Research article Special Issues

Stochastic prey-predator model with small random immigration

  • Received: 24 January 2024 Revised: 18 March 2024 Accepted: 03 April 2024 Published: 25 April 2024
  • MSC : 92-11, 60H10, 34D20

  • In this paper, we introduce a novel stochastic prey-predator model under random small immigration. Mainly, we prove boundedness for the solution of the model using probabilistic and analytic types of inequalities. Furthermore, possible conditions on the immigration for achieving stochastic square stability are obtained. The immigration of both prey and predator is assumed to be either constant and stochastically perturbed or proportional to the population and stochastically perturbed. In all cases, we arrived at the fact that stability can only be achieved if the immigration is small enough. We also show that as random immigration increases, the dynamic becomes destabilized and could lead to chaos. Lastly, we perform a computational analysis in order to verify the obtained theoretical results.

    Citation: Jawdat Alebraheem, Mogtaba Mohammed, Ismail M. Tayel, Muhamad Hifzhudin Noor Aziz. Stochastic prey-predator model with small random immigration[J]. AIMS Mathematics, 2024, 9(6): 14982-14996. doi: 10.3934/math.2024725

    Related Papers:

    [1] Rashid Ali, Faisar Mehmood, Aqib Saghir, Hassen Aydi, Saber Mansour, Wajdi Kallel . Solution of integral equations for multivalued maps in fuzzy b-metric spaces using Geraghty type contractions. AIMS Mathematics, 2023, 8(7): 16633-16654. doi: 10.3934/math.2023851
    [2] Afrah Ahmad Noman Abdou . Chatterjea type theorems for complex valued extended b-metric spaces with applications. AIMS Mathematics, 2023, 8(8): 19142-19160. doi: 10.3934/math.2023977
    [3] Naeem Saleem, Salman Furqan, Mujahid Abbas, Fahd Jarad . Extended rectangular fuzzy b-metric space with application. AIMS Mathematics, 2022, 7(9): 16208-16230. doi: 10.3934/math.2022885
    [4] Samina Batul, Faisar Mehmood, Azhar Hussain, Reny George, Muhammad Sohail Ashraf . Some results for multivalued mappings in extended fuzzy b-metric spaces. AIMS Mathematics, 2023, 8(3): 5338-5351. doi: 10.3934/math.2023268
    [5] Siniša N. Ješić, Nataša A. Ćirović, Rale M. Nikolić, Branislav M. Ranƌelović . A fixed point theorem in strictly convex b-fuzzy metric spaces. AIMS Mathematics, 2023, 8(9): 20989-21000. doi: 10.3934/math.20231068
    [6] Abdullah Shoaib, Poom Kumam, Shaif Saleh Alshoraify, Muhammad Arshad . Fixed point results in double controlled quasi metric type spaces. AIMS Mathematics, 2021, 6(2): 1851-1864. doi: 10.3934/math.2021112
    [7] Dong Ji, Yao Yu, Chaobo Li . Fixed point and endpoint theorems of multivalued mappings in convex b-metric spaces with an application. AIMS Mathematics, 2024, 9(3): 7589-7609. doi: 10.3934/math.2024368
    [8] Pragati Gautam, Vishnu Narayan Mishra, Rifaqat Ali, Swapnil Verma . Interpolative Chatterjea and cyclic Chatterjea contraction on quasi-partial b-metric space. AIMS Mathematics, 2021, 6(2): 1727-1742. doi: 10.3934/math.2021103
    [9] Mustafa Mudhesh, Hasanen A. Hammad, Eskandar Ameer, Muhammad Arshad, Fahd Jarad . Novel results on fixed-point methodologies for hybrid contraction mappings in Mb-metric spaces with an application. AIMS Mathematics, 2023, 8(1): 1530-1549. doi: 10.3934/math.2023077
    [10] Abdolsattar Gholidahneh, Shaban Sedghi, Ozgur Ege, Zoran D. Mitrovic, Manuel de la Sen . The Meir-Keeler type contractions in extended modular b-metric spaces with an application. AIMS Mathematics, 2021, 6(2): 1781-1799. doi: 10.3934/math.2021107
  • In this paper, we introduce a novel stochastic prey-predator model under random small immigration. Mainly, we prove boundedness for the solution of the model using probabilistic and analytic types of inequalities. Furthermore, possible conditions on the immigration for achieving stochastic square stability are obtained. The immigration of both prey and predator is assumed to be either constant and stochastically perturbed or proportional to the population and stochastically perturbed. In all cases, we arrived at the fact that stability can only be achieved if the immigration is small enough. We also show that as random immigration increases, the dynamic becomes destabilized and could lead to chaos. Lastly, we perform a computational analysis in order to verify the obtained theoretical results.



    Fixed point theory has a vital role in mathematics and applied sciences. Also, this theory has lot of applications in differential equations and integral equations to guarantee the existence and uniqueness of the solutions [1,2]. The Banach contraction principle [3] has an imperative role in fixed point theory. Since after the appearance of this principle, it has become very popular and there has been a lot of activity in this area. On the other hand, to establish Banach contraction principle in a more general structure, the notion of a metric space was generalized by Bakhtin [4] in 1989 by introducing the idea of a b-metric space. Afterwards, the same idea was further investigated by Czerwik [5] to establish different results in b-metric spaces. The study of b-metric spaces holds a prominent place in fixed point theory. Banach contraction principle is generalized in many ways by changing the main platform of the metric space [6,7,8,9].

    Zadeh [10] introduced the notion of a fuzzy set theory to deal with the uncertain states in daily life. Motivated by the concept, Kramosil and Michálek [11] defined the idea of fuzzy metric spaces. Grabiec [12] gave contractive mappings on a fuzzy metric space and extended fixed point theorems of Banach and Edelstein in such spaces. Successively, George and Veeramani [13] slightly altered the concept of a fuzzy metric space introduced by Kramosil and Michálek [11] and then attained a Hausdorff topology and a first countable topology on it. Numerous fixed point theorems have been constructed in fuzzy metric spaces. For instance, see [14,15,16,17,18,19,20].

    Nǎdǎban [21] studied the notion of a fuzzy b-metric space and proved some results. Rakić et al. [22] (see also [23]) proved some new fixed point results in b-fuzzy metric spaces. The notion of a Hausdorff fuzzy metric on compact sets is introduced in [24] and recently studied by Shahzad et al. [25] to establish fixed point theorems for multivalued mappings in complete fuzzy metric spaces. In this paper, we use the idea of a fuzzy b-metric space and establish some fixed point results for multivalued mappings in Hausdorff fuzzy b-metric spaces. Some fixed point theorems are also derived from these results. Finally, we investigate the applicability of the obtained results to integral equations.

    Throughout the article, fuzzy metric space and fuzzy b-metric space are denoted by FMS and FBMS, respectively.

    Bakhtin [4] defined the notion of a b-metric space as follows:

    Definition 2.1. [4] Let Ω be a non-empty set. For any real number b1, a function db:Ω×ΩR is called a b-metric if it satisfies the following properties for all ζ1,ζ2,ζ3Ω:

    BM1 : db(ζ1,ζ2)0;

    BM2 : db(ζ1,ζ2)=0 if and only if ζ1=ζ2;

    BM3 : db(ζ1,ζ2)=db(ζ2,ζ1) for all ζ1,ζ2Ω;

    BM4 : db(ζ1,ζ3)b[db(ζ1,ζ2)+db(ζ2,ζ3)].

    The pair (Ω,db) is called a b-metric space.

    Definition 2.2. [26] A binary operation :[0,1]×[0,1][0,1] is called a continuous t-norm if it satisfies the following conditions:

    (1) is associative and commutative;

    (2) is continuous;

    (3) ζ1=ζ for all ζ[0,1];

    (4) ζ1ζ2ζ3ζ4whereverζ1ζ3andζ2ζ4, for all ζ1,ζ2,ζ3,ζ4[0,1].

    Example 2.1. Define a mapping :[0,1]×[0,1][0,1] by

    ζ1ζ2=ζ1ζ2forζ1,ζ2[0,1].

    It is then obvious that is a continuous t-norm, known as the product norm.

    George and Veermani [13] defined a fuzzy metric space as follows:

    Definition 2.3. [13] Consider a nonempty set Ω, then (Ω,F,) is a fuzzy metric space if is a continuous t-norm and F is a fuzzy set on Ω×Ω×[0,+) satisfying the following for all ζ1,ζ2,ζ3Ω and α,β>0:

    [F1]: F(ζ1,ζ2,α)>0;

    [F2]: F(ζ1,ζ2,α)=1 if and only if ζ1=ζ2;

    [F3]: F(ζ1,ζ2,α)=F(ζ2,ζ1,α);

    [F4]: F(ζ1,ζ3,α+β)F(ζ1,ζ2,α)F(ζ2,ζ3,β);

    [F5]: F(ζ1,ζ2,.):[0,+)[0,1] is continuous.

    In [27], the idea of a fuzzy b-metric space is given as:

    Definition 2.4. [27] Let Ωϕ be a set, b1 be a real number and be a continuous t-norm. A fuzzy set Fb on Ω×Ω×[0,+) is called a fuzzy b-metric on Ω if for all ζ1,ζ2,ζ3Ω, the following conditions hold:

    [Fb1]: Fb(ζ1,ζ2,α)>0;

    [Fb2]: Fb(ζ1,ζ2,α)=1,forallα>0 if and only if ζ1=ζ2;

    [Fb3]: Fb(ζ1,ζ2,α)=Fb(ζ2,ζ1,α);

    [Fb4]: Fb(ζ1,ζ3,b(α+β))Fb(ζ1,ζ2,α)Fb(ζ2,ζ3,β) forallα,β0;

    [Fb5]: Fb(ζ1,ζ2,.):(0,+)[0,1] is left continuous.

    Example 2.2. Let (Ω,db) be a b-metric space. Define a mapping Fb:Ω×Ω×[0,+)[0,1] by

    Fb(ζ1,ζ2,α)={αα+db(ζ1,ζ2)ifα>00ifα=0.

    Then (Ω,Fb,) is a fuzzy b-metric space, where

    ζ1ζ2=min{ζ1,ζ2}forallζ1,ζ2[0,1].

    is a t-norm, known as the minimum t-norm.

    Following Grabiec [12], we extend the idea of a G-Cauchy sequence and the notion of completeness in the FBMS as follows:

    Definition 2.5. Let (Ω,Fb,) be a FBMS.

    1) A sequence {ζn} in Ω is said to be a G-Cauchy sequence if limn+Fb(ζn,ζn+q,α)=1 for α>0 and q>0.

    2) A FBMS in which every G-Cauchy sequence is convergent is called a G-complete FBMS.

    Similarly, for a FBMS (Ω,Fb,), a sequence {ζn} in Ω is said to be convergent if there exits ζΩ such that for all α>0,

    limn+Fb(ζn,ζ,α)=1.

    Definition 2.6. [25] Let ϕ be a subset of a FBMS (Ω,F,) and α>0, then the fuzzy distance F of an element ϱ1Ω and the subset Ω is

    F(ϱ1,,α)=sup{F(ϱ1,ϱ2,α):ϱ2}.

    Note that F(ϱ1,,α)=F(,ϱ1,α).

    Lemma 2.1. [28] If ΛCB(Ω), then ζ1Λ if and only if F(Λ,ζ1,α)=1 for all α>0, where CB(Ω) is the collection of closed bounded subsets of Ω.

    Definition 2.7. [25] Let (Ω,F,) be a FMS. Define a function ΘF on ^C0(Ω)×^C0(Ω)×(0,+) by

    ΘF(Λ,,α)=min{ infϱ1ΛF(ϱ1,,α),infϱ2F(Λ,ϱ2,α)}

    for all Λ,^C0(Ω) and α>0, where ^C0(Ω) is the collection of all nonemty compact subsets of Ω.

    Lemma 2.2. [29] Let (Ω,F,) be a complete FMS and F(ζ1,ζ2,kα)F(ζ1,ζ2,α) for all ζ1,ζ2Ω,k(0,1) and α>0 then ζ1=ζ2.

    Lemma 2.3. [25] Let (Ω,F,) be a complete FMS such that (^C0,ΘF,) is a Hausdorff FMS on ^C0. Then for all Λ,^C0, for each ζΛ and for α>0, there exists ϱζ so that F(ζ,,α)=F(ζ,ϱζ,α) then

    ΘF(Λ,,α)F(ζ,ϱζ,α).

    The notion of a Hausdorff FMS in Definition 2.6 of [25] can be extended naturally for a Hausdorff FBMS on ^C0 as follows:

    Definition 2.8. Let (Ω,Fb,) be a FBMS. Define a function ΘFb on ^C0(Ω)×^C0(Ω)×(0,+) by

    ΘFb(Λ,,α)=min{ infζΛFb(ζ,,α),infϱFb(Λ,ϱ,α)}

    for all Λ,^C0(Ω) and α>0.

    This section deals with the idea of Hausdorff FBMS and certain new fixed point results in a fuzzy FBMS. Note that, one can easily extend Lemma 2.1 to 2.3 in the setting of fuzzy b-metric spaces.

    Lemma 3.1. If ΛC(Ω), then ζΛ if and only if Fb(Λ,ζ,α)=1forallα>0.

    Proof. Since

    Fb(Λ,ζ,α)=sup{Fb(ζ,ϱ,α):ϱΛ}=1,

    there exists a sequence {ϱn}Λ such that Fb(ζ,ϱn,α)>11n. Letting n+, we get ϱnζ. From ΛC(Ω), it follows that ζΛ. Conversely, if ζΛ, we have

    Fb(Λ,ζ,α)=sup{Fθ(ζ,ϱ,α):ϱΛ}>Fb(ζ,ζ,α)=1.

    Again, due to [17], the following fact follows from [Fb5].

    Lemma 3.2. Let (Ω,Fb,) be a G-complete FBMS. If for two elements ζ,ϱΩ and for a numberk<1

    Fb(ζ,ϱ,kα)Fb(ζ,ϱ,α),

    then ζ=ϱ.

    Lemma 3.3. Let (Ω,Fb,) be a G-complete FBMS, such that (^C0,ΘFb,) is a Hausdorff FBMS on ^C0. Then for all Λ,^C0, foreach ζΛ and for α>0 there exists ϱζ, satisfying Fb(ζ,,α)=Fb(ζ,ϱζ,α) also

    ΘFb(Λ,,α)Fb(ζ,ϱζ,α).

    Proof. If

    ΘFb(Λ,,α)=infζΛFb(ζ,,α),

    then

    ΘFb(Λ,,α)Fb(ζ,,α).

    Since for each ζΛ, there exists ϱζ satisfying

    Fb(ζ,,α)=Fb(α,ϱζ,α).

    Hence,

    ΘFb(Λ,,α)Fb(ζ,ϱζ,α).

    Now, if

    ΘFb(Λ,,α)=infϱFb(Λ,ϱ,α)infζΛFb(ζ,,α)Fb(ζ,,α)=Fb(ζ,ϱζ,α),

    this implies

    ΘFb(Λ,,α)Fb(ζ,ϱζ,α)

    for some ϱζ. Hence, in both cases, the result is proved.

    Theorem 3.1. Let (Ω,Fb,) be a G-complete FBMS with b1 and ΘFb be aHausdorff FBMS. Let S:Ω^C0(Ω) be a multivalued mapping satisfying

    ΘFb(Sζ,Sϱ,kα)Fb(ζ,ϱ,α) (3.1)

    for all ζ,ϱΩ, where bk<1,then S has a fixed point.

    Proof. For a0Ω, we choose a sequence {ζn} in Ω as follows: Let a1Ω such that a1Sa0. By using Lemma 6, we can choose a2Sa1 such that

    Fb(a1,a2,α)ΘFb(Sa0,Sa1,α)forallα>0.

    By induction, we have an+1San satisfying

    Fb(an,an+1,α)ΘFb(San1,San,α)forallnN.

    Now, by (3.1) together with Lemma 3.3, we have

    Fb(an,an+1,α)ΘFb(San1,San,α)Fb(an1,an,αk)ΘFb(San2,San1,αk)Fb(an2,an1,αk2)ΘFb(Sa0,Sa1,αkn1)Fb(a0,a1,αkn). (3.2)

    For any qN, writing α=αqb+α(q1)qb and using [Fb4] to get

    Fb(an,an+q,α)Fb(an,an+1,αqb)Fb(an+1,an+q,(q1)αqb).

    Again, writing (q1)αqb=αqb+α(q2)qb together with [Fb4], we have

    Fb(an,an+q,α)Fb(an,an+1,αqb)Fb(an+1,an+2,αqb2)Fb(an+2,an+q,(q2)αqb2).

    Continuing in the same way and using [Fb4] repeatedly for (q2) more steps, we obtain

    Fb(an,an+q,α)Fb(an,an+1,αqb)Fb(an+1,an+2,αqb2)Fb(an+q1,an+q,αqbq).

    Using (3.2) and [Fb5], we get

    Fb(an,an+q,α)Fb(a0,a1,αqbkn)Fb(a0,a1,αq(b)2kn+1)Fb(a0,a1,αq(b)3kn+2)Fb(a0,a1,αq(b)qkn+q1).

    Consequently,

    Fb(an,an+q,α)Fb(a0,a1,αq(bk)kn1)Fb(a0,a1,αq(bk)2kn1)Fb(a0,a1,αq(bk)3kn1)Fb(a0,a1,αq(bk)qkn1).

    Since for all n,qN, we have bk<1, taking limit as n+, we get

    limn+Fb(an,an+q,α)=111=1.

    Hence, {an} is a G-Cauchy sequence. Then, the G-completeness of Ω implies that there exists zΩ such that

    Fb(z,Sz,α)Fb(z,an+1,α2b)Fb(an+1,Sz,α2b)Fb(z,an+1,α2b)ΘFb(San,Sz,α2b)Fb(z,an+1,α2b)Fb(an,z,α2bk)1asn+.

    By Lemma 3.1, we have zSz. Hence, z is a fixed point for S.

    Example 3.1. Let Ω=[0,1] and Fb(ζ,ϱ,α)=αα+(ζϱ)2.

    It is easy to verify that (Ω,Fb,) is a G-complete FBMS with b1.

    For k(0,1), define a mapping S:Ω^C0(Ω) by

    S(ζ)={{0}ifζ=0{0,kζ2}otherwise.

    In the case ζ=ϱ, we have

    ΘFb(Sζ,Sϱ,kα)=1=Fb(ζ,ϱ,α).

    For ζϱ, we have the following cases:

    If ζ=0 and ϱ(0,1], we have

    ΘFb(S(0),S(ϱ),kα)=min{ infaS(0)Fb(a,S(ϱ),kα),infbS(ϱ)Fb(S(0),b,kα)}=min{infaS(0)Fb(a,{0,kϱ2},kα),infbS(ϱ)Fb({0},b,kα)}=min{inf{Fb(0,{0,kϱ2},kα)},inf{Fb({0},0,kα),Fb({0},kϱ2,kα)}}=min{inf{sup{Fb(0,0,kα),Fb(0,kϱ2,kα)}},inf{Fb(0,0,kα),Fb(0,kϱ2,kα)}}=min{inf{sup{1,αα+ϱ24}},inf{1,αα+ϱ24}}=min{inf{1},αα+ϱ24}=min{1,αα+ϱ24}=αα+ϱ24.

    It follows that ΘFb(S(0),S(ϱ),kα)>Fb(0,ϱ,α)=αα+ϱ2.

    If ζ and ϱ(0,1], an easy calculation with either possibility of supremum and infimum, yield that

    ΘFb(S(ζ),S(ϱ),kα)=min{sup{αα+ζ24,αα+(ζϱ)24},sup{αα+ϱ24,αα+(ζϱ)24}}αα+(ζϱ)24>αα+(ζϱ)2=Fb(ζ,ϱ,α).

    Thus, for all cases, we have

    ΘFb(Sζ,Sϱ,kα)Fb(ζ,ϱ,α).

    Hence, all the conditions of Theorem 3.1 are satisfied and 0 is a fixed point of S.

    Theorem 3.2. Let (Ω,Fb,) be a G-complete FBMS with b1 and ΘFb be a Hausdorff FBMS. Let S:Ω^C0(Ω) be a multivalued mapping which satisfies

    ΘFb(Sζ,Sϱ,kα)min{Fb(ϱ,Sϱ,α)[1+Fb(ζ,Sϱ,α)]1+Fb(ζ,ϱ,α),Fb(ζ,ϱ,α)} (3.3)

    for all ζ,ϱΩ, where bk<1,then S has a fixed point.

    Proof. In the same way as in Theorem 3.1 for a0Ω, we choose a sequence {an} in Ω as follows: Let a1Ω such that a1Sa0. By Lemma 2.3, we can choose a2Sa1 such that

    Fb(a1,a2,α)ΘFb(Sa0,Sa1,α)forallα>0.

    By induction, we have an+1San satisfying

    Fb(an,an+1,α)ΘFb(San1,San,α)forallnN.

    Now, by (3.3) together with Lemma 3.3, we have

    Fb(an,an+1,α)ΘFb(San1,San,α)min{Fb(an,San,αk)[1+Fb(an1,San1,αk)]1+Fb(an1,an,αk),Fb(an1,an,αk)}min{Fb(an,an+1,αk)[1+Fb(an1,an,αk)]1+Fb(an1,an,αk),Fb(an1,an,αk)}min{Fb(an,an+1,αk),Fb(an1,an,αk)}. (3.4)

    If

    min{Fb(an,an+1,αk),Fb(an1,an,αk)}=Fb(an,an+1,αk),

    then (3.4) implies

    Fb(an,an+1,α)Fb(an,an+1,αk).

    Then nothing to prove by Lemma 3.2. If

    min{Fb(an,an+1,αk),Fb(an1,an,αk)}=Fb(an1,an,αk),

    then from (3.4) we have

    Fb(an,an+1,α)Fb(an1,an,αk)Fb(a0,a1,αkn).

    By adopting the same procedure as in Theorem 3.1 after inequality (3.2), we can complete the proof.

    Remark 3.1. By taking b=1 in Theorem 3.2, Theorem 2.1 of [25] can be obtained.

    Theorem 3.3. Let (Ω,Fb,) be a G-complete FBMS (with b1) and ΘFb be a Hausdorff FBMS. Let S:ΩˆC0(Ω) be a multivalued map which satisfies

    ΘFb(Sζ,Sϱ,kα)min{Fb(ϱ,Sϱ,α)[1+Fb(ζ,Sζ,α)+Fb(ϱ,Sζ,α)]2+Fb(ζ,ϱ,α),Fb(ζ,ϱ,α)} (3.5)

    for all ζ,ϱΩ, where bk<1,then S has a fixed point.

    Proof. Starting same way as in Theorem 3.1, we have

    Fb(a1,a2,α)ΘFb(Sa0,Sa1,α)forallα>0.

    By induction, we have an+1San satisfying

    Fb(an,an+1,α)ΘFb(San1,San,α)forallnN.

    Now, by (3.5) together with Lemma 3.3, we have

    Fb(an,an+1,α)ΘFb(San1,San,α)min{Fb(an,San,αk)[1+Fb(an1,San1,αk)+Fb(an,San1,αk)]2+Fb(an1,an,αk),Fb(an1,an,αk)}min{Fb(an,an+1,αk)[1+Fb(an1,an,αk)+Fb(an,an,αk)]2+Fb(an1,an,αk),Fb(an1,an,αk)}min{Fb(an,an+1,αk)[1+Fb(an1,an,αk)+1]2+Fb(an1,an,αk),Fb(an1,an,αk)}min{Fb(an,an+1,αk)[2+Fb(an1,an,αk)]2+Fb(an1,an,αk),Fb(an1,an,αk)}min{Fb(an,an+1,αk),Fb(an1,an,αk)}. (3.6)

    If

    min{Fb(an,an+1,αk),Fb(an1,an,αk)}=Fb(an,an+1,αk),

    then (3.6) implies

    Fb(an,an+1,α)Fb(an,an+1,αk).

    Then nothing to prove by Lemma 3.2.

    If

    min{Fb(an,an+1,αk),Fb(an1,an,αk)}=Fb(an1,an,αk),

    then from (3.6), we have

    Fb(an,an+1,α)Fb(an1,an,αk)Fb(a0,a1,αkn).

    By adopting the same procedure as in Theorem 3.1 after inequality (3.2), we can complete the proof.

    Next, a corollary of Theorem 3.3 is given.

    Corollary 3.1. Let (Ω,F,) be a G-complete FMS and ΘF be a Hausdorff FMS. Let S:ΩˆC0(Ω) be a multivalued mapping satisfying

    ΘF(Sζ,Sϱ,kα)min{F(ϱ,Sϱ,α)[1+F(ζ,Sζ,α)+F(ϱ,Sζ,α)]2+F(ζ,ϱ,α),F(ζ,ϱ,α)}

    for all ζ,ϱΩ, where 0<k<1, then S has a fixed point.

    Proof. Taking b=1 in Theorem 3.3, one can complete the proof.

    Theorem 3.4. Let (Ω,Fb,) be a G-complete FBMS with b1 and ΘFb be a Hausdorff FBMS. Let S:ΩˆC0(Ω) be a multivalued map which satisfies

    ΘFb(Sζ,Sϱ,kα)min{Fb(ζ,Sζ,α)[1+Fb(ϱ,Sϱ,α)]1+Fb(Sζ,Sϱ,α),Fb(ζ,Sϱ,α)[1+Fb(ζ,Sζ,α)]1+Fb(ζ,ϱ,α),Fb(ζ,Sζ,α)[2+Fb(ζ,Sϱ,α)]1+Fb(ζ,Sϱ,α)+Fb(ϱ,Sζ,α),Fb(ζ,ϱ,α)} (3.7)

    for all ζ,ϱΩ, where bk<1,then S has a fixed point.

    Proof. For a0Ω, we choose a sequence {xn} in Ω as follows: Let a1Ω such that a1Sa0. By using Lemma 2.3, we can choose a2Sa1 such that

    Fb(a1,a2,α)ΘFb(Sa0,Sa1,α)forallα>0.

    By induction, we have an+1San satisfying

    Fb(an,an+1,α)ΘFb(San1,San,α)forallnN.

    Now, by (3.7) together with 3.3, we have

    Fb(an,an+1,α)ΘFb(San1,San,α)min{Fb(an1,San1,αk)[1+Fb(an,San,αk)]1+Fb(San1,San,αk),Fb(an,San,αk)[1+Fb(an1,San1,αk)]1+Fb(an1,an,αk),Fb(an1,San1,αk)[2+Fb(an1,San,αk)]1+Fb(an1,San,αk)+Fb(an,San1,αk),Fb(an1,an,αk)}
    min{Fb(an1,an,αk)[1+Fb(an,an+1,αk)]1+Fb(an,an+1,αk),Fb(an,an+1,αk)[1+Fb(an1,an,αk)]1+Fb(an1,an,αk),Fb(an1,an,αk)[2+Fb(an1,an+1,αk)]1+Fb(an1,an+1,αk)+Fb(an,an,αk),Fb(an1,an,αk)}
    Fb(an,an+1,α)min{Fb(an,an+1,αk),Fb(an1,an,αk)}. (3.8)

    If

    min{Fb(an,an+1,αk),Fb(an1,an,αk)}=Fb(an,an+1,αk),

    so (3.8) implies

    Fb(an,an+1,α)Fb(an,an+1,αk).

    Then nothing to prove by Lemma 3.2. While, if

    min{Fb(an,an+1,αk),Fb(an1,an,αk)}=Fb(an1,an,αk),

    then from (3.6) we have

    Fb(an,an+1,α)Fb(an1,an,αk)Fb(a0,a1,αkn).

    By adopting the same procedure as in Theorem 3.1 after inequality (3.2) we can complete the proof.

    The same result in fuzzy metric spaces is stated as follows.

    Corollary 3.2. Let (Ω,F,) be a G-complete FMS and ΘF be a Hausdorff FMS. Let S:Ω^C0(Ω) be a multivalued mapping satisfying

    ΘF(Sζ,Sϱ,kα)min{F(ζ,Sζ,α)[1+F(ϱ,Sϱ,α)]1+F(Sζ,Sϱ,α),F(ϱ,Sϱ,α)[1+F(ζ,Sζ,α)]1+F(ζ,ϱ,α),F(ζ,Sζ,α)[2+F(ζ,Sϱ,α)]1+F(ζ,Sϱ,α)+F(ϱ,Sζ,α),F(ζ,ϱ,α)}

    for all ζ,ϱΩ,then S has a fixed point.

    Proof. Taking b=1 in Theorem 3.4, one can complete the proof.

    This section is about the construction of some fixed point results involving integral inequalities as consequences of our results. Define a function τ:[0,+)[0,+) by

    τ(α)=α0ψ(α)dαforallα>0, (4.1)

    where τ(α) is a non-decreasing and continuous function. Moreover, ψ(α)>0 for α>0 and ψ(α)=0 if and only if α=0.

    Theorem 4.1. Let (Ω,Fb,) be a complete fuzzy b-metric space and ΘFb be a Hausdorff fuzzy b-metric space. Let S:ΩˆC0(Ω) be a multivalued mapping satisfying

    ΘFb(Sζ,Sϱ,kα)0ψ(α)dαFb(ζ,ϱ,α)0ψ(α)dα (4.2)

    for all ζ,ϱΩ, where bk<1, then S has a fixed point.

    Proof. Taking (4.1) in account, (4.2) implies that

    τ(ΘFb(Sζ,Sϱ,kα))τ(Fb(ζ,ϱ,α)).

    Since τ is continuous and non-decreasing, we have

    ΘFb(Sζ,Sϱ,kα)Fb(ζ,ϱ,α).

    The rest of the proof follows immediately from Theorem 3.1.

    A more general form of Theorem 4.1 can be stated as an immediate consequence of Theorem 3.2.

    Theorem 4.2. Let (Ω,Fb,) be a complete FBMS and ΘFb be a Hausdorff FBMS. Let S:ΩˆC0(Ω) be a multivalued mapping satisfying

    ΘFb(Sζ,Sϱ,kα)0ψ(α)dαβ(ζ,ϱ,α)0ψ(α)dα, (4.3)

    where

    β(ζ,ϱ,α)=min{Fb(ϱ,Sϱ,α)[1+Fb(ζ,Sϱ,α)]1+Fb(ζ,ϱ,α),Fb(ζ,ϱ,α)}

    for all ζ,ϱΩ, where bk<1, then S has a fixed point.

    Proof. Taking (4.1) in account, (4.3) implies that

    τ(ΘFb(Sζ,Sϱ,kα))τ(β(ζ,ϱ,α).

    Since τ is continuous and non-decreasing, we have

    ΘFb(Sζ,Sϱ,kα)β(ζ,ϱ,α).

    The rest of the proof follows immediately from Theorem 3.2.

    Remark 4.1. By taking b=1 in Theorem 4.2, Theorem 3.1 of [25] can be obtained.

    Theorem 4.3. Let (Ω,Fb,) be a complete FBMS and ΘFb be a Hausdorff FBMS. Let S:ΩˆC0(Ω) be a multivalued mapping satisfying

    ΘFb(Sζ,Sϱ,kα)0ψ(α)dαβ(ζ,ϱ,α)0ψ(α)dα,

    where

    β(ζ,ϱ,α)=min{Fb(ϱ,Sϱ,α)[1+Fb(ζ,Sζ,α)+Fb(ϱ,Sζ,α)]2+Fb(ζ,ϱ,α),Fb(ζ,ϱ,α)}

    for all ζ,ϱΩ, where bk<1, then S has a fixed point.

    Note that if β(ζ,ϱ,α)=Fb(ζ,ϱ,α), then the above result follows from Theorem 4.1. Similar results on integral inequalities can be obtained as a consequence of Theorem 3.4.

    Theorem 4.4. Let (Ω,Fb,) be a complete FBMS and ΘFb be a Hausdorff FBMS. Let S:ΩˆC0(Ω) be a multivalued mapping satisfying

    ΘFb(Sζ,Sϱ,kα)0ψ(α)dαγ(ζ,ϱ,α)0ψ(α)dα,

    where

    γ(ζ,ϱ,α)=min{Fb(ζ,Sζ,α)[1+Fb(ϱ,Sϱ,α)]1+Fb(Sζ,Sϱ,α),Fb(ϱ,Sϱ,α)[1+Fb(ζ,Sζ,α)]1+Fb(ζ,ϱ,α),Fb(ζ,Sζ,α)[2+Fb(ζ,Sϱ,α)]1+Fb(ζ,Sϱ,α)+Fb(ϱ,Sζ,α),Fb(ζ,ϱ,α)}

    for all ζ,ϱΩ, where bk<1, then S has a fixed point.

    Nonlinear integral equations arise in a variety of fields of physical science, engineering, biology, and applied mathematics [31,32]. This theory in abstract spaces is a rapidly growing field with lot of applications in analysis as well as other branches of mathematics [33].

    Fixed point theory is a valuable tool for the existence of a solution of different kinds of integral as well as differential inclusions, such as [33,34,35]. Many authors provided a solution of different integral inclusions in this context, for instance see [30,36,37,38,39,40]. In this section, a Volterra-type integral inclusion as an application of Theorem 3.1 is studied.

    Consider Ω=C([0,1],R) as the space of all continuous functions defined on [0,1] and define the G-complete fuzzy b-metric on Ω by

    Fb(ξ,ϱ,α)=esupε[0,1]|ξ(ε)ϱ(ε)|2α

    for all α>0 and ξ,ϱΩ.

    Consider the integral inclusion:

    ξ(ε)u0G(ε,σ,ξ(σ))dσ+h(ε)forallε,σ[0,1]andh,ξC([0,1], (5.1)

    where G:[0,1]×[0,1]×RPcv(R) is a multivalued continuous function.

    For the above integral inclusion, we define a multivalued operator S:Ω^C0(Ω) by

    S(ξ(ε))={wΩ:wu0G(ε,σ,ξ(σ))dσ+h(ε),ε[0,1]}.

    The next result proves the existence of a solution of the integral inclusion (5.1).

    Theorem 5.1. Let S:Ω^C0(Ω) be the multivalued integral operator given by

    S(ξ(ε))={wΩ:wε0G(ε,σ,ξ(σ))dσ+h(ε),ε[0,1]}.

    Suppose the following conditions are satisfied:

    1) G:[0,1]×[0,1]×RPcv(R) is such that G(ε,σ,ξ(σ)) is lower semi-continuous in [0,1]×[0,1];

    2) For all ε,σ[0,1], f(ε,σ)Ω and for all ξ,ϱΩ, we have

    |G(ε,σ,ξ(σ))G(ε,σ,ϱ(σ))|2f2(ε,σ)|ξ(σ)ϱ(σ)|2,

    where f:[0,1][0,+) is continuous;

    3) There exists 0<k<1 such that

    supε[0,1]ε0f2(ε,σ)dσk.

    Then the integral inclusion (5.1) has the solution in Ω.

    Proof. For G:[0,1]×[0,1]×RPcv(R), it follows from Michael's selection theorem that there exists a continuous operator

    Gi:[0,1]×[0,1]×RR

    such that Gi(ε,σ,ξ(σ))G(ε,σ,ξ(σ)) for all ε,σ[0,1]. It follows that

    ξ(ε)ε0Gi(ε,σ,ξ(σ))dσ+h(ε))S(ξ(ε))

    hence S(ξ(ε)) and closed. Moreover, since h(ε) is continuous on [0,1], and G is continuous, their ranges are bounded. This means that S(ξ(ε)) is bounded and S(ξ(ε))^C0(Ω). For q,rΩ, there exist q(ε)S(ξ(ε)) and r(ε)S(ϱ(ε)) such that

    q(ξ(ε))={wΩ:wε0Gi(ε,σ,ξ(σ))dσ+h(σ),ε[0,1]}

    and

    r(ϱ(u))={wΩ:wε0Gi(ε,σ,ϱ(σ))dσ+h(ε),ε[0,1]}.

    It follows from item 5.1 that

    |Gi(ε,σ,ξ(σ))Gi(ε,σ,ϱ(σ))|2f2(ε,σ)|ξ(σ)ϱ(σ)|2.

    Now,

    esupt[0,1]|q(ε)r(ε))|2kαesupε[0,1]ε0|Gi(ε,σ,ξ(σ))Gi(ε,σ,ϱ(σ))|2dσkαesupε[0,1]ε0f2(ε,σ)|ξ(σ)ϱ(σ)|2dσkαe|ξ(σ)ϱ(σ)|2supε[0,1]ε0f2(ε,σ)dσkαek|ξ(σ)ϱ(σ)|2kα=e|ξ(σ)ϱ(σ)|2αesupσ[0,1]|ξ(σ)ϱ(σ)|2α=Fb(ξ,ϱ,α).

    So, we have

    Fb(q,r,kα)Fb(ξ,ϱ,α).

    By interchanging the roll of ξ and ϱ, we reach to

    ΘFb(Sξ,Sϱ,kα)Fb(ξ,ϱ,α).

    Hence, S has a fixed point in Ω, which is a solution of the integral inclusion (5.1).

    In this article we proved certain fixed point results for Hausdorff fuzzy b-metric spaces. The main results are validated by an example. Theorem 3.2 generalizes the result of [25]. These results extend the theory of fixed points for multivalued mappings in a more general class of fuzzy b-metric spaces. For instance, some fixed point results can be obtained by taking b=1 (corresponding to G-complete FMSs). An application for the existence of a solution for a Volterra type integral inclusion is also provided.

    The author Aiman Mukheimer would like to thank Prince Sultan University for paying APC and for the support through the TAS research LAB.

    The authors declare no conflict of interest.



    [1] A. J. Lotka, Elements of Physical Biology, Philadelphia: Williams & Wilkins, 1925.
    [2] V. Volterra, Variazone e fluttuazini del numero d'individui in specie animali conviventi, Mem. Accad. Naz. Lincei. Ser. 6, 1926.
    [3] P. H. Leslie, Some further notes on the use of matrices in population dynamics, Biometrika, 35 (1948), 213–245.
    [4] M. L. Rosenzweig, R. H. MacArthur, Graphical representation and stability conditions of predator-prey interactions, Amer. Natur., 97 (1963), 209–223.
    [5] Y. Kuang, Basic properties of mathematical population models, J. Biomath., 17 (2002), 129–142.
    [6] M. A. Aziz-Alaoui, M. D. Okiye, Boundedness and global stability for a predator-prey model with modified Leslie-Gower and Holling-type Ⅱ schemes, Appl. Math. Lett., 16 (2003), 1069–1075. https://doi.org/10.1016/S0893-9659(03)90096-6 doi: 10.1016/S0893-9659(03)90096-6
    [7] Y. Abu Hasan, J. Alebraheem, Functional and numerical response in prey-predator system, AIP Conf. Proc., 1651 (2015), 3–11. https://doi.org/10.1063/1.4914425 doi: 10.1063/1.4914425
    [8] C. S. Holling, Some characteristics of simple types of predation and parasitism, Can. Entomol., 91 (1959), 385–398. https://doi.org/10.4039/Ent91385-7 doi: 10.4039/Ent91385-7
    [9] P. H. Crowley, E. K. Martin, Functional responses and interference within and between year classes of a dragonfly population, J. North Amer. Benthol. Soc., 8 (1989), 211–221.
    [10] Y. Kuang, E. Beretta, Global qualitative analysis of a ratio-dependent predator-prey system, J. Math. Biol., 36 (1998), 389–406. https://doi.org/10.1007/s002850050105 doi: 10.1007/s002850050105
    [11] J. Yen, Effects of prey concentration, prey size, predator life stage, predator starvation, and season on predation rates of the carnivorous copepod Euchaeta elongata, Mar. Biol., 75 (1983), 69–77. https://doi.org/10.1007/BF00392632 doi: 10.1007/BF00392632
    [12] P. J. Sullivan, Effect of boundary conditions, region length, and diffusion rates on a spatially heterogeneous predator-prey system, Ecol. Model., 43 (1988), 235–249. https://doi.org/10.1016/0304-3800(88)90006-3 doi: 10.1016/0304-3800(88)90006-3
    [13] P. A. Abrams, The effects of adaptive behavior on the type‐2 functional response, Ecology, 71 (1990), 877–885. https://doi.org/10.2307/1937359 doi: 10.2307/1937359
    [14] P. A. Abrams, L. Rowe, The effects of predation on the age and size of maturity of prey, Evolution, 50 (1996), 1052–1061. https://doi.org/10.1111/j.1558-5646.1996.tb02346.x doi: 10.1111/j.1558-5646.1996.tb02346.x
    [15] H. W. Hethcote, W. Wang, L. Han, Z. Ma, A predator-prey model with infected prey, Theor. Popul. Biol., 66 (2004), 259–268. https://doi.org/10.1016/j.tpb.2004.06.010 doi: 10.1016/j.tpb.2004.06.010
    [16] J. Alebraheem, Fluctuations in interactions of prey predator systems, Sci. Int., 28 (2016), 2357–2362.
    [17] F. Al Basir, P. K. Tiwari, S. Samanta, Effects of incubation and gestation periods in a prey–predator model with infection in prey, Math. Comput. Simul., 190 (2021), 449–473. https://doi.org/10.1016/j.matcom.2021.05.035 doi: 10.1016/j.matcom.2021.05.035
    [18] T. Gard, Introduction to Stochastic Differential Equations, New York: Dekker, 1988.
    [19] X. Mao, Stochastic Differential Equations and Applications, Amsterdam: Elsevier, 2007.
    [20] X. Mao, G. Marion, E. Renshaw, Environmental Brownian noise suppresses explosions in population dynamics, Stoc. Proc. Appl., 97 (2002), 95–110. https://doi.org/10.1016/S0304-4149(01)00126-0 doi: 10.1016/S0304-4149(01)00126-0
    [21] X. Mao, S. Sabanis, E. Renshaw, Asymptotic behaviour of the stochastic Lotka-Volterra model, J. Math. Anal. Appl., 287 (2003), 141–156. https://doi.org/10.1016/S0022-247X(03)00539-0 doi: 10.1016/S0022-247X(03)00539-0
    [22] K. Wang, Y. Zhu, Dynamics of a stochastic predator-prey model with mutual interference, Int. J. Biomath., 7 (2014), 1450026. https://doi.org/10.1142/S1793524514500260 doi: 10.1142/S1793524514500260
    [23] J. Alebraheem, Paradox of enrichment in a stochastic predator-prey model, J. Math., 2020 (2020), 8864999. https://doi.org/10.1155/2020/8864999 doi: 10.1155/2020/8864999
    [24] J. Alebraheem, N. S. Elazab, M. Mohammed, A. Riahi, A. Elmoasry, Deterministic sudden changes and stochastic fluctuation effects on stability and persistence dynamics of two-predator one-prey model, J. Math., 2021 (2021), 6611970. https://doi.org/10.1155/2021/6611970 doi: 10.1155/2021/6611970
    [25] D. Mukherjee, The effect of refuge and immigration in a predator-prey system in the presence of a competitor for the prey, Nonlinear Anal. Real World Appl., 31 (2016), 277–287. https://doi.org/10.1016/j.nonrwa.2016.02.004 doi: 10.1016/j.nonrwa.2016.02.004
    [26] J. Alebraheem, Dynamics of a predator-prey model with the effect of oscillation of immigration of the prey, Diversity, 13 (2021), 23. https://doi.org/10.3390/d13010023 doi: 10.3390/d13010023
    [27] T. Tahara, M. K. A. Gavina, T. Kawano, J. M. Tubay, J. F. Rabajante, H. Ito, et al., Asymptotic stability of a modified Lotka-Volterra model with small immigrations, Sci. Rep., 8 (2018), 7029. https://doi.org/10.1038/s41598-018-25436-2 doi: 10.1038/s41598-018-25436-2
    [28] J. Alebraheem, Relationship between the paradox of enrichment and the dynamics of persistence and extinction in prey-predator systems, Symmetry, 10 (2018), 532. https://doi.org/10.3390/sym10100532 doi: 10.3390/sym10100532
    [29] J. Alebraheem, Y. Abu-Hassan, A novel mechanism measurement of predator interference in predator-prey models, J. Math. Biol., 86 (2023), 84. https://doi.org/10.1007/s00285-023-01914-8 doi: 10.1007/s00285-023-01914-8
    [30] D. Cioranescu, P. Donato, M. P. Roque, An Introduction to Second Order Partial Differential Equations: Classical and Variational Solutions, Singapore: World Scientific, 2018.
    [31] V. N. Afanasiev, V. Kolmanovskii, V. R. Nosov, Mathematical Theory of Control Systems Design, Berlin: Springer, 2013.
    [32] K. L. Cottingham, J. A. Rusak, P. R. Leavitt, Increased ecosystem variability and reduced predictability following fertilisation: evidence from palaeolimnology, Ecol. Lett., 3 (2000), 340–348. https://doi.org/10.1046/j.1461-0248.2000.00158.x doi: 10.1046/j.1461-0248.2000.00158.x
  • This article has been cited by:

    1. Sorin Nădăban, Fuzzy quasi-b-metric spaces, 2022, 58, 1841-3307, 38, 10.2478/awutm-2022-0015
    2. Samina Batul, Faisar Mehmood, Azhar Hussain, Reny George, Muhammad Sohail Ashraf, Some results for multivalued mappings in extended fuzzy b-metric spaces, 2022, 8, 2473-6988, 5338, 10.3934/math.2023268
    3. Rashid Ali, Faisar Mehmood, Aqib Saghir, Hassen Aydi, Saber Mansour, Wajdi Kallel, Solution of integral equations for multivalued maps in fuzzy b-metric spaces using Geraghty type contractions, 2023, 8, 2473-6988, 16633, 10.3934/math.2023851
    4. Gunaseelan Mani, Poornavel Subbarayan, Zoran D. Mitrović, Ahmad Aloqaily, Nabil Mlaiki, Solving Some Integral and Fractional Differential Equations via Neutrosophic Pentagonal Metric Space, 2023, 12, 2075-1680, 758, 10.3390/axioms12080758
    5. Salvador Romaguera, Concerning Fuzzy b-Metric Spaces †, 2023, 11, 2227-7390, 4625, 10.3390/math11224625
    6. Shumin Lu, Ning Lu, Jianying Zhang, Fei He, Answer to a question on Cauchy sequence in fuzzy b-metric spaces and its applications, 2025, 2025, 1029-242X, 10.1186/s13660-025-03289-4
  • Reader Comments
  • © 2024 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(991) PDF downloads(69) Cited by(0)

Figures and Tables

Figures(13)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog