfrak{s}_1)}{1+\mathfrak{s}_1}\bigg\|^2\leq 2E\bigg\|\frac{(\mho_2\mathsf{x})(\mathfrak{s}_2)}{1+\mathfrak{s}_2}-\frac{(\mho_2\mathsf{x})(T)}{1+T}\bigg\|^2+E\bigg\|\frac{(\mho_2\mathsf{x})(T)}{1+T}-\frac{(\mho_2\mathsf{x})(\mathfrak{s}_1)}{1+\mathfrak{s}_1}\bigg\|^2, \end{align*}

    holds. So we have,

    \begin{align*} E\bigg\|\frac{(\mho_2\mathsf{x})(\mathfrak{s}_2)}{1+\mathfrak{s}_2}-\frac{(\mho_2\mathsf{x})(\mathfrak{s}_1)}{1+\mathfrak{s}_1}\bigg\|^2\rightarrow 0,\ \text{as}\ \mathfrak{s}_2\rightarrow \mathfrak{s}_1. \end{align*}

    Hence, \mathcal{D}_2: = \bigg\{\mathrm{z}:\mathrm{z}(\mathfrak{s}) = \frac{(\mho_2\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}, \ \mathsf{x}\in \Phi_1\bigg\} is equicontinuous. As a consequence, \mathcal{D} = \mathcal{D}_1+\mathcal{D}_2 is equicontinuous. Hence, the proof is ended.

    Lemma 3.2. If (H_1) (H_5) are satisfied, then, for all \mathsf{x}\in \Phi_1 , \lim\limits_{\mathfrak{s}\rightarrow \infty}E\bigg\|\dfrac{(\mho\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}\bigg\|^2 = 0 uniformly.

    Proof. Indeed, for any \mathsf{x}\in \Phi_1 , by using Lemma 2.12 and the assumptions (H_2) , (H_4) , and (H_5) , we obtain

    \begin{align*} E\|(\mho\mathsf{x})(\mathfrak{s})\|^2&\leq 4E\|\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}\mathscr{O}_{\lambda,\mu}[\mathfrak{g}_0-\varpi(0,\mathfrak{g}(0))]\|^2+4E\|\mathfrak{s}^{(1-\lambda)(1-\mu)}\varpi(\mathfrak{s},\mathfrak{g}(\mathfrak{s}))\|^2\nonumber\\[0.3cm] & \quad+4E\|\mathfrak{s}^{(1-\lambda)(1-\mu)}\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))d\mathfrak{l}\|^2\nonumber\\[0.3cm] & \quad+4E\|\mathfrak{s}^{(1-\lambda)(1-\mu)}\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))dW(\omega)d\mathfrak{l}\|^2\\[0.3cm] & \leq 8\mathcal{K}_2^2[E\|\mathfrak{g}_0\|^2+\mathcal{K}_{\varpi}^2(1+\|\mathfrak{g}_0\|^2)]+4\mathcal{K}_\varpi^2\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}(1+\|\mathfrak{g}\|^2)\\[0.3cm] & \quad +\frac{4\mathcal{K}_1^2}{\mu\kappa}\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)+\mu\kappa}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}\mathfrak{p}(\mathfrak{s})d\mathfrak{l}\\[0.3cm] & \quad +4Tr(Q)\mathcal{K}_1^2\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}\mathfrak{q}(\mathfrak{s})d\mathfrak{l}. \end{align*}

    Dividing both sides of the above inequalities by (1+\mathfrak{s})^2 , we obtain

    \begin{align} E\bigg\|\frac{(\mho\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}\bigg\|^2& \leq \frac{8\mathcal{K}_2^2}{(1+\mathfrak{s})^2}[E\|\mathfrak{g}_0\|^2+\mathcal{K}_{\varpi}^2(1+\|\mathfrak{g}_0\|^2)]+\frac{4\mathcal{K}_\varpi^2}{(1+\mathfrak{s})^2}\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}(1+\|\mathfrak{g}\|^2)\\[0.3cm] & \quad +\frac{4\mathcal{K}_1^2}{\mu\kappa(1+\mathfrak{s})^2}\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)+\mu\kappa}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\\[0.3cm] & \quad +4Tr(Q)\mathcal{K}_1^2\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}\mathfrak{q}(\mathfrak{l})d\mathfrak{l}\rightarrow 0,\ \text{as}\ \mathfrak{s}\rightarrow \infty, \end{align} (3.1)

    which proves that for any \mathsf{x}\in \Phi_1 , \lim\limits_{\mathfrak{s}\rightarrow \infty}E\bigg\|\frac{(\mho\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}\bigg\|^2 = 0 holds uniformly.

    Lemma 3.3. If (H_1) (H_5) are satisfied, then \mho\Phi_1\subset \Phi_1 .

    Proof. For the case \mathfrak{s} > 0 , by Eq (3.1), we have

    \begin{align*} E\bigg\|\frac{(\mho\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}\bigg\|^2& \leq \frac{8\mathcal{K}_2^2}{(1+\mathfrak{s})^2}[E\|\mathfrak{g}_0\|^2+\mathcal{K}_{\varpi}^2(1+\|\mathfrak{g}_0\|^2)]+\frac{4\mathcal{K}_\varpi^2}{(1+\mathfrak{s})^2}\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}(1+\|\mathfrak{g}\|^2)\\[0.3cm] & \quad +\frac{4\mathcal{K}_1^2}{\mu\kappa(1+\mathfrak{s})^2}\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)+\mu\kappa}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}\mathfrak{p}(\mathfrak{s})d\mathfrak{l}\\[0.3cm] & \quad +4Tr(Q)\mathcal{K}_1^2\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}\mathfrak{q}(\mathfrak{s})d\mathfrak{l}\leq \mathfrak{r}. \end{align*}

    For the case \mathfrak{s} = 0 , we have

    \begin{align*} E\bigg\|\frac{(\mho\mathsf{x})(0)}{1+0}\bigg\|^2 = E\|(\mho\mathsf{x})(0)\|^2\leq 8\mathcal{K}_2^2[E\|\mathfrak{g}_0\|^2+\mathcal{K}_{\varpi}^2(1+\|\mathfrak{g}_0\|^2)]\leq \mathfrak{r}. \end{align*}

    As a consequence, \mho\Phi_1\subset \Phi_1 .

    Lemma 3.4. If (H_1) (H_5) are satisfied, then \mho is continuous.

    Proof. Let the sequence \{\mathsf{x}_m\}_{m = 1}^{\infty} be in \Phi_1 and convergent to \mathsf{x}\in \Phi_1 . In this case, it follows that \lim\limits_{m\rightarrow \infty}E\|\mathsf{x}_m(\mathfrak{s})\|^2 = E\|\mathsf{x}(\mathfrak{s})\|^2 and \lim\limits_{m\rightarrow \infty}E\|\mathfrak{s}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathsf{x}_m(\mathfrak{s})\|^2 = E\|\mathfrak{s}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathsf{x}(\mathfrak{s})\|^2 , for \mathfrak{s}\in (0, \infty) .

    We assume \mathfrak{g}(\mathfrak{s}) = \mathfrak{s}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathsf{x}(\mathfrak{s}), \ \mathfrak{g}_m(\mathfrak{s}) = \mathfrak{s}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathsf{x}_m(\mathfrak{s}), \mathfrak{s}\in(0, \infty) . Then, clearly \mathfrak{g}, \mathfrak{g}_m\in \Phi_1 . According to (H_1) and (H_3) , we get \lim\limits_{m\rightarrow \infty} E\|\mathcal{F}(\mathfrak{s}, \mathfrak{g}_m(\mathfrak{s}))\|^2 = E\|\mathcal{F}(\mathfrak{s}, \mathfrak{s}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathfrak{g}_m(\mathfrak{s}))\|^2 = E\|\mathcal{F}(\mathfrak{s}, \mathfrak{s}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathfrak{g}(\mathfrak{s}))\|^2 = E\|\mathcal{F}(\mathfrak{s}, \mathfrak{g}_m(\mathfrak{s}))\|^2 and \lim\limits_{m\rightarrow \infty} E\|\mathit{G}(\mathfrak{s}, \mathfrak{g}_m(\mathfrak{s}))\|^2 = E\|\mathit{G}(\mathfrak{s}, \mathfrak{s}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathfrak{g}_m(\mathfrak{s}))\|^2 = E\|\mathit{G}(\mathfrak{s}, \mathfrak{s}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathfrak{g}(\mathfrak{s}))\|^2 = E\|\mathit{G} (\mathfrak{s}, \mathfrak{g}_m(\mathfrak{s}))\|^2 .

    From (H_2) , for all \mathfrak{s}\in (0, \infty) , we obtain

    \begin{align*} (\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}E\|\mathcal{F}(\mathfrak{l},\mathfrak{g}_m(\mathfrak{l}))-\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))\|^2\leq 2(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}\mathfrak{p}(\mathfrak{l}),\ \text{a.e. in}\ [0,\mathfrak{s}). \end{align*}

    Moreover, since 2(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}\mathfrak{p}(\mathfrak{l}) is integrable for \mathfrak{l} \in [0, \mathfrak{s}) and \mathfrak{s}\in [0, \infty) , the LDCT enables us to claim that

    \begin{equation*} \int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}E\|\mathcal{F}(\mathfrak{l},\mathfrak{g}_m(\mathfrak{l}))-\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))\|^2d\mathfrak{l}\rightarrow 0\ \text{as}\ m\rightarrow \infty. \end{equation*}

    Identically, by using (H_4) and LDCT, we obtain

    \begin{equation*} \int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}E\|[\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}_m(\omega))dW(\omega)-\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))dW(\omega)]\|^2d\mathfrak{l}\rightarrow 0\ \text{as}\ m\rightarrow \infty. \end{equation*}

    Thus, for \mathfrak{s}\in [0, \infty) , we have

    \begin{align*} &\quad E\bigg\|\frac{(\mho\mathsf{x}_m)(\mathfrak{s})}{1+\mathfrak{s}}-\frac{(\mho\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}\bigg\|^2\\[0.3cm] & \leq 2\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}E\bigg\|\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})[\mathcal{F}(\mathfrak{l},\mathfrak{g}_m(\mathfrak{l}))-\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))]d\mathfrak{l}\bigg\|^2\\[0.3cm] & \quad+2\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}E\bigg\|\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\bigg[\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}_m(\omega))dW(\omega)-\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))dW(\omega)\bigg]d\mathfrak{l}\bigg\|^2\\[0.3cm] & \leq 2\mathcal{K}_1\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}d\mathfrak{l}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}E\|\mathcal{F}(\mathfrak{l},\mathfrak{g}_m(\mathfrak{l}))-\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))\|^2d\mathfrak{l}\\[0.3cm] & \quad +2\mathcal{K}_1Tr(Q)\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}E\|\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}_m(\omega))d\omega-\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))d\omega\|^2d\mathfrak{l}\\[0.3cm] & \rightarrow 0\ \text{as}\ m\rightarrow \infty. \end{align*}

    Hence, \|\mho\mathsf{x}_m-\mho\mathsf{x}\|\rightarrow 0 as m\rightarrow \infty ; i.e., \mho is continuous.

    We are now prepared to present and support our first theorem about the mild solutions of the neutral stochastic HF-system (1.1).

    Theorem 3.5. Assume that the semigroup operator \mathscr{O}(\mathfrak{s}) is compact, for every \mathfrak{s} > 0 . If (H_1) (H_5) are satisfied, then (i) there exist some mild solutions in \widehat{\Phi}_1 for the given neutral stochastic HF-system (1.1) ; (ii) all mild solutions of (1.1) are attractive.

    Proof. (ⅰ) According to the properties of \mho and \Sigma , we know that the neutral stochastic HF-system (1.1) possesses a mild solution \mathfrak{g}\in \widehat{\Phi}_1 if \mho has a fixed-point \mathsf{x}\in \Phi_1 , where \mathsf{x}(\mathfrak{s}) = \mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}\mathfrak{g}(\mathfrak{s}) . We have to prove that \mho has a fixed-point in \Phi_1 . In fact, from Lemmas 3.3 and 3.4, we already have that \mho maps \Phi_1 into itself and \mho is continuous on \Phi_1 . To demonstrate that \mho is completely continuous, we have to show that the set \mho\Phi_1 is relatively compact. According to Lemmas 3.1 and 3.2, the set \mathcal{D}: = \{\mathrm{z}:\mathrm{z}(\mathfrak{s}) = \dfrac{(\mho\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}, \ \mathsf{x}\in \Phi_1\} is equicontinuous, and for any \mathsf{x}\in \Phi_1, \ \lim\limits_{\mathfrak{s}\rightarrow \infty}E\|\dfrac{(\mho\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}\|^2 = 0 satisfies uniformly. From Lemma 2.14, for each \mathfrak{s}\in [0, \infty) , we prove \mathcal{D}: = \{\mathrm{z}:\mathrm{z}(\mathfrak{s}) = \dfrac{(\mho\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}, \ \mathsf{x}\in \Phi_1\} is relatively compact in L_2(\Xi, \mathscr{Y}) . It is obvious that \mathcal{D}(0) is relatively compact in L_2(\Xi, \mathscr{Y}) . Therefore, we just need to investigate the case \mathfrak{s}\in (0, \infty) . For any \epsilon\in (0, \mathfrak{s}) and \gamma > 0 , we consider \mho_{\epsilon, \gamma} on \Phi_1 in the form:

    \begin{align*} (\mho_{\epsilon,\gamma}\mathsf{x})(\mathfrak{s}):& = \mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}(\Sigma_{\epsilon,\gamma}\mathfrak{g})(\mathfrak{s})\\[0.3cm] & = \mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}\bigg\{\mathscr{O}_{\lambda,\mu}[\mathfrak{g}_0-\varpi(0,\mathfrak{g}(0))]+\varpi(\mathfrak{s},\mathfrak{g}(\mathfrak{s}))\\[0.3cm] & \quad+\int_0^{\mathfrak{s}-\epsilon}\int_0^{\infty}\mu\vartheta(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathscr{M}_{\mu}(\vartheta)\mathscr{T}((\mathfrak{s}-\mathfrak{l})^{\mu}\vartheta)\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))d\vartheta d\mathfrak{l}\\[0.3cm] & \quad+\int_0^{\mathfrak{s}-\epsilon}\int_0^{\infty}\mu\vartheta(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathscr{M}_{\mu}(\vartheta)\mathscr{T}((\mathfrak{s}-\mathfrak{l})^{\mu}\vartheta)\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))dW(\omega)d\vartheta d\mathfrak{l}\bigg\}. \end{align*}

    Thus,

    \begin{align*} \frac{(\mho_{\epsilon,\gamma}\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}& = \frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\bigg\{\mathscr{O}_{\lambda,\mu}[\mathfrak{g}_0-\varpi(0,\mathfrak{g}(0))]+\varpi(\mathfrak{s},\mathfrak{g}(\mathfrak{s}))\\[0.3cm] & \quad+\mathscr{T}(\epsilon^{\mu}\gamma)\int_0^{\mathfrak{s}-\epsilon}\int_0^{\infty}\mu\vartheta(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathscr{M}_{\mu}(\vartheta)\mathscr{T}((\mathfrak{s}-\mathfrak{l})^{\mu}\vartheta-\epsilon^{\mu}\gamma)\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))d\vartheta d\mathfrak{l}\\[0.3cm] & \quad+\mathscr{T}(\epsilon^{\mu}\gamma)\int_0^{\mathfrak{s}-\epsilon}\int_0^{\infty}\mu\vartheta(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathscr{M}_{\mu}(\vartheta)\mathscr{T}((\mathfrak{s}-\mathfrak{l})^{\mu}\vartheta-\epsilon^{\mu}\gamma)\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))dW(\omega)d\vartheta d\mathfrak{l}\bigg\}. \end{align*}

    Since the semigroup \mathscr{O}(\mathfrak{s}) is compact for any \mathfrak{s} > 0 , so \mathscr{O}_{\lambda, \mu}(\mathfrak{s}) is also compact. Furthermore, \mathscr{T}(\epsilon^{\mu}\gamma) is compact. Then for all \epsilon\in (0, \mathfrak{s}) and for any \gamma > 0 , the set \{\dfrac{(\mho_{\epsilon, \gamma}\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}, \ \mathsf{x}\in \Phi_1\} is relatively compact in L_2(\Xi, \mathscr{Y}) . From (H_2) and (H_4) and Lemma 2.12, for each \mathsf{x}\in \Phi_1 , we derive that

    \begin{align*} &\quad E\bigg\|\frac{(\mho\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}-\frac{(\mho_{\epsilon,\gamma}\mathsf{x})(\mathfrak{s})}{1+\mathfrak{s}}\bigg\|^2\\[0.3cm] & \leq 4E\bigg\|\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_0^{\mathfrak{s}}\int_0^{\gamma}\mu\vartheta(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathscr{M}_{\mu}(\vartheta)\mathscr{T}((\mathfrak{s}-\mathfrak{l})^{\mu}\vartheta)\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))d\vartheta d\mathfrak{l}\bigg\|^2\\[0.3cm] & \quad +4E\bigg\|\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_0^{\mathfrak{s}}\int_0^{\gamma}\mu\vartheta(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathscr{M}_{\mu}(\vartheta)\mathscr{T}((\mathfrak{s}-\mathfrak{l})^{\mu}\vartheta)\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))dW(\omega)d\vartheta d\mathfrak{l}\bigg\|^2\\[0.3cm] & \quad +4E\bigg\|\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_{\mathfrak{s}-\epsilon}^{\mathfrak{s}}\int_{\gamma}^{\infty}\mu\vartheta(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathscr{M}_{\mu}(\vartheta)\mathscr{T}((\mathfrak{s}-\mathfrak{l})^{\mu}\vartheta)\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))d\vartheta d\mathfrak{l}\bigg\|^2\\[0.3cm] & \quad +4E\bigg\|\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_{\mathfrak{s}-\epsilon}^{\mathfrak{s}}\int_{\gamma}^{\infty}\mu\vartheta(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathscr{M}_{\mu}(\vartheta)\mathscr{T}((\mathfrak{s}-\mathfrak{l})^{\mu}\vartheta)\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))dW(\omega)d\vartheta d\mathfrak{l}\bigg\|^2\\[0.3cm] & \leq 4(\mu\mathcal{K})^2\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu-1}d\mathfrak{l}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\bigg(\int_0^{\gamma}\vartheta\mathscr{M}_{\mu}(\vartheta)d\vartheta\bigg)^2\\[0.3cm] & \quad +4(\mu\mathcal{K})^2Tr(Q)\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu-1)}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\bigg(\int_0^{\gamma}\vartheta\mathscr{M}_{\mu}(\vartheta)d\vartheta\bigg)^2\\[0.3cm] & \quad +4(\mu\mathcal{K})^2\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_{\mathfrak{s}-\epsilon}^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu-1}d\mathfrak{l}\int_{\mathfrak{s}-\epsilon}^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\bigg(\int_0^{\infty}\vartheta\mathscr{M}_{\mu}(\vartheta)d\vartheta\bigg)^2\\[0.3cm] & \quad +4(\mu\mathcal{K})^2Tr(Q)\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_{\mathfrak{s}-\epsilon}^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu-1)}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\bigg(\int_0^{\infty}\vartheta\mathscr{M}_{\mu}(\vartheta)d\vartheta\bigg)^2\\[0.3cm] & \leq 4\mu\mathcal{K}^2\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\bigg(\int_0^{\gamma}\vartheta\mathscr{M}_{\mu}(\vartheta)d\vartheta\bigg)^2\\[0.3cm] & \quad +4(\mu\mathcal{K})^2Tr(Q)\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu-1)}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\bigg(\int_0^{\gamma}\vartheta\mathscr{M}_{\mu}(\vartheta)d\vartheta\bigg)^2\\[0.3cm] & \quad +4\mu\mathcal{K}^2\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_{\mathfrak{s}-\epsilon}^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu-1}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\bigg(\frac{1}{\Gamma(\mu+1)}\bigg)^2\\[0.3cm] & \quad +4(\mu\mathcal{K})^2Tr(Q)\frac{\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}}{(1+\mathfrak{s})^2}\int_{\mathfrak{s}-\epsilon}^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu-1)}\mathfrak{p}(\mathfrak{l})d\mathfrak{l}\bigg(\frac{1}{\Gamma(\mu+1)}\bigg)^2\\[0.3cm] & \rightarrow 0\ \text{as}\ \epsilon\rightarrow 0, \gamma\rightarrow 0. \end{align*}

    Therefore, \mathcal{D}(\mathfrak{s}) is also a relatively compact set in L_2(\Xi, \mathscr{Y}) for \mathfrak{s}\in [0, \infty) . Now, the Schauder's fixed point theorem implies that \mho has at least a fixed-point \mathsf{x}^*\in \Phi_1 . Let \mathfrak{g}^*(\mathfrak{s}) = \mathfrak{s}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathsf{x}^*(\mathfrak{s}) . From the relationship between \Sigma and \mho , we have

    \begin{align*} \mathfrak{g}^*(\mathfrak{s})& = \mathscr{O}_{\lambda,\mu}[\mathfrak{g}_0-\varpi(0,\mathfrak{g}(0))]+\varpi(\mathfrak{s},\mathfrak{g}^*(\mathfrak{s}))+\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\mathcal{F}(\mathfrak{l},\mathfrak{g}^*(\mathfrak{l}))d\mathfrak{l}\nonumber\\[0.3cm] & \quad+\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}^*(\omega))dW(\omega)d\mathfrak{l},\quad \mathfrak{s}\in [0,\infty), \end{align*}

    which shows that \mathfrak{g}^* is a mild solution of the neutral stochastic HF-system (1.1).

    (ⅱ) If \mathfrak{g}(\mathfrak{s}) is a mild solution of the neutral stochastic HF-system (1.1), then

    \begin{align*} \mathfrak{g}(\mathfrak{s})& = \mathscr{O}_{\lambda,\mu}[\mathfrak{g}_0-\varpi(0,\mathfrak{g}(0))]+\varpi(\mathfrak{s},\mathfrak{g}(\mathfrak{s}))+\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\mathcal{F}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))d\mathfrak{l}\nonumber\\[0.3cm] & \quad+\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))dW(\omega)d\mathfrak{l},\quad \mathfrak{s}\in [0,\infty). \end{align*}

    By (H_2) , (H_4) , and (H_5) , noting that -1+\lambda-\lambda\mu+\mu\kappa < 0 , we obtain

    \begin{align*} E\|\mathfrak{g}(\mathfrak{s})\|^2&\leq 8\mathcal{K}_2^2[E\|\mathfrak{g}_0\|^2+\mathcal{K}_{\varpi}^2(1+\|\mathfrak{g}_0\|^2)]+4\mathcal{K}_\varpi^2\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}(1+\|\mathfrak{g}\|^2)\\[0.3cm] & \quad +\frac{4\mathcal{K}_1^2}{\mu\kappa}\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)+\mu\kappa}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}\mathfrak{p}(\mathfrak{s})d\mathfrak{l}\\[0.3cm] & \quad +4Tr(Q)\mathcal{K}_1^2\mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}\mathfrak{q}(\mathfrak{s})d\mathfrak{l}\rightarrow 0,\ \text{as}\ \mathfrak{s}\rightarrow \infty. \end{align*}

    Immediately, we can conclude that \mathfrak{g}(\mathfrak{s}) is an attractive solution which completes the proof.

    We assume that the subsequent hypothesis is true to demonstrate the existence results when the semigroup operator \{\mathscr{O}(\mathfrak{s})\}_{\mathfrak{s} > 0} is noncompact.

    (H_6) There exists a constant \mathscr{L} > 0 such that for every bounded set D\subset \mathscr{Y} , \alpha(\mathcal{F}(\mathfrak{s}, D))\vee \alpha(\int_0^{\mathfrak{l}}\mathit{G}(\mathfrak{l}, D))\leq \mathscr{L}\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}\alpha(D) , for a.e. \mathfrak{s}\in [0, \infty) .

    Theorem 3.6. Assume the semigroup operator \mathscr{O}(\mathfrak{s}) is noncompact for any \mathfrak{s} > 0 . If (H_1) (H_6) are satisfied, then

    (i) there exists at least one mild solution in \widehat{\Phi}_1 for the neutral stochastic HF-system (1.1);

    (ii) all these mild solutions are attractive.

    Proof. (ⅰ) We set \mathsf{x}_0(\mathfrak{s}) = \mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}\mathscr{O}_{\lambda, \mu}(\mathfrak{s})\mathfrak{g}_0, \ \mathfrak{s}\in [0, \infty) and \mathsf{x}_{m+1} = \mho\mathsf{x}_m, \ m = 0, 1, 2, \cdots . From Lemma 3.3, \mho\mathsf{x}_m\subset \Phi_1 whenever \mathsf{x}_m\in \Phi_1, \ m = 0, 1, 2, \cdots . Define \widehat{\mathcal{D}} = \{\mathrm{z}_m:\mathrm{z}_m(\mathfrak{s}) = \dfrac{(\mho\mathsf{x}_m)(\mathfrak{s})}{1+\mathfrak{s}}, \ \mathsf{x}_m\in \Phi_1\}_{m = 0}^{\infty} . We have to show that set \widehat{\mathcal{D}} is relatively compact.

    According to Lemmas 3.1 and 3.2, we already know that \widehat{\mathcal{D}} is equicontinuous, and for \mathsf{x}_m\in \Phi_1, \ \lim\limits_{\mathfrak{s}\rightarrow \infty}E\|\dfrac{(\mho\mathsf{x}_m)(\mathfrak{s})}{1+\mathfrak{s}}\|^2 = 0 uniformly. From Lemma 2.14, we have to show

    \widehat{\mathcal{D}} = \{\mathrm{z}_m:\mathrm{z}_m(\mathfrak{s}) = \dfrac{(\mho\mathsf{x})_m(\mathfrak{s})}{1+\mathfrak{s}},\ \mathsf{x}_m\in \Phi_1\}_{m = 0}^{\infty}

    is relatively compact in L^2(\Xi, \mathscr{Y}) .

    By Lemmas 2.6 and 2.12, along with the condition (H_6) , we obtain

    \begin{align*} &\quad \alpha\bigg(\bigg\{\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\mathcal{F}(\mathfrak{l},\mathfrak{g}_m(\mathfrak{l}))d\mathfrak{l}\bigg\}_{m = 0}^{\infty}\bigg)\\[0.3cm] &\leq 2\mathcal{K}_1\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}\alpha\bigg(\mathcal{F}\bigg(\mathfrak{l},\bigg\{\mathfrak{l}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathsf{x}_m(\mathfrak{l})\bigg\}_{m = 0}^{\infty}\bigg)\bigg)d\mathfrak{l}\\[0.3cm] &\leq 2\mathscr{L}\mathcal{K}_1\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}\mathfrak{l}^{1-\lambda+\lambda\mu-\mu\kappa}\alpha\bigg(\bigg\{\mathfrak{l}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathsf{x}_m(\mathfrak{l})\bigg\}_{m = 0}^{\infty}\bigg)d\mathfrak{l}\\[0.3cm] &\leq 2\mathscr{L}\mathcal{K}_1\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}(1+\mathfrak{l})\alpha\bigg(\bigg\{\frac{\mathsf{x}_m(\mathfrak{l})}{1+\mathfrak{l}}\bigg\}_{m = 0}^{\infty}\bigg)d\mathfrak{l}. \end{align*}

    On the other side, for all \mathfrak{g}, v\in \mathscr{Y} , from Lemmas 2.6 and 2.12, we obtain

    \begin{align*} &\quad\bigg\|\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\bigg[\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))-\int_0^{\mathfrak{l}}\mathit{G}(\omega,v(\omega))\bigg]dW(\omega)\bigg\|\\[0.3cm] &\leq \mathcal{K}_1\bigg(\bigg\|\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}[\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))-\int_0^{\mathfrak{l}}\mathit{G}(\omega,v(\omega))]dW(\omega)\bigg\|^2\bigg)^{\frac{1}{2}}\\[0.3cm] &\leq \mathcal{K}_1Tr(Q)\bigg(\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)} \mathcal{K}_1\bigg\|\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}(\omega))-\int_0^{\mathfrak{l}}\mathit{G}(\omega,v(\omega)) \mathcal{K}_1\bigg\|^2d\omega\bigg)^{\frac{1}{2}}. \end{align*}

    Thus, one has

    \begin{align*} &\quad\alpha\bigg(\bigg\{\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}_m(\omega))dW(\omega)\bigg\}_{m = 0}^{\infty}\bigg)\\[0.3cm] &\leq \mathcal{K}_1\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\bigg[2Tr(Q)\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}\bigg[\alpha\bigg(\mathit{G}\bigg(\mathfrak{l},\bigg\{\mathfrak{l}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathsf{x}_m(\mathfrak{l})\bigg\}_{m = 0}^{\infty}\bigg)\bigg)\bigg]^2d\mathfrak{l}\bigg]^{\frac{1}{2}}\\[0.3cm] &\leq \mathscr{L}\mathcal{K}_1\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\bigg[2Tr(Q)\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}\mathfrak{l}^{2(1-\lambda+\lambda\mu-\mu\kappa)}\bigg[\alpha\bigg(\bigg\{\mathfrak{l}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathsf{x}_m(\mathfrak{l})\bigg\}_{m = 0}^{\infty}\bigg)\bigg]^2d\mathfrak{l}\bigg]^{\frac{1}{2}}\\[0.3cm] &\leq \mathscr{L}\mathcal{K}_1\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\bigg[2Tr(Q)\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}(1+\mathfrak{l})^2\bigg[\alpha\bigg(\bigg\{\frac{\mathsf{x}_m(\mathfrak{l})}{1+\mathfrak{l}}\bigg\}_{m = 0}^{\infty}\bigg)\bigg]^2d\mathfrak{l}\bigg]^{\frac{1}{2}}. \end{align*}

    The above estimates yield that

    \begin{align*} \alpha(\widehat{\mathcal{D}}(\mathfrak{s}))& = \alpha\bigg(\bigg\{\frac{(\mho\mathsf{x})_m(\mathfrak{s})}{1+\mathfrak{s}}\bigg\}_{m = 0}^{\infty}\bigg)\\[0.3cm] & = \alpha\bigg(\bigg\{\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\mathscr{O}{\lambda,\mu}[\mathfrak{g}_0-\varpi(0,\mathfrak{g}(0))]+\varpi(\mathfrak{s},\mathfrak{g}_m(\mathfrak{s}))\\[0.3cm] & \quad+\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\mathcal{F}(\mathfrak{l},\mathfrak{g}_m(\mathfrak{l}))d\mathfrak{l}\\[0.3cm] &\quad+\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}_m(\omega))dW(\omega)d\mathfrak{l}\bigg\}_{m = 0}^{\infty}\bigg)\\[0.3cm] & = \alpha\bigg(\bigg\{\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\mathcal{F}(\mathfrak{l},\mathfrak{g}_m(\mathfrak{l}))d\mathfrak{l}\\[0.3cm] &\quad+\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\int_0^{\mathfrak{s}}\mathscr{P}_{\mu}(\mathfrak{s}-\mathfrak{l})\int_0^{\mathfrak{l}}\mathit{G}(\omega,\mathfrak{g}_m(\omega))dW(\omega)d\mathfrak{l}\bigg\}_{m = 0}^{\infty}\bigg)\\[0.3cm] & = 2\mathscr{L}\mathcal{K}_1\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}(1+\mathfrak{l})\alpha\bigg(\bigg\{\frac{\mathsf{x}_m(\mathfrak{l})}{1+\mathfrak{l}}\bigg\}_{m = 0}^{\infty}\bigg)d\mathfrak{l}\\[0.3cm] &\quad +\mathscr{L}\mathcal{K}_1\frac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\bigg[2Tr(Q)\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}(1+\mathfrak{l})^2\bigg[\alpha\bigg(\bigg\{\frac{\mathsf{x}_m(\mathfrak{l})}{1+\mathfrak{l}}\bigg\}_{m = 0}^{\infty}\bigg)\bigg]^2d\mathfrak{l}\bigg]^{\frac{1}{2}}. \end{align*}

    For any \mathfrak{s}\in [0, \infty) , from Lemma 2.5, one can derive that

    \begin{align*} \alpha\bigg(\bigg\{\frac{\mathsf{x}_m(\mathfrak{s})}{1+\mathfrak{s}}\bigg\}_{m = 0}^{\infty}\bigg) = \alpha\bigg(\bigg\{\frac{\mathsf{x}_0(\mathfrak{s})}{1+\mathfrak{s}}\bigg\}\cup\bigg\{\frac{\mathsf{x}_m(\mathfrak{s})}{1+\mathfrak{s}}\bigg\}_{m = 1}^{\infty}\bigg) = \alpha\bigg(\bigg\{\frac{\mathsf{x}_m(\mathfrak{s})}{1+\mathfrak{s}}\bigg\}_{m = 1}^{\infty}\bigg) = \alpha(\widehat{\mathcal{D}}(\mathfrak{s})). \end{align*}

    Hence, we deduce that

    \begin{align*} \alpha(\widehat{\mathcal{D}}(\mathfrak{s}))&\leq 2\mathscr{L}\mathcal{K}_1\mathcal{M}^*\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}(1+\mathfrak{l})\alpha(\widehat{\mathcal{D}}(\mathfrak{l}))d\mathfrak{l}\\[0.3cm] &\quad +\mathscr{L}\mathcal{K}_1\mathcal{M}^*\bigg[2Tr(Q)\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}(1+\mathfrak{l})^2[\alpha(\widehat{\mathcal{D}}(\mathfrak{l}))]^2d\mathfrak{l}\bigg]^{\frac{1}{2}}\\[0.3cm] & = M_1+M_2, \end{align*}

    where \mathcal{M}^* = \max\limits_{\mathfrak{s}\in [0, \infty)}\bigg\{\dfrac{\mathfrak{s}^{1-\lambda+\lambda\mu-\mu\kappa}}{1+\mathfrak{s}}\bigg\} .

    If M_1 > M_2 , from the estimates above, we have

    \begin{align*} \alpha(\widehat{\mathcal{D}}(\mathfrak{s}))&\leq 4\mathscr{L}\mathcal{K}_1\mathcal{M}^*\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}(1+\mathfrak{l})\alpha(\widehat{\mathcal{D}}(\mathfrak{l}))d\mathfrak{l}. \end{align*}

    Therefore, by a similar estimation, one of the inequalities

    \begin{align*} \alpha(\widehat{\mathcal{D}}(\mathfrak{s}))&\leq 8\mathscr{L}\mathcal{K}_1\mathcal{M}^*\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}\alpha(\widehat{\mathcal{D}}(\mathfrak{l}))d\mathfrak{l}, \end{align*}

    or

    \begin{align*} \alpha(\widehat{\mathcal{D}}(\mathfrak{s}))&\leq 8\mathscr{L}\mathcal{K}_1\mathcal{M}^*\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{\mu\kappa-1}\mathfrak{l}\alpha(\widehat{\mathcal{D}}(\mathfrak{l}))d\mathfrak{l} \end{align*}

    holds. As a result, the inequality, in ([46], p. 188), enables us to claim that \alpha(\widehat{\mathcal{D}}(\mathfrak{s})) = 0 .

    If M_1 < M_2 , a standard calculation yields that

    \begin{align*} \big(\alpha(\widehat{\mathcal{D}}(\mathfrak{s}))\big)^2\leq (2\mathscr{L}\mathcal{K}_1\mathcal{M}^*)^2\bigg(2Tr(Q)\int_0^{\mathfrak{s}}(\mathfrak{s}-\mathfrak{l})^{2(\mu\kappa-1)}(1+\mathfrak{l})^2[\alpha(\widehat{\mathcal{D}}(\mathfrak{l}))]^2d\mathfrak{l}\bigg). \end{align*}

    We may also conclude that \alpha(\widehat{\mathcal{D}}(\mathfrak{s})) = 0 by using an analogous argument to the first scenario. Therefore, \widehat{\mathcal{D}}(\mathfrak{s}) is relatively compact. Lemma 2.14, finally, gives this fact that the set \widehat{\mathcal{D}} is relatively compact. A subsequence of \{\mathsf{x}_m\}_{m = 0}^{\infty} exists so that it is convergent to, say, \mathsf{x}^* , i.e., \lim_{m\rightarrow \infty}\mathsf{x}_m = \mathsf{x}^*\in \Phi_1 . Thus, the continuity of the operator \mho enables us to declare that

    \begin{align*} \mathsf{x}^* = \lim\limits_{m\rightarrow \infty}\mathsf{x}_m = \lim\limits_{m\rightarrow \infty}\mho\mathsf{x}_{m-1} = \mho(\lim\limits_{m\rightarrow \infty}\mathsf{x}_{m-1}) = \mho\mathsf{x}^*. \end{align*}

    Let \mathfrak{g}^*(\mathfrak{s}) = \mathfrak{s}^{-1+\lambda-\lambda\mu+\mu\kappa}\mathsf{x}^*(\mathfrak{s}) . Thus, \mathfrak{g}^* is a fixed-point of \Sigma , which will be the mild solution of the neutral stochastic HF-system (1.1).

    (ⅱ) This proof is similar to (ⅱ) in Theorem 3.5.

    By Theorems 3.5 and 3.6, we have a corollary.

    Corollary 3.7. Assume that the semigroup operator \mathscr{O}(\mathfrak{s}) is compact for any \mathfrak{s} > 0 and assumptions (H_1) and (H_3) are fulfilled.

    (H_7) There exist a function \mathfrak{p}:(0, \infty)\rightarrow (0, \infty) and constants \chi\in (0, 1), \ \mathscr{N} > 0 such that for any \mathfrak{g}\in \mathscr{Y}, \ \mathfrak{s}\in (0, \infty) ,

    (I_{0+}^{\mu}\mathfrak{p})(\mathfrak{s})\in C((0,\infty),(0,\infty)),\ \mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)+\mu}(I_{0+}^{\mu}\mathfrak{p})(\mathfrak{s})\leq \mathscr{N}\mathfrak{s}^{2\chi},

    and

    E\|\mathcal{F}(\mathfrak{s},\mathfrak{g})\|^2\leq \mathfrak{p}(\mathfrak{s}).

    (H_8) There exist a function \mathfrak{q}:(0, \infty)\rightarrow (0, \infty) and constants \widehat{\chi}\in (0, 1), \ \widehat{\mathscr{N}} > 0 such that for any \mathfrak{g}\in \mathscr{Y}, \ \mathfrak{s}\in (0, \infty) ,

    (I_{0+}^{2\mu-1}\mathfrak{q})(\mathfrak{s})\in C((0,\infty),(0,\infty)),\ \mathfrak{s}^{2(1-\lambda+\lambda\mu-\mu\kappa)}(I_{0+}^{2\mu-1}\mathfrak{q})(\mathfrak{s})\leq \widehat{\mathscr{N}}\mathfrak{s}^{2\widehat{\chi}},

    and

    E\|\int_0^{\mathfrak{s}}\mathit{G}(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))d\mathfrak{l}\|^2\leq \mathfrak{q}(\mathfrak{s}).

    Then, there exists at least one mild solution in \widehat{\Phi}_1 for the neutral stochastic HF-system (1.1).

    Corollary 3.8. Suppose that the semigroup operator \mathscr{O}(\mathfrak{s}) is noncompact for all \mathfrak{s} > 0 . If (H_1) , (H_3) , (H_7) , (H_8) , and (H_6) are hold, then one can find at least one mild solution in \widehat{\Phi}_1 to the neutral stochastic HF-system (1.1).

    Consider the following HF neutral stochastic evolution integro-differential system on an infinite interval:

    \begin{align} \begin{cases} ^{H}D_{0+}^{\mu}[\mathfrak{g}(\mathfrak{s})-w(\mathfrak{s},\mathfrak{g}(\mathfrak{s}))] = \mathcal{A}[\mathfrak{g}(\mathfrak{s})-w(\mathfrak{s},\mathfrak{g}(\mathfrak{s}))]+f(\mathfrak{s},\mathfrak{g}(\mathfrak{s}))+ \int_0^{\mathfrak{s}}g(\mathfrak{l},\mathfrak{g}(\mathfrak{l}))dW(\mathfrak{l}),\\[0.2cm] I_{0+}^{1-\mu}\mathfrak{g}(0) = \mathfrak{g}_0,\; \; \; \; \; \mathfrak{s}\in (0,\infty), \end{cases} \end{align} (4.1)

    where f(\mathfrak{s}, \mathfrak{g}(\mathfrak{s})) and \int_0^{\mathfrak{s}}g(\mathfrak{l}, \mathfrak{g}(\mathfrak{l}))dW(\mathfrak{l}) fulfill (H_1) and (H_3) , respectively, and the constants \zeta, \beta > 0 exist such that E\|f(\mathfrak{s}, \mathfrak{g}(\mathfrak{s}))\|^2\leq \mathfrak{s}^{-\zeta}, \ E\| \int_0^{\mathfrak{s}}g(\mathfrak{l}, \mathfrak{g}(\mathfrak{l}))d\mathfrak{l}\|^2\leq \mathfrak{s}^{-\beta} for \zeta\in (\mu, 1), \ \beta\in (2\mu-1, 1) , and for \mathfrak{s}\in (0, \infty), \ \{\mathscr{O}(\mathfrak{s})\}_{\mathfrak{s}\geq 0} is compact.

    Let \mathfrak{p}(\mathfrak{s}) = \mathfrak{s}^{-\zeta}, \ \mathfrak{q}(\mathfrak{s}) = \mathfrak{s}^{-\beta} , for \mathfrak{s} > 0 . Then, it is easy to verify that

    \begin{align*} (I_{0+}^{\mu}\mathfrak{p})(\mathfrak{s})& = \frac{\Gamma(1-\zeta)}{\Gamma(1+\mu-\zeta)}\mathfrak{s}^{\mu-\zeta}\in C((0,\infty),(0,\infty)),\ \mathfrak{s}^{2(1-\mu)+\mu}(I_{0+}^{\mu}\mathfrak{p})(\mathfrak{s})\leq \mathscr{N}\mathfrak{s}^{2\chi},\\[0.3cm] (I_{0+}^{2\mu-1}\mathfrak{q})(\mathfrak{s})& = \frac{\Gamma(1-\beta)}{\Gamma(2\mu-\beta)}\mathfrak{s}^{2\mu-\beta-1}\in C((0,\infty),(0,\infty)),\ \mathfrak{s}^{2(1-\mu)}(I_{0+}^{2\mu-1}\mathfrak{q})(\mathfrak{s})\leq \widehat{\mathscr{N}}\mathfrak{s}^{2\widehat{\chi}}, \end{align*}

    where \chi = \dfrac{1}{2}(2-\zeta)\in (0, 1), \ \widehat{\chi} = \dfrac{1}{2}(1-\beta)\in (0, 1), \ \mathscr{N}\geq \dfrac{\Gamma(1-\zeta)}{\Gamma(1+\mu-\zeta)}\mathfrak{s}^{\mu-\zeta}, \widehat{\mathscr{N}}\geq \dfrac{\Gamma(1-\beta)}{\Gamma(2\mu-\beta)}\mathfrak{s}^{2\mu-\beta-1} , which means that the conditions (H_7) and (H_8) are fulfilled. Further, it is easy to prove that 1-\dfrac{\mu}{2} > \dfrac{1}{2}(2-\zeta) = \chi and 1-\mu > \dfrac{1}{2}(1-\beta) = \widehat{\chi} . By Corollary 3.7, the neutral stochastic HF-system (4.1) has at least a mild solution and also an attractive solution.

    Remark 4.1. This result may also extend to the attractive solution for Hilfer fractional neutral stochastic differential equations with Poisson jump.

    In this paper, we proved that Hilfer fractional neutral stochastic integro-differential equations on an infinite interval with almost sectorial operators have global mild and attractive solutions, and that the corresponding semigroup is either compact or noncompact. We determined the Wright function, the measure of noncompactness, and several alternative criteria to ensure the worldwide existence of mild solutions to the HF-system (1.1) by using the generalized Ascoli-Arzela theorem. To demonstrate the acquired theoretical findings, an example was given. This result may also be used to study Hilfer fractional neutral stochastic integro-differential equations with impulses on an infinite interval and their approximate controllability.

    The authors declare they have not used artificial intelligence (AI) tools in the creation of this article.

    This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia (grant no. 6041). This study is supported via funding from Prince Sattam bin Abdulaziz University, project number (PSAU/2024/R/1445).

    The authors declare no conflicts of interest.



    [1] M. V. D. Akker, H. Hoogeveen, N. Vakhania, Restarts can help in the on-line minimization of the maximum delivery time on a single machine, J. Scheduling, 3 (2000), 333–341. https://doi.org/10.1002/1099-1425(200011/12)3:6<333::AID-JOS53>3.0.CO;2-8 doi: 10.1002/1099-1425(200011/12)3:6<333::AID-JOS53>3.0.CO;2-8
    [2] H. Hoogeveen, C. N. Potts, G. J. Woeginger, On-line scheduling on a single machine: Maximizing the number of early jobs, Oper. Res. Lett., 27 (2000), 193–197. https://doi.org/10.1016/S0167-6377(00)00061-4 doi: 10.1016/S0167-6377(00)00061-4
    [3] R. Y. Fu, J. Tian, J. J. Yuan, C. He, On-line scheduling on a batch machine to minimize makespan with limited restarts, Oper. Res. Lett., 36 (2008), 255–258. https://doi.org/10.1016/j.orl.2007.07.001 doi: 10.1016/j.orl.2007.07.001
    [4] H. L. Liu, J. J. Yuan, Online scheduling of equal length jobs on a bounded parallel batch machine with restart or limited restart, Theor. Comput. Sci., 543 (2014), 24–36. https://doi.org/10.1016/j.tcs.2014.05.021 doi: 10.1016/j.tcs.2014.05.021
    [5] H. L. Liu, X. W. Lu, Online scheduling on a parallel batch machine with delivery times and limited restarts, J. Oper. Res. Soc. China, 10 (2022), 113–131. https://doi.org/10.1007/s40305-021-00356-7 doi: 10.1007/s40305-021-00356-7
    [6] R. Y. Fu, T. Ji, J. J. Yuan, Y. X. Lin, Online scheduling in a parallel batch processing system to minimize makespan using restarts, Theor. Comput. Sci., 374 (2007), 196–202. https://doi.org/10.1016/j.tcs.2006.12.040 doi: 10.1016/j.tcs.2006.12.040
    [7] J. J. Yuan, R. Y. Fu, C. T. Ng, T. C. E. Cheng, A best online algorithm for unbounded parallel-batch scheduling with restarts to minimize makespan, J. Scheduling, 14 (2011), 361–369. https://doi.org/10.1007/s10951-010-0172-2 doi: 10.1007/s10951-010-0172-2
    [8] R. Y. Fu, T. C. E. Cheng, C. T. Ng, J. J. Yuan, Online scheduling on two parallel-batching machines with limited restarts to minimize the makespan, Inform. Process. Lett., 110 (2010), 444–450. https://doi.org/10.1016/j.ipl.2010.04.008 doi: 10.1016/j.ipl.2010.04.008
    [9] J. Tian, R. Y. Fu, J. J. Yuan, Online over time scheduling on parallel-batch machines: A survey, J. Oper. Res. Soc. China, 2 (2014), 445–454. https://doi.org/10.1007/s40305-014-0060-0 doi: 10.1007/s40305-014-0060-0
    [10] W. J. Li, A best possible online algorithm for the parallel-machine scheduling to minimize the maximum weighted completion time, Asia-Pac. J. Oper. Res., 32 (2015), 1550030. https://doi.org/10.1142/S021759591550030X doi: 10.1142/S021759591550030X
    [11] X. Chai, L. F. Lu, W. H. Li, L. Q. Zhang, Best-possible online algorithms for single machine scheduling to minimize the maximum weighted completion time, Asia-Pac. J. Oper. Res., 35 (2018), 1850048. https://doi.org/10.1142/S0217595918500483 doi: 10.1142/S0217595918500483
    [12] L. F. Lu, L. Q. Zhang, J. W. Ou, Single machine scheduling with rejection to minimize the weighted makespan, In: Algorithmic Aspects in Information and Management, AAIM 2021, Lecture Notes in Computer Science, Springer, Cham, 13153 (2021), 96–110. https://doi.org/10.1007/978-3-030-93176-6_9
    [13] W. H. Li, X. Chai, Online scheduling on bounded batch machines to minimize the maximum weighted completion time, J. Oper. Res. Soc. China, 6 (2018), 455–465. https://doi.org/10.1007/s40305-017-0179-X doi: 10.1007/s40305-017-0179-X
    [14] R. Q. Sun, On the parameterized tractability of single machine scheduling with rejection to minimize the weighted makespan, In: Theoretical Computer Science, NCTCS 2022, Communications in Computer and Information Science, Springer, Singapore, 1693 (2022), 236–247. https://doi.org/10.1007/978-981-19-8152-4_17
    [15] H. Nouinou, T. Arbaoui, A. Yalaoui, Minimising total weighted completion time for semi-online single machine scheduling with known arrivals and bounded processing times, Int. J. Prod. Res., 2023, 1–14. https://doi.org/10.1080/00207543.2023.2217294 doi: 10.1080/00207543.2023.2217294
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