Research article Special Issues

Optimal harvesting strategy for stochastic hybrid delay Lotka-Volterra systems with Lévy noise in a polluted environment


  • This paper concerns the dynamics of two stochastic hybrid delay Lotka-Volterra systems with harvesting and Lévy noise in a polluted environment (i.e., predator-prey system and competitive system). For every system, sufficient and necessary conditions for persistence in mean and extinction of each species are established. Then, sufficient conditions for global attractivity of the systems are obtained. Finally, sufficient and necessary conditions for the existence of optimal harvesting strategy are provided. The accurate expressions for the optimal harvesting effort (OHE) and the maximum of expectation of sustainable yield (MESY) are given. Our results show that the dynamic behaviors and optimal harvesting strategy are closely correlated with both time delays and three types of environmental noises (namely white Gaussian noises, telephone noises and Lévy noises).

    Citation: Sheng Wang, Lijuan Dong, Zeyan Yue. Optimal harvesting strategy for stochastic hybrid delay Lotka-Volterra systems with Lévy noise in a polluted environment[J]. Mathematical Biosciences and Engineering, 2023, 20(4): 6084-6109. doi: 10.3934/mbe.2023263

    Related Papers:

    [1] Mohammed S. El-Khatib, Atta A. K. Abu Hany, Mohammed M. Matar, Manar A. Alqudah, Thabet Abdeljawad . On Cerone's and Bellman's generalization of Steffensen's integral inequality via conformable sense. AIMS Mathematics, 2023, 8(1): 2062-2082. doi: 10.3934/math.2023106
    [2] Ahmed A. El-Deeb, Dumitru Baleanu, Nehad Ali Shah, Ahmed Abdeldaim . On some dynamic inequalities of Hilbert's-type on time scales. AIMS Mathematics, 2023, 8(2): 3378-3402. doi: 10.3934/math.2023174
    [3] Awais Younus, Khizra Bukhsh, Manar A. Alqudah, Thabet Abdeljawad . Generalized exponential function and initial value problem for conformable dynamic equations. AIMS Mathematics, 2022, 7(7): 12050-12076. doi: 10.3934/math.2022670
    [4] Ahmed A. El-Deeb, Inho Hwang, Choonkil Park, Omar Bazighifan . Some new dynamic Steffensen-type inequalities on a general time scale measure space. AIMS Mathematics, 2022, 7(3): 4326-4337. doi: 10.3934/math.2022240
    [5] Tingting Guan, Guotao Wang, Haiyong Xu . Initial boundary value problems for space-time fractional conformable differential equation. AIMS Mathematics, 2021, 6(5): 5275-5291. doi: 10.3934/math.2021312
    [6] Elkhateeb S. Aly, Y. A. Madani, F. Gassem, A. I. Saied, H. M. Rezk, Wael W. Mohammed . Some dynamic Hardy-type inequalities with negative parameters on time scales nabla calculus. AIMS Mathematics, 2024, 9(2): 5147-5170. doi: 10.3934/math.2024250
    [7] Ahmed A. El-Deeb, Samer D. Makharesh, Sameh S. Askar, Dumitru Baleanu . Bennett-Leindler nabla type inequalities via conformable fractional derivatives on time scales. AIMS Mathematics, 2022, 7(8): 14099-14116. doi: 10.3934/math.2022777
    [8] Gauhar Rahman, Kottakkaran Sooppy Nisar, Feng Qi . Some new inequalities of the Grüss type for conformable fractional integrals. AIMS Mathematics, 2018, 3(4): 575-583. doi: 10.3934/Math.2018.4.575
    [9] Ahmed M. Ahmed, Ahmed I. Saied, Mohammed Zakarya, Amirah Ayidh I Al-Thaqfan, Maha Ali, Haytham M. Rezk . Advanced Hardy-type inequalities with negative parameters involving monotone functions in delta calculus on time scales. AIMS Mathematics, 2024, 9(11): 31926-31946. doi: 10.3934/math.20241534
    [10] Mehmet Eyüp Kiriş, Miguel Vivas-Cortez, Gözde Bayrak, Tuğba Çınar, Hüseyin Budak . On Hermite-Hadamard type inequalities for co-ordinated convex function via conformable fractional integrals. AIMS Mathematics, 2024, 9(4): 10267-10288. doi: 10.3934/math.2024502
  • This paper concerns the dynamics of two stochastic hybrid delay Lotka-Volterra systems with harvesting and Lévy noise in a polluted environment (i.e., predator-prey system and competitive system). For every system, sufficient and necessary conditions for persistence in mean and extinction of each species are established. Then, sufficient conditions for global attractivity of the systems are obtained. Finally, sufficient and necessary conditions for the existence of optimal harvesting strategy are provided. The accurate expressions for the optimal harvesting effort (OHE) and the maximum of expectation of sustainable yield (MESY) are given. Our results show that the dynamic behaviors and optimal harvesting strategy are closely correlated with both time delays and three types of environmental noises (namely white Gaussian noises, telephone noises and Lévy noises).



    Riemann-Liouville fractional integral given by

    Iαa+ξ()=1Γ(α)χa(χ)α1ξ()dt.

    Many different concepts of fractional derivative maybe found in [9,10,11]. In [12] studied a conformable derivative:

    αf()=limϵ0f(+ϵ1α)f()ϵ.

    The time scale conformable derivatives was introduced by Benkhettou et al. [17].

    Further, in recent years, numerous mathematicians claimed that non-integer order derivatives and integrals are well suited to describing the properties of many actual materials, such as polymers. Fractional derivatives are a wonderful tool for describing memory and learning. a variety of materials and procedures inherited properties is one of the most significant benefits of fractional ownership. For more concepts and definition on time scales see [13,14,15,16,17,18,19,33,34,35].

    Continuous version of Steffensen's inequality [7] is written as: For 0g()1 on [a,b]. Then

    bbλf()dtbaf()g()dta+λaf()dt, (1.1)

    where λ=bag()dt.

    Supposing f is nondecreasing gets the reverse of (1.1).

    Also, the discrete inequality of Steffensen [6] is: For λ2n=1g()λ1. Then

    n=nλ2+1f()n=1f()g()λ1=1f(). (1.2)

    Recently, a large number of dynamic inequalities on time scales have been studied by a small number of writers who were inspired by a few applications (see [1,2,3,4,8,28,29,30,31,32,36,37,40,41,42,44,48,49,50,51,52,53]).

    In [5] Jakšetić et al. proved that, if ˆμ([c,d])=[a,b]g()dˆμ(), where [c,d][a,b]. Then

    [a,b]f()g()dˆμ()[c,d]f()g()dˆμ()+[a,c](f()f(d))g()dˆμ(),

    and

    [c,d]f()dˆμ()[d,b](f(c)f())g()dˆμ()[a,b]f()g()dˆμ().

    Anderson, in [3], studied the inequality:

    bbλϕ()baϕ()ψ()a+λaϕ(), (1.3)

    In [47] the authors have proved, for

    m+λ1mζ()d=kmζ()g()d,

    and

    nnλ2ζ()d=nkζ()g()d.

    If there exists a constant A such that r()/ζ()At is monotonic on the intervals [m,k], [k,n], and

    nmtq()g()d=m+λ1mtq()d+nnλ2tq()d,

    then

    nmr()g()dm+λ1mr()d+nnλ2r()d.

    In particularly, Anderson [3] proved

    nnλr()nmr()g()m+λmr().

    where m,nTκ with m<n, r, g:[m,n]TR are -integrable functions such that r is of one sign and nonincreasing and 0g()1 on [m,n]T and λ=nmg(), nλ,m+λT.

    We prove the next two needed results:

    Theorem 1.1. Assume q>0 with 0g()ζ() [m,n]T and λ is given from nmg()Δα=m+λmζ()Δα, then

    nmr()g()Δαm+λmr()ζ()Δα. (1.4)

    Also, provided with 0g()ζ() and nnλζ()Δα=nmg()Δα, we have

    nnλr()ζ()Δαnmr()g()Δα. (1.5)

    We get the reverse inequalities of (1.4) and (1.5) when assuming r/ζ is nondecreasing.

    Theorem 1.2. Assume ψ is integrable on time scales interval [m,n], with ζ()ψ()g()ψ()0[m,n]T and m+λmζ()Δα=nmg()Δα=nnλζ()Δα and g, r and ζ are Δα-integrable functions, ζ()g()0, we have

    nnλr()ζ()Δα+nm|(r()r(nλ))ψ()|Δαnmr()g()Δαm+λmr()ζ()Δαnm|(r()r(m+λ))ψ()|Δα, (1.6)

    and

    nnλr()ζ()Δαnnλ[r()ζ()(r()r(nλ))][ζ()g()]Δαnmr()g()Δαm+λm[r()ζ()(r()r(m+λ))][ζ()g()]Δαm+λmr()ζ()Δα. (1.7)

    Proof. The proof techniques of Theorems 1.6 and 1.7 are like to that in [4] and is removed.

    Several authors proved conformable Hardy's inequality [20,21], conformable Hermite-Hadamard's inequality [22,23,24], conformable inequality of Opial's [26,27] and conformable inequality of Steffensen's [25]. In [45] Anderson proved the followong results:

    Theorem 1.3. [45] Suppose α(0,1] and r1, r2R such that 0r1r2. Suppose :[r1,r2][0,) and Γ:[r1,r2][0,1] are α-fractional integrable functions on [r1,r2] with Π is decreasing, we get

    r2r2Π(ζ)dαζr2r1Π(ζ)Γ(ζ)dαζr1+r1Π(ζ)dαζ,

    where =α(r2r1)rα2rα1r2r1Γ(ζ)dαζ[0,r2r1].

    In [46] the authors gave an extension for Theorem 1.8:

    Theorem 1.4. Assume α(0,1] and r1, r2R such that 0r1r2. Suppose ,Γ,Σ:[r1,r2][0,) are integrable on [r1,r2] with the decreasing function Π and 0ΓΣ, we get

    r2r2Σ(ζ)Π(ζ)dαζr2r1Π(ζ)Γ(ζ)dαζr1+r1Σ(ζ)Π(ζ)dαζ,

    where =(r2r1)r2r1Σ(ζ)dαζr2r1Γ(ζ)dαζ[0,r2r1].

    In this paper, we prove and explore several novel speculations of the Steffensen inequality obtained in [47] through the conformable integral containing time scale concept. We furthermore recover certain known results as special cases of our results.

    Lemma 2.1. Assume ζ>0 is rd-continuous function on [m,n]T, g, r be rd-continuous on [m,n]T such that r/ζ nonincreasing function and 0g()1 [m,n]T. Then

    (Λ1)

    nmr()g()Δαm+λmr()Δα, (2.1)

    where λ is given by

    nmζ()g()Δα=m+λmζ()Δα.

    (Λ2)

    nnλr()Δαnmr()g()Δα, (2.2)

    such that

    nnλζ()Δα=nmζ()g()Δα.

    (2.1) and (2.2) are reversed when r/ζ is nondecreasing.

    Proof. Putting g()ζ()g() and r()r()/ζ() in (1.4), (1.5) to get (Λ1) and (Λ2) simultaneously.

    Lemma 2.2. Under the same hypotheses of Lemma 2.1. with ψ be integrable functions on [m,n]T and 0ψ()g()1ψ() for all [m,n]T. Then

    nnλr()Δα+nm|(r()ζ()r(nλ)ζ(nλ))ζ()ψ()|Δαnmr()g()Δαm+λmr()Δαnm|(r()ζ()r(m+λ)ζ(m+λ))ζ()ψ()|Δα,

    where λ is obtained from

    m+λmh()Δα=nmζ()g()Δα=nnλζ()Δα.

    Proof. Putting g()ζ()g(), r()r()/h() and ψ()ζ()ψ() in (1.6).

    Lemma 2.3. Under the same conditions of Lemma 2.1. Then

    nnλr()Δαnnλ(r()[r()ζ()r(nλ)ζ(nλ)]ζ()[1g()])Δαnmr()g()Δαm+λm(r()[r()ζ()r(a+λ)ζ(m+λ)]ζ()[1g()])Δαm+λmr()Δα,

    where λ is obtained from

    m+λmζ()Δα=nmg()Δα=nnλζ()Δα.

    Proof. Taking g()ζ()g() and r()r()/ζ() in (1.7).

    Theorem 2.1. Under the same conditions of Lemma 2.3 such that k(m,n) and λ1, λ2 are given from

    (Λ3)

    m+λ1mζ()Δα=kmζ()g()Δα,
    nnλ2ζ()Δα=nkζ()g()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=m+λ1mϕ()ζ()Δα+nnλ2ϕ()ζ()Δα, (2.3)

    then

    nmrσ()g()Δαm+λ1mrσ()Δα+nnλ2rσ()Δα. (2.4)

    (2.4) is reversed if rσ/ζAHk2[m,n] and (2.3).

    (Λ4)

    kkλ1ζ()Δα=kmζ()g()Δα,
    k+λ2kζ()Δα=nkζ()g()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=k+λ2kλ1ϕ()ζ()Δα, (2.5)

    then

    nmrσ()g()Δαk+λ2kλ1rσ()Δα. (2.6)

    If rσ/ζAHk2[m,n] and (2.5) satisfied, then we reverse (2.6).

    (Λ5) If λ1, λ2 be the same as in (Λ3) and rσ/ζAHk1[m,n] so that

    nmϕ()ζ()g()Δα=m+λ1m(ϕ()ζ()[ϕ()mλ1]ζ()[1g()])Δα+nnλ2(ϕ()ζ()[ϕ()n+λ2]ζ()[1g()])Δα, (2.7)

    then

    nmrσ()g()Δαm+λ1m(rσ()|rσ()ζ()rσ(m+λ1)ζ(m+λ1)|ζ()[1g()])Δα+nnλ2(rσ()|rσ()ζ()rσ(nλ2)ζ(nλ2)|ζ()[1g()])Δα. (2.8)

    If rσ/ζAHk2[m,n] and (2.7) satisfied, the inequality in (2.8) is reversed.

    (Λ6) If λ1, λ2 be defined as in (Λ4) and rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=kkλ1(ϕ()ζ()[ϕ()k+λ1]ζ()[1g()])Δα=m+λ1m(ϕ()ζ()[ϕ()k+λ2]ζ()[1g()])Δα, (2.9)

    then

    nmrσ()g()Δαkkλ1(rσ()[rσ()ζ()rσ(kλ1)ζ(kλ1)]ζ()[1g()])Δα+k+λ2k(rσ()[rσ()ζ()rσ(k+λ2)ζ(k+λ2)]ζ()[1g()])Δα. (2.10)

    If rσ/ζAHk2[m,n] and (2.9) satisfied, we reverse (2.10).

    Proof. (Λ3) Consider rσ/ζAHk1[m,n], and R1()=rσ()Aϕ()ζ(), since A is given in Definition 2.1. Since R1/ζ:[m,k]TR, using Lemma 2.1(Λ1), we deduce

    0m+λ1mR1()ΔαkmR1()g()Δα=m+λ1mrσ()Δαkmrσ()g()ΔαA(m+λ1mϕ()ζ()Δαkmϕ()ζ()g()Δα). (2.11)

    As R1/ζ:[k,n]TR is nondecreasing, using Lemma 2.1(Λ2), we obtain

    0nkR1()g()Δαnnλ2R1()Δα=nkrσ()g()Δαnnλ2rσ()ΔαA(nkϕ()ζ()g()Δαnnλ2ϕ()ζ()Δα). (2.12)

    (2.11) and (2.12) imply that

    m+λ1mrσ()Δα+nnλ2rσ()Δαnmrσ()g()ΔαA(m+λ1mϕ()ζ()Δα+nnλ2ϕ()ζ()Δαnmϕ()ζ()g()Δα)

    Hence, if (2.3) is hold, then (2.4) holds. For rσ/ζAHk2[m,n], we get the some steps.

    (Λ4) Let rσ/ζAHk1[m,n], also R1(x)=rσ(x)Aϕ(x)ζ(x), where A as in Definition 2.1. R1/ζ:[m,k]TR is nonincreasing, so from Lemma 2.1(Λ1) we obtain

    0kmrσ()g()Δαkkλ1rσ()ΔαA(kmϕ()h()g()Δαkcλ1ϕ()ζ()Δα). (2.13)

    Using Lemma 2.1(Λ1) we have

    0k+λ2krσ()Δαnkrσ()g()ΔαA(k+λ2kϕ()ζ()Δαnkϕ()ζ()g()Δα). (2.14)

    Thus, from (2.13), (2.14), we get

    nmrσ()g()Δαk+λ2kλ1rσ()ΔαA(nmϕ()ζ()g()Δαk+λ2kλ1ϕ()ζ()Δα)

    Therefore, if nmϕ()ζ()g()Δα=k+λ2kλ1ϕ()ζ()Δα is satisfied, then (2.8) holds. Follow the same steps for rσ/ζAHk2[m,n].

    Using Lemma 2.3 and repeat the steps of Theorem 2.1(Λ3) and Theorem 2.1(Λ4) in the proof of (Λ5) and (Λ6) respectively.

    Corollary 2.1. The inequalities (2.4), (2.6), (2.8) and (2.10) of Theorem 2.1 letting T=R takes

    (i)nmfσ()g()dαm+λ1mrσ()dα+nnλ2rσ()dα. (2.15)
    (ii)nmrσ()g()dαk+λ2kλ1rσ()dα. (2.16)
    (iii)nmrσ()g()dαm+λ1m(rσ()[rσ()ζ()rσ(m+λ1)ζ(m+λ1)]ζ()[1g()])dα+nnλ2(rσ()[rσ()ζ()rσ(nλ2)ζ(nλ2)]ζ()[1g()])dα. (2.17)
    (iv)nmrσ()g()dαkkλ1(rσ()[rσ()ζ()rσ(kλ1)ζ(kλ1)]ζ()[1g()])dα+k+λ2k(rσ()[rσ()ζ()rσ(k+λ2)ζ(k+λ2)]ζ()[1g()])dα. (2.18)

    Corollary 2.2. We get [47,Theorems 8,10,21 and 22], if we put α=1 and ϕ()= in Corollary 2.1 [(i),(ii),(iii),(iv)] simultaneously.

    Corollary 2.3. In Corollary 2.1 taking T=Z, the results (2.15)–(2.18) will be equivalent to

    (i)n1=mr(+1)g()α1m+λ11=mr(+1)+n1=nλ2r(+1)α1.
    (ii)n1=mr(+1)g()α1k+λ21=kλ1r(+1)α1.
    (iii)n1=mr(+1)g()α1m+λ11=m(r(+1)[r(+1)ζ()r(a+λ1+1)ζ(m+λ1)]ζ()[1g()])α1+n1=nλ2(r(+1)[r(+1)ζ()r(nλ2+1)ζ(nλ2)]ζ()[1g()])α1.
    (iv)n1=mr(+1)g())α1k1=kλ1(r(+1)[r(+1)ζ()r(kλ1+1)ζ(kλ1)]ζ()[1g()]))α1+k+λ21=k(r(+1)[r(+1)ζ()r(k+λ2+1)ζ(k+λ2)]ζ()[1g()]))α1.

    Theorem 2.2. Under the assumptions in Lemma 2.1 with 0g()ζ() and λ1, λ2 be defined as

    (Λ7)

    m+λ1mζ()Δα=kmg()Δα,
    nnλ2ζ()Δα=nkg()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()g()Δα=m+λ1mϕ()ζ()Δα+nnλ2ϕ()ζ()Δα, (2.19)

    then

    nmrσ()g()Δαm+λ1mrσ()ζ()Δα+nnλ2rσ()ζ()Δα. (2.20)

    (Λ8)

    kkλ1ζ()Δα=kmg()Δα,
    k+λ2kζ()Δα=nkg()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()g()Δα=k+λ2kλ1ϕ()ζ()Δα, (2.21)

    then

    nmrσ()g()Δαk+λ2kλ1rσ()ζ()Δα. (2.22)

    If rσ/ζAHk2[m,n] and (2.19), (2.21) satisfied, we get the reverse of (2.20) and (2.22).

    Proof. By using Theorem 2.1 [(Λ3),(Λ4)] and by putting gg/h and ffh, we get the proof of (Λ7) and (Λ8).

    Corollary 2.4. In Theorem 2.2 [(Λ7),(Λ8)], assuming T=R, the following results obtains:

    (i)nmrσ()g()dαm+λ1mrσ()ζ()dα+nnλ2rσ()ζ()dα. (2.23)
    (ii)nmrσ()g()dαk+λ2kλ1rσ()ζ()dα. (2.24)

    Corollary 2.5. In Corollary 2.4 [(i),(ii)], when we put α=1 and ϕ()= then [47,Theorems 16 and 17] gotten.

    Corollary 2.6. In (2.23) and (2.24) letting T=Z, gets

    (i)n1=mr(+1)g()α1m+λ11=mr(+1)h()+n1=nλ2r(+1)h()α1.
    (ii)n1=mr(+1)g()α1k+λ21=kλ1r(+1)ζ()α1.

    Theorem 2.3. Using the same conditions in Lemma 2.3. Letting w:[m,n]TR be integrable with 0g()w() [m,n]T and

    (Λ9)m+λ1mw()ζ()Δα=kmζ()g()Δα,
    nnλ2w()ζ()Δα=nkζ()g()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=m+λ1mϕ()w()ζ()Δα+nnλ2ϕ()w()ζ()Δα, (2.25)

    then

    nmrσ()g()Δαm+λ1mrσ()w()Δα+nnλ2rσ()w()Δα. (2.26)
    (Λ10)kkλ1w()ζ()Δα=kmζ()g()Δα,
    k+λ2kw()ζ()Δα=nkζ()g()Δα.

    If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=k+λ2kλ1ϕ()w()ζ()Δα, (2.27)
    nmrσ()g()Δαk+λ2kλ1rσ()w()Δα. (2.28)

    The inequalities in (2.26) and (2.28) are reversible if rσ/ζAHc2[a,b] and (2.25), (2.27) hold.

    Proof. In Theorem 2.1 [(Λ3),(Λ4)], ζ changes wq, g changes g/w and r changes rw.

    Corollary 2.7. In (2.26) and (2.28). Letting T=R, we have

    (i)nmrσ()g()dαm+λ1mrσ()w()dα+nnλ2rσ()w()dα. (2.29)
    (ii)nmrσ()g()dαk+λ2kλ1rσ()w()dα. (2.30)

    Corollary 2.8. In Corollary 2.7 [(i),(ii)], letting α=1 and ϕ()= we get [47,Theorems 18 and 19].

    Corollary 2.9. In (2.29) and (2.30), crossing T=Z, gets

    (i)n1=mr(+1)g()α1m+λ11=mr(+1)w()+n1=nλ2r(+1)w()α1.
    (ii)n1=mr(+1)g()α1k+λ21=kλ1r(+1)w()α1.

    Theorem 2.4. Using the same conditions in Lemma 2.1, and Theorem 2.1 [(Λ3),(Λ4)] with ψ:[m,n]TR be a integrable: 0ψ()g()1ψ().

    (Λ11) If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=m+λ1mϕ()ζ()Δαkm|ϕ()mλ1|ζ()ψ()Δα+nnλ2ϕ()ζ()Δα+nk|ϕ()n+λ2|ζ()ψ()Δα, (2.31)

    then

    nmrσ()g()Δαm+λ1mrσ()Δαkm|rσ()ζ()rσ(m+λ1)ζ(m+λ1)|ζ()ψ()Δα+nnλ2rσ()Δα+nk|rσ()ζ()rσ(nλ2)ζ(nλ2)|ζ()ψ()Δα. (2.32)

    (Λ12) If rσ/ζAHk1[m,n] and

    nmϕ()ζ()g()Δα=kkλ1ϕ()ζ()Δαkm|ϕ()k+λ1|ζ()ψ()Δα+nk|ϕ()kλ1|ζ()ψ()Δα, (2.33)

    then

    nmrσ()g()Δαk+λ2kλ1rσ()Δα+km|rσ()ζ()rσ(kλ1)ζ(kλ1)|ζ()ψ()Δαnk|rσ()ζ()rσ(k+λ2)ζ(k+λ2)|ζ()ψ()Δα. (2.34)

    If rσ/ζAHk2[m,n] and (2.31) and (2.33) satisfied, we get the reverse of (2.32) and (2.34).

    Proof. The same steps of Theorem 2.1 [(Λ3),(Λ4)] with Lemma 2.1, R1/ζ:[m,k]TR nonincreasing, R1/ζ:[k,n]TR nondecreasing.

    Corollary 2.10. In Theorem 2.4 [(Λ11),(Λ12)], letting T=R we get:

    (i)nmrσ()g()dαm+λ1mrσ()dαkm|rσ()ζ()rσ(m+λ1)ζ(m+λ1)|ζ()ψ()dα+nnλ2rσ()dα+nk|rσ()ζ()rσ(nλ2)ζ(nλ2)|ζ()ψ()dα. (2.35)
    (ii)nmrσ()g()dαk+λ2kλ1rσ()dα+km|rσ()ζ()rσ(kλ1)ζ(kλ1)|ζ()ψ()dαnk|rσ()ζ()rσ(k+λ2)ζ(k+λ2)|ζ()ψ()dα. (2.36)

    Corollary 2.11. In (2.35) and (2.36), we put α=1, with ϕ()= we get [47,Theorems 23 and 24].

    Corollary 2.12. Our results (2.35) and (2.36), by using T=Z gets

    (i)n1=mr(+1)g()α1m+λ11=mr(+1)α1k1=m|r(+1)ζ()r(m+λ1+1)ζ(m+λ1)|ζ()ψ()ˆ+n1=nλ2r(+1)α1+n1=k|r(+1)ζ()r(nλ2+1)ζ(nλ2)|ζ()ψ()α1.
    (ii)n1=mr(+1)g()α1k+λ21=kλ1r(+1)α1+k1=m|r(+1)ζ()r(kλ1+1)ζ(kλ1)|ζ()ψ()α1n1=k|r(+1)ζ()r(k+λ2+1)ζ(k+λ2)|h()ψ()α1.

    In this work, we explore new generalizations of the integral Steffensen inequality given in [38,39,43] by the utilization of the α-conformable derivatives and integrals, A few of these results are generalised to time scales. We also obtained the discrete and continuous case of our main results, in order to gain some fresh inequalities as specific cases.

    The authors extend their appreciation to the Research Supporting Project number (RSP-2022/167), King Saud University, Riyadh, Saudi Arabia.

    The authors declare no conflict of interest.



    [1] X. Zou, K. Wang, Optimal harvesting for a stochastic regime-switching logistic diffusion system with jumps, Nonlinear Anal. Hybrid Syst., 13 (2014), 32–44. https://doi.org/10.1016/j.nahs.2014.01.001 doi: 10.1016/j.nahs.2014.01.001
    [2] J. Roy, D. Barman, S. Alam, Role of fear in a predator-prey system with ratio-dependent functional response in deterministic and stochastic environment, Biosystems, 197 (2020), 104176. https://doi.org/10.1016/j.biosystems.2020.104176 doi: 10.1016/j.biosystems.2020.104176
    [3] Q. Liu, D. Jiang, Influence of the fear factor on the dynamics of a stochastic predator-prey model, Appl. Math. Lett., 112 (2021), 106756. https://doi.org/10.1016/j.aml.2020.106756 doi: 10.1016/j.aml.2020.106756
    [4] Q. Yang, X. Zhang, D. Jiang, Dynamical behaviors of a stochastic food chain system with Ornstein-Uhlenbeck process, J. Nonlinear Sci., 32 (2022), 1–40. https://doi.org/10.1007/s00332-021-09760-y doi: 10.1007/s00332-021-09760-y
    [5] L. Wang, D. Jiang, Ergodicity and threshold behaviors of a predator-prey model in stochastic chemostat driven by regime switching, Math. Meth. Appl. Sci., 44 (2021), 325–344. https://doi.org/10.1002/mma.6738 doi: 10.1002/mma.6738
    [6] Q. Luo, X. Mao, Stochastic population dynamics under regime switching, J. Math. Anal. Appl., 334 (2007), 69–84. https://doi.org/10.1016/j.jmaa.2006.12.032 doi: 10.1016/j.jmaa.2006.12.032
    [7] Q. Luo, X. Mao, Stochastic population dynamics under regime switching Ⅱ, J. Math. Anal. Appl., 355 (2009), 577–593. https://doi.org/10.1016/j.jmaa.2009.02.010 doi: 10.1016/j.jmaa.2009.02.010
    [8] C. Zhu, G. Yin, On hybrid competitive Lotka-Volterra ecosystems, Nonlinear Anal., 71 (2009), 1370–1379. https://doi.org/10.1016/j.na.2009.01.166 doi: 10.1016/j.na.2009.01.166
    [9] X. Li, A. Gray, D. Jiang, X. Mao, Sufficient and necessary conditions of stochastic permanence and extinction for stochastic logistic populations under regime switching, J. Math. Anal. Appl., 376 (2011), 11–28. https://doi.org/10.1016/j.jmaa.2010.10.053 doi: 10.1016/j.jmaa.2010.10.053
    [10] M. Ouyang, X. Li, Permanence and asymptotical behavior of stochastic prey-predator system with Markovian switching, Appl. Math. Comput., 266 (2015), 539–559. https://doi.org/10.1016/j.amc.2015.05.083 doi: 10.1016/j.amc.2015.05.083
    [11] J. Bao, J. Shao, Permanence and extinction of regime-switching predator-prey models, SIAM J. Math. Anal., 48 (2016), 725–739. https://doi.org/10.1137/15M1024512 doi: 10.1137/15M1024512
    [12] M. Liu, X. He, J. Yu, Dynamics of a stochastic regime-switching predator-prey model with harvesting and distributed delays, Nonlinear Anal. Hybrid Syst., 28 (2018), 87–104. https://doi.org/10.1016/j.nahs.2017.10.004 doi: 10.1016/j.nahs.2017.10.004
    [13] Y. Cai, S. Cai, X. Mao, Stochastic delay foraging arena predator-prey system with Markov switching, Stoch. Anal. Appl., 38 (2020), 191–212. https://doi.org/10.1080/07362994.2019.1679645 doi: 10.1080/07362994.2019.1679645
    [14] J. Bao, X. Mao, G. Yin, C. Yuan, Competitive Lotka-Volterra population dynamics with jumps, Nonlinear Anal., 74 (2011), 6601–6616. https://doi.org/10.1016/j.na.2011.06.043 doi: 10.1016/j.na.2011.06.043
    [15] J. Bao, C. Yuan, Stochastic population dynamics driven by Lévy noise, J. Math. Anal. Appl., 391 (2012), 363–375. https://doi.org/10.1016/j.jmaa.2012.02.043 doi: 10.1016/j.jmaa.2012.02.043
    [16] M. Liu, K. Wang, Dynamics of a Leslie-Gower Holling-type Ⅱ predator-prey system with Lévy jumps, Nonlinear Anal., 85 (2013), 204–213. https://doi.org/10.1016/j.na.2013.02.018 doi: 10.1016/j.na.2013.02.018
    [17] M. Liu, K. Wang, Stochastic Lotka-Volterra systems with Lévy noise, J. Math. Anal. Appl., 410 (2014), 750–763. https://doi.org/10.1016/j.jmaa.2013.07.078 doi: 10.1016/j.jmaa.2013.07.078
    [18] M. Liu, M. Deng, B. Du, Analysis of a stochastic logistic model with diffusion, Appl. Math. Comput., 266 (2015), 169–182. https://doi.org/10.1016/j.amc.2015.05.050 doi: 10.1016/j.amc.2015.05.050
    [19] X. Zhang, W. Li, M. Liu, K. Wang, Dynamics of a stochastic Holling Ⅱ one-predator two-prey system with jumps, Phys. A, 421 (2015), 571–582. https://doi.org/10.1016/j.physa.2014.11.060 doi: 10.1016/j.physa.2014.11.060
    [20] D. Valenti, G. Denaro, A. Cognata, B. La Spagnolo, A. Bonanno, G. Basilone, et al., Picophytoplankton dynamics in noisy marine environment, Acta Phys. Pol. B, 43 (2012), 1227–1240. https://doi.org/10.5506/APhysPolB.43.1227 doi: 10.5506/APhysPolB.43.1227
    [21] C. Guarcello, D. Valenti, G. Augello, B. Spagnolo, The role of non-Gaussian sources in the transient dynamics of long Josephson junctions, Acta Phys. Pol. B, 44 (2013), 997–1005. https://doi.org/10.5506/APhysPolB.44.997 doi: 10.5506/APhysPolB.44.997
    [22] C. Guarcello, D. Valenti, B. Spagnolo, V. Pierro, G. Filatrella, Josephson-based threshold detector for Lévy-distributed current fluctuations, Phys. Rev. Appl., 11 (2019), 044078. https://doi.org/10.1103/PhysRevApplied.11.044078 doi: 10.1103/PhysRevApplied.11.044078
    [23] A. A. Dubkov, A. La Cognata, B. Spagnolo, The problem of analytical calculation of barrier crossing characteristics for Lévy flights, J. Stat. Mech. Theory Exp., 2009 (2019), P01002. https://doi.org/10.1088/1742-5468/2009/01/P01002 doi: 10.1088/1742-5468/2009/01/P01002
    [24] B. Lisowski, D. Valenti, B. Spagnolo, M. Bier, E. Gudowska-Nowak, Stepping molecular motor amid Lévy white noise, Phys. Rev. E, 91 (2015), 042713. https://doi.org/10.1103/PhysRevE.91.042713 doi: 10.1103/PhysRevE.91.042713
    [25] I. A. Surazhevsky, V. A. Demin, A. I. Ilyasov, A. V. Emelyanov, K. E. Nikiruy, V. V. Rylkov, et al., Noise-assisted persistence and recovery of memory state in a memristive spiking neuromorphic network, Chaos Solitons Fractals, 146 (2021), 110890. https://doi.org/10.1016/j.chaos.2021.110890 doi: 10.1016/j.chaos.2021.110890
    [26] A. N. Mikhaylov, D. V. Guseinov, A. I. Belov, D. S. Korolev, V. A. Shishmakova, M. N. Koryazhkina, et al., Stochastic resonance in a metal-oxide memristive device, Chaos Solitons Fractal, 144 (2021), 110723. https://doi.org/10.1016/j.chaos.2021.110723 doi: 10.1016/j.chaos.2021.110723
    [27] Y. V. Ushakov, A. A. Dubkov, B. Spagnolo, Spike train statistics for consonant and dissonant musical accords in a simple auditory sensory model, Phys. Rev. E, 81 (2010), 041911. https://doi.org/10.1103/PhysRevE.81.041911 doi: 10.1103/PhysRevE.81.041911
    [28] N. V. Agudov, A. V. Safonov, A. V. Krichigin, A. A. Kharcheva, A. A. Dubkov, D. Valenti, et al., Nonstationary distributions and relaxation times in a stochastic model of memristor, J. Stat. Mech. Theory Exp., 2020 (2020), 024003. https://doi.org/10.1088/1742-5468/ab684a doi: 10.1088/1742-5468/ab684a
    [29] D. O. Filatov, D. V. Vrzheshch, O. V. Tabakov, A. S. Novikov, A. I. Belov, I. N. Antonov, et al., Noise-induced resistive switching in a memristor based on ZrO2(Y)/Ta2O5 stack, J. Stat. Mech. Theory Exp., 2019 (2019), 124026. https://doi.org/10.1088/1742-5468/ab5704 doi: 10.1088/1742-5468/ab5704
    [30] A. Carollo, B. Spagnolo, A. A. Dubkov, D. Valenti, On quantumness in multi-parameter quantum estimation, J. Stat. Mech. Theory Exp., 2019 (2019), 094010. https://doi.org/10.1088/1742-5468/ab3ccb doi: 10.1088/1742-5468/ab3ccb
    [31] R. Stassi, S. Savasta, L. Garziano, B. Spagnolo, F. Nori, Output field-quadrature measurements and squeezing in ultrastrong cavity-QED, New J. Phys., 18 (2016), 123005. https://doi.org/10.1088/1367-2630/18/12/123005 doi: 10.1088/1367-2630/18/12/123005
    [32] S. Ciuchi, F. De Pasquale, B. Spagnolo, Nonlinear relaxation in the presence of an absorbing barrier, Phys. Rev. E, 47 (1993), 3915. https://doi.org/10.1103/PhysRevE.47.3915 doi: 10.1103/PhysRevE.47.3915
    [33] Y. Kuang, Delay Differential Equations: With Applications in Population Dynamics, Academic Press, Boston, 1993.
    [34] W. Zuo, D. Jiang, X. Sun, T. Hayat, A. Alsaedi, Long-time behaviors of a stochastic cooperative Lotka-Volterra system with distributed delay, Phys. A, 506 (2018), 542–559. https://doi.org/10.1016/j.physa.2018.03.071 doi: 10.1016/j.physa.2018.03.071
    [35] F. A. Rihan, H. J. Alsakaji, Stochastic delay differential equations of three-species prey-predator system with cooperation among prey species, Discret. Contin. Dyn. Syst. Ser. S, 15 (2020), 245. https://doi.org/10.3934/dcdss.2020468 doi: 10.3934/dcdss.2020468
    [36] H. J. Alsakaji, S. Kundu, F. A. Rihan, Delay differential model of one-predator two-prey system with Monod-Haldane and holling type Ⅱ functional responses, Appl. Math. Comput., 397 (2021), 125919. https://doi.org/10.1016/j.amc.2020.125919 doi: 10.1016/j.amc.2020.125919
    [37] L. Wang, R. Zhang, Y. Wang, Global exponential stability of reaction-diffusion cellular neural networks with S-type distributed time delays, Nonlinear Anal., 10 (2009), 1101–1113. https://doi.org/10.1016/j.nonrwa.2007.12.002 doi: 10.1016/j.nonrwa.2007.12.002
    [38] L. Wang, D. Xu, Global asymptotic stability of bidirectional associative memory neural networks with S-type distributed delays, Int. J. Syst. Sci., 338 (2002), 869–877. https://doi.org/10.1080/00207720210161777 doi: 10.1080/00207720210161777
    [39] S. Abbas, D. Bahuguna, M. Banerjee, Effect of stochastic perturbation on a two species competitive model, Nonlinear Anal. Hybrid Syst., 3 (2009), 195–206. https://doi.org/10.1016/j.nahs.2009.01.001 doi: 10.1016/j.nahs.2009.01.001
    [40] Q. Han, D. Jiang, C. Ji, Analysis of a delayed stochastic predator-prey model in a polluted environment, Appl. Math. Model., 38 (2014), 3067–3080. https://doi.org/10.1016/j.apm.2013.11.014 doi: 10.1016/j.apm.2013.11.014
    [41] Q. Liu, Q. Chen, Analysis of a stochastic delay predator-prey system with jumps in a polluted environment, Appl. Math. Comput., 242 (2014), 90–100. https://doi.org/10.1016/j.amc.2014.05.033 doi: 10.1016/j.amc.2014.05.033
    [42] Y. Zhao, S. Yuan, Optimal harvesting policy of a stochastic two-species competitive model with Lévy noise in a polluted environment, Phys. A, 477 (2017), 20–33. https://doi.org/10.1016/j.physa.2017.02.019 doi: 10.1016/j.physa.2017.02.019
    [43] M. Liu, X. He, J. Yu, Dynamics of a stochastic regime-switching predator-prey model with harvesting and distributed delays, Nonlinear Anal. Hybrid Syst., 28 (2018), 87–104. https://doi.org/10.1016/j.nahs.2017.10.004 doi: 10.1016/j.nahs.2017.10.004
    [44] M. Liu, C. Bai, Dynamics of a stochastic one-prey two-predator model with Lévy jumps, Appl. Math. Comput., 284 (2016), 308–321. https://doi.org/10.1016/j.amc.2016.02.033 doi: 10.1016/j.amc.2016.02.033
    [45] Y. Zhao, L. You, D. Burkow, S. Yuan, Optimal harvesting strategy of a stochastic inshore-offshore hairtail fishery model driven by Lévy jumps in a polluted environment, Nonlinear Dyn., 95 (2019), 1529–1548. https://doi.org/10.1007/s11071-018-4642-y doi: 10.1007/s11071-018-4642-y
    [46] Q. Liu, D. Jiang, N. Shi, T. Hayat, A. Alsaedi, Stochastic mutualism model with Lévy jumps, Commun. Nonlinear Sci. Numer. Simul., 43 (2017), 78–90. https://doi.org/10.1016/j.cnsns.2016.05.003 doi: 10.1016/j.cnsns.2016.05.003
    [47] H. Qiu, W. Deng, Optimal harvesting of a stochastic delay competitive Lotka-Volterra model with Lévy jumps, Appl. Math. Comput., 317 (2018), 210–222. https://doi.org/10.1016/j.amc.2017.08.044 doi: 10.1016/j.amc.2017.08.044
    [48] M. Liu, K. Wang, Survival analysis of stochastic single-species population models in polluted environments, Ecol. Model., 220 (2009), 1347–1357. https://doi.org/10.1016/j.ecolmodel.2009.03.001 doi: 10.1016/j.ecolmodel.2009.03.001
    [49] G. Liu, X. Meng, Optimal harvesting strategy for a stochastic mutualism system in a polluted environment with regime switching, Phys. A, 536 (2019), 120893. https://doi.org/10.1016/j.physa.2019.04.129 doi: 10.1016/j.physa.2019.04.129
    [50] S. Wang, L. Wang, T. Wei, Optimal harvesting for a stochastic logistic model with S-type distributed time delay, J. Differ. Equation Appl., 23 (2017), 618–632. https://doi.org/10.1080/10236198.2016.1269761 doi: 10.1080/10236198.2016.1269761
    [51] M. Liu, K. Wang, Q. Wu, Survival analysis of stochastic competitive models in a polluted environment and stochastic competitive exclusion principle, Bull. Math. Biol., 73 (2011), 1969–2012. https://doi.org/10.1007/s11538-010-9569-5 doi: 10.1007/s11538-010-9569-5
    [52] M. Liu, C. Bai, On a stochastic delayed predator-prey model with Lévy jumps, Appl. Math. Comput., 228 (2014), 563–570. https://doi.org/10.1016/j.amc.2013.12.026 doi: 10.1016/j.amc.2013.12.026
    [53] Q. Liu, Q. Chen, Z. Liu, Analysis on stochastic delay Lotka-Volterra systems driven by Lévy noise, Appl. Math. Comput., 235 (2014), 261–271. https://doi.org/10.1016/j.amc.2014.03.011 doi: 10.1016/j.amc.2014.03.011
    [54] X. Mao, Stochastic Differential Equations and Applications, Horwood Publishing Limited, 2007. https://doi.org/10.1533/9780857099402
    [55] D. Applebaum, Lévy Processes and Stochastic Calculus, Cambridge University Press, 2009. https://doi.org/10.1017/CBO9780511809781
    [56] I. Barbalat, Systems dequations differentielles d'osci d'oscillations, Rev. Roumaine Math. Pures Appl., 4 (1959), 267–270.
    [57] M. Kinnally, R. Williams, On existence and uniqueness of stationary distributions for stochastic delay differential equations with positivity constraints, Electron. J. Probab., 15 (2010), 409–451. https://doi.org/10.1214/EJP.v15-756 doi: 10.1214/EJP.v15-756
    [58] M. Hairer, J. C. Mattingly, M. Scheutzow, Asymptotic coupling and a general form of Harris' theorem with applications to stochastic delay equations, Probab. Theory Related Fields, 149 (2011), 223–259. https://doi.org/10.1007/s00440-009-0250-6 doi: 10.1007/s00440-009-0250-6
    [59] G. Prato, J. Zabczyk, Ergodicity for Infinite Dimensional Systems, Cambridge University Press, 1996.
    [60] M. Liu, Optimal harvesting policy of a stochastic predator-prey model with time delay, Appl. Math. Lett., 48 (2015), 102–108. https://doi.org/10.1016/j.aml.2014.10.007 doi: 10.1016/j.aml.2014.10.007
  • This article has been cited by:

    1. Ahmed A. El-Deeb, Clemente Cesarano, On Some Generalizations of Reverse Dynamic Hardy Type Inequalities on Time Scales, 2022, 11, 2075-1680, 336, 10.3390/axioms11070336
    2. Ahmed A. El-Deeb, Dumitru Baleanu, Jan Awrejcewicz, (Δ∇)∇-Pachpatte Dynamic Inequalities Associated with Leibniz Integral Rule on Time Scales with Applications, 2022, 14, 2073-8994, 1867, 10.3390/sym14091867
    3. Ahmed A. El-Deeb, Dumitru Baleanu, Nehad Ali Shah, Ahmed Abdeldaim, On some dynamic inequalities of Hilbert's-type on time scales, 2023, 8, 2473-6988, 3378, 10.3934/math.2023174
    4. Ahmed A. El-Deeb, Samer D. Makharesh, Sameh S. Askar, Dumitru Baleanu, Bennett-Leindler nabla type inequalities via conformable fractional derivatives on time scales, 2022, 7, 2473-6988, 14099, 10.3934/math.2022777
    5. Ahmed A. El-Deeb, Dumitru Baleanu, Clemente Cesarano, Ahmed Abdeldaim, On Some Important Dynamic Inequalities of Hardy–Hilbert-Type on Timescales, 2022, 14, 2073-8994, 1421, 10.3390/sym14071421
    6. Hassan M. El-Owaidy, Ahmed A. El-Deeb, Samer D. Makharesh, Dumitru Baleanu, Clemente Cesarano, On Some Important Class of Dynamic Hilbert’s-Type Inequalities on Time Scales, 2022, 14, 2073-8994, 1395, 10.3390/sym14071395
    7. Ahmed A. El-Deeb, Alaa A. El-Bary, Jan Awrejcewicz, On Some Dynamic (ΔΔ)∇- Gronwall–Bellman–Pachpatte-Type Inequalities on Time Scales and Its Applications, 2022, 14, 2073-8994, 1902, 10.3390/sym14091902
    8. Asfand Fahad, Saad Ihsaan Butt, Josip Pečarić, Marjan Praljak, Generalized Taylor’s Formula and Steffensen’s Inequality, 2023, 11, 2227-7390, 3570, 10.3390/math11163570
  • Reader Comments
  • © 2023 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1936) PDF downloads(120) Cited by(1)

Figures and Tables

Tables(1)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog