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New extension to fuzzy dynamic system and fuzzy fixed point results with an application

  • In this paper we introduce the notion of fuzzy dynamic system in b -metric-like space. By applying this, discuss some new refinements of the F-fuzzy Suzuki-type fixed point results for the fuzzy operators are presented. Also, establish the concept fuzzy dynamic system instead of the Piscard iterative sequence, which improves the existing results for such analysis as those presented here. Includes some tangible instances and an application are given to highlight the usability and validity of the theoretical results.

    Citation: Amjad Ali, Eskandar Ameer, Suhad Subhi Aiadi, Muhammad Tariq, Muhammad Arshad, Nabil Mlaiki, Wasfi Shatanawi. New extension to fuzzy dynamic system and fuzzy fixed point results with an application[J]. AIMS Mathematics, 2023, 8(1): 1208-1229. doi: 10.3934/math.2023061

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  • In this paper we introduce the notion of fuzzy dynamic system in b -metric-like space. By applying this, discuss some new refinements of the F-fuzzy Suzuki-type fixed point results for the fuzzy operators are presented. Also, establish the concept fuzzy dynamic system instead of the Piscard iterative sequence, which improves the existing results for such analysis as those presented here. Includes some tangible instances and an application are given to highlight the usability and validity of the theoretical results.



    Dynamic process is a mightful formalistic apparatus for association with a large spectrum analysis of multistage decision making problems. Such problems appear and are congruent in essentially all human activities. Unfavourably, for explicit reasons, the analysis of fuzzy dynamic process is difficult. Fuzzy dynamic process are characteristic of all dynamic process where the variables associated are state and decision variables. Fuzzy dynamic iterative process is established as a process getting preprocessed inputs and having outputs that are furthermore defuzzified for realistic applications.

    In the light of epistemic access, the term fuzzy sets appear as descriptions or perceptions of nonexistent underlying crisp values. As an example, it is noted that the temperature was high form but the numerical value is uncharted. This leads the way, to a number of classical problems which usually provide themselves to fuzzification fashions like Zadeh's generalization theorem [19].

    In functional analysis, the field Banach fixed point theory originate as an imperative apparatus over the last some decades in non-linear sciences and engineering via behavioral science, economics, etc see ([4,6,7,8,11,12,14,16,20,21,23,24,25,26,29,31]). To be unequivocal, while codifying an experiment mathematically, many number of researchers to interrogate the solvability of a functional equation in terms of differential equations, integral equations, or fractional differential equations. Such as the existence and uniqueness of a solution are often achieved by finding fixed point of a particular contraction mapping, (see more [1,3,9,10,13,15,18,30]). The three major structure in Banach fixed point theory are metric structure, topological structure, and discrete structure. These idea was extend by either generalized metric spaces into by modifying the structure of the contraction operators. However, Nadler [22] display the concept of Hausdorff metric discoursed the Banach fixed point theory for multi-valued mapping rather than single-valued mappings.

    On the other hand, Alghamdi et al. [2] improved the idea of partial metric space to b-metric-like space. They produced interesting theorems of fixed point in the newly defined frame. Their concept was expedited by various researchers in many ways (see more [17,27,28]).

    This article regards fuzzy dynamic process as fuzzy dynamic process on b -metric-like space, specifically the mapping of set-valued (extended) fuzzy intervals endowed with the b-metric-like. From that point of view, a natural topic is convergence theorems via fuzzy dynamic process in the class of b -metric-like space. Our view of convergence theorems in b -metric-like space, then, disposes of fuzzy dynamic process entirely. Instead, we just adopt the standard setting of fuzzy dynamic process in b -metric-like space which defines convergence theorems in generalized F-contraction via expectations of fuzzy Suzuki Hardy Rogers type contraction operators. Subsequently, corollaries are originated from the main result. To explain the example in the main section, a table and diagram has been created that best illustrates the Fuzzy dynamic process to the readers. At the end, gives an application of our results in solving Hukuhara differentiability through the fuzzy initial valued problem and fuzzy functions. The pivotal role of Hukuhara differentiability in Fuzzy dynamic process is stated. At last, a summary of the article is described in the conclusion section.

    Formally, an fuzzy set is defined as [32]:

    A fuzzy set on G is a mapping that assigns every value of G to some element in [0,1]. The family of all such mappings is expressed as F(G). For a fuzzy set A on G and </p><p>μ</p><p>∈G, the value A(</p><p>μ</p><p>) is known as the membership grade of </p><p>μ</p><p> in A. The αlevel set of A expressed as [A]α is given by

    {[A]α={μ:A(μ)α},α(0,1];[A]0=¯{μ:A(μ)>0}.

    For a nonempty set G and an ms G, a mapping T:GF(G) is a fuzzy mapping and is a fuzzy subset of G×G having the membership function T(g)(g). T(g)(g) describes the membership grade of g in T(g), while [T(g)]α states the αlevel set of T(g), for more details see [5].

    Definition 2.1. [5] A point gG is called a fuzzy fixed point of a fuzzy mapping T:GF(G) if there is α(0,1] such that g[T(g)]α.

    In the recent past, Wardowski [31] provided the term known as F-contraction and implemented on Banach fixed point theory. Which is the efficient generalization of Banach fixed point theory. Formally, an F-contraction is defined as follows [31]:

    Definition 2.2. Let F is the set of mappig F:R+R satisfying (Fi)(Fiii):

    (Fi) μ1<μ2 implies F(μ1)<F(μ2)forallμ1,μ2(0,+);

    (Fii) For every sequence {μσ} in R+ such that

    limσ+μσ=0ifandonlyiflimσ+F(μσ)=;

    (Fiii) There exist k(0,1) such that limμ0()μkF(μ)=0.

    A mapping T:GG is called an F-contraction on a metric space (G,d), if there is τR+/{0} such that

    d(Tμ1,Tμ2)>0τ+F(Tμ1,Tμ2)F(d(μ1,μ2))foreachμ1,μ2G.

    After, we recall the following some basic idea of dynamic system:

    Let ξ:GC(G) be a mapping. A set

    ˇD(ξ,μ0)={(μa)a0:μaξμa1  forallaN}.

    is called dynamic process ˇD(ξ,μ0) of μ with starting point μ0. Where μ0G be arbitrary and fixed. In the light of ˇD(ξ,μ0), (μa)aN{0} onward has the form (μa) (see more [18]).

    Further, the literature contains many generalizations of the idea of fixed point theory in metric spaces and its topological behavior. In particularly, Alghamdi et al. [2] designed the fashion of b-metric-like space as follows:

    Definition 2.3. [2] Let G be a b -metric-like space with Gϕ and s1. A function d:G×GR+{0} such that for every μ1,μ2,μ3G, the following conditions (bi), (bii) and (biii) hold true:

    (bi) the condition: d(μ1,μ2)=0 implies μ1=μ2;

    (bii) the condition is hold true: d(μ1,μ2)=d(μ2,μ1);

    (biii) the condition is satisfied: d(μ1,μ3)s[d(μ1,μ2)+d(μ2,μ3)].

    The pair (G,d) is known as a b -metric-like space.

    Example 2.4. Define (G,d) with s=2 by\newline

    d(0,0)=0,d(1,1)=d(2,2)=d(0,2)=2,d(0,1)=4,d(1,2)=1,

    with

    d(μ1,μ2)=d(μ2,μ1),

    for all μ1,μ2G={0,1,2}. Then, (G,d) is a b -metric-like space. Clearly, it is neither a b-metric nor a metric-like space, see more detail in [2].

    Remark 2.5. Owing to above definition (2.3), every partial metric is a b -metric-like space but converse may not hold true in general, see more [2]

    Nadler [22], design the idea of Hausdorff metric and extended the Banach contraction theorem for multi-valued operators instead of single-valued operators. Hereinafter, we investigate the concept of Hausdorff b-metric-like as follows. Let (G,μ) be a b-metric-like space. For μ1G and L1G, let db(μ1,L2)=inf{d(μ1,μ2):μ2L2}. Define ^Hb:CB(G)×CB(G)[0,+) by

    ^Hb(L1,L2)=max{supμ1L1db(μ1,L2),supμ2L2db(μ1,L1)},

    for each L1,L2CB(G). Where CB(G) denote the family of all non-empty closed and bounded-subsets of G and CL(G) the family of all non-empty closed-subsets of G.

    Definition 2.6. [5] Let L1,L2V(G), α(0,1]. Then dα(L1,L2)=infgL1α,gL2αd(g,g),

    Hα(L1,L2)=ˆHbl(L1α,L2α),

    where ˆHbl is the Hausdorff distance.

    Lemma 2.7. Let L1 and L2 be nonempty proximal subsets of a b -MLS (G,d). If gL1, then

    d(g,L2)H(L1,L2).

    Lemma 2.8. Let (G,d) be a b -metric-like space. For all L1,L2CB(G) and for any gL1 such that d(g,L2)=d(g,g), where gL2. Then, ˆHbl(L1,L2)d(g,g).

    In the following, the concept of fuzzy dynamic process as a generalization of dynamic process, and some elementary facts about these concepts are discussed.

    In this section, first we deal with some new aspects of the fuzzy dynamic process as follows:

    Definition 3.1. Let T:GF(G) be a fuzzy mapping. If there is α(0,1], and let μ0G be arbitrary and fixed such that

    ˇD([Tμ]α,μ0)={(μj)jN{0}:μj[Tμj1]α,jN}.

    Every membership value of ˇD([Tμ]α,μ0) is called a fuzzy dynamic process of T starting point μ0. The fuzzy dynamic process (μj)jN{0} onward is written as (μj).

    Example 3.2. Let G=C([0,1]) be a Banach space with norm μ=supr[0,1]|μ(r)| for μG. Let T:GF(G) be a fuzzy mapping. If there is α(0,1] such that for every μG, [Tμ]α is a set of the function

    δkδ0μ(r)dr,k[0,1],

    that is,

    ˇD([Tμ]α(δ),μ0)={kδ0μ(r)dr:k[0,1]},μG,

    and let μ0(δ)=δ, δ[0,1]. Then the iterative sequence

    μj={(1j!(j+1)!δj+1),j0;0elsewehere.

    is a fuzzy dynamic process of mapping T with starting point μ0. The mapping T:GF(R) is said to be ˇD([Tμ]α,μ0) fuzzy dynamic lower semi-continuous at μG, if for every fuzzy dynamic process (μj)D(T,μ0) and for every subsequence (μj(i)) of (μj) convergent to μ

    [Tμ]αliminfi+[Tμj(i)]α.

    In this case, T is fuzzy dynamic lower semi-continuous ˇD([Tμ]α,μ0). If T is fuzzy dynamic lower semi-continuous ˇD([Tμ]α,μ0) at each μG, then T is known as lower semi-continuous. For every sequence (μj)G and μG such that (μj)μ, we have [Tμ]αliminfi+[Tμ(j)]α.

    Example 3.3. Let G=R+{0}. Define T:GF(G) by

    T(μ)(μ)={1,if0μμ4;12,ifμ4<μμ3;14,ifμ3<μμ2;0,ifμ2<μ1.

    all μG, there is α(μ)=1 such that [Tμ]α(μ)=[0,μ2]. Apply the following iterative procedure to generate a sequence {μn} of fuzzy sets is given by (see Table 1 and Figure 1)

    μi={μ0hi1,ifi2;0,elsewhere.
    Table 1.  Fuzzy dynamic process.
    i2 μi=μ0gi1 [Tμ]α(μ)=[0,μ2]
    μi=2 1 [Tμ1]α(μ1)=[0,1]
    μi=3 12 [Tμ2]α(μ2)=[0,12]
    μi=4 14 [Tμ3]α(μ3)=[0,14]
    μi=5 18 [Tμ3]α(μ4)=[0,18]
    μi=6 116 [Tμ3]α(μ5)=[0,116]
    μi=7 132 [Tμ3]α(μ6)=[0,132]
    μi=8 164 [Tμ3]α(μ7)=[0,164]
    μi=9 1128 [Tμ3]α(μ8)=[0,1128]
    μi=10 1256 [Tμ4]α(μ9)=[0,1256]

     | Show Table
    DownLoad: CSV
    Figure 1.  Fuzzy dynamic process: ˇD([Tμ]α,μ0).

    Where μ0=2 is intial point and h=12.

    We obtain,

    ˇD([Tμ]α,μ0)={12,14,18,116,132,164,1128,1256}

    is a fuzzy dynamic process of T starting at point μ0=2.

    Further, in the following we develop fuzzy fixed point theorems with respect to fuzzy dynamic process ˇD([Tμ]α,μ0) as follows.

    Now, we start with the following main definition:

    Definition 4.1. Let (G,d) be a b -metric-like space with s1. A mapping T:GF(G) is called a F-fuzzy Suzuki-Hardy-Rogers (abbr., F-FSHR) type contraction with respect to ˇD([Tμ]α,μ0) and α:G(0,1] such that [Tμi]α(i) are nonempty closed subsets of G if for some Fϝ and τ:(0,+)(0,+) such that

    12sdb(μi1,[Tμi1]α(i1))d(μi1,μi),

    we have

    τ(U(μi1,μi))+F[^Hb([Tμi]α(i),[Tμi+1]α(i+1))]F(U(μi1,μi)), (4.1)

    where

    U(μi1,μi)=e1[d(μi1,μi)]+e2[db(μi1,[Tμi1]α(i1))]+e3[db(μi,[Tμi]α(i))]+e42s[db(μi1,[Tμi]α(i))]+e52s[db(μi,[Tμi1]α(i1))],

    for all μiˇD([Tμ]α,μ0), ˆHb([Tμi]α(i),[Tμi+1]α(i+1))>0, where e1,e2,e3,e4,e5[0,1] such that e1+e2+e3+e4+e5=1 and 1e3e5>0.

    Remark 4.2. To continue with our results, the behavior of self distance in b-metric-like space is defined by

    d(μ1,μ1)2d(μ1,μ2).

    Additionally, we assume that μiˇD([Tμ]α,μ0) satisfying fuzzy dynamic process for below condition:

    db(μi,[Tμi])α(i)>0,db(μi1,[Tμi1]α(i1))>0, (4.2)

    for all iN. If for the investigated process that does not satisfy (4.2), there is some i0N such that

    db(μi0,[Tμi0]α(i0))>0,

    and

    db(μi01,[Tμi01]α(i01))=0,

    then we get μi01=μi0[Tμi01]α(i01) which implies the existence of fuzzy fixed point. In the light of this consideration, fuzzy dynamic process satisfying (4.2) does not depreciate a generality of our analysis.

    Now, we proceed to our main result:

    Theorem 4.3. Let (G,d,s) be a complete b -metric-like space. Let T:Gμα(G) be an F-FSHR type contraction with respect to μi. Assume that the following holds:

    (i) There is a fuzzy dynamic iterative process μiˇD([Tμ]α,μ0) such that for each l0 liminfkl+τ(k)>0;

    (ii) A mapping Gμidb(μi,[Tμi]α(i)) is fuzzy dynamic lower semi-continuous ˇD([Tμ]α,μ0);

    (iii) If, in addition, Fis super-additive, i.e., for μ1,μ2,ξ1,ξ2R+ we have

    F(ξ1μ1+ξ2μ2)ξ2F(μ1)+ξ2F(μ2).

    Then T has a fuzzy fixed point.

    Proof. Choose an arbitrary point μ0G. In veiw of fuzzy dynamic iterative process, we have

    ˇD([Tμ]α,μ0)={(μi)iN{0}:μi+1=μi[Tμi1]α(i1)foralliN}.

    In case that there is i0N such that μi0=μi0+1, then our proof of Theorem (4.3) go ahead as follows. If we let μiμi+1 for all iN, then we have

    12sdb(μi,[Tμi]α(i))d(μi,μi+1),foralliN. (4.3)

    From (4.1) and in the light of Lemma (2.8), we have

    F(d(μi+1,μi+2)F[^Hb([Tμi]α(i),[Tμi+1]α(i+1))]F[e1d(μi,μi+1)+e2db(μi,[Tμi]α(i))+e3db(μi+1,[Tμi+1]α(i+1))+e42sdb(μi,[Tμi+1]α(i+1))+e52sdb(μi+1,[Tμi]α(i))]τ[e1d(μi,μi+1)+e2db(μi,[Tμi]α(i))+e3db(μi+1,[Tμi+1]α(i+1))+e42sdb(μi,[Tμi+1]α(i+1))+e52sdb(μi+1,[Tμi]α(i))]. (4.4)

    Now, we survey to the following inequality

    db(μi+1,[Tμi+1]α(i+1))<db(μi,[Tμi]α(i)), (4.5)

    for all iN. Suppose, on the contrary, there is i0N such that d(μi0+1,[Tμi0+1]α(i0+1))d(μi0,[Tμi0]α(i0)). By (4.4) and Lemma (2.8), we have

    F[db(μi0+1,[Tμi0+1]α(i0+1))]=F[d(μi0+1,μi0+2)]F[ˆHb([T(μi0)]α(i0),[T(μi0+1)]α(i0+1))]τ(U(μi0,μi0+1))F[e1(db(μi0,[T(μi0)]α(i0)))+e2(db(μi0,[T(μi0)]α(i0)))+e3(db(μi0+1,[T(μi0+1)]α(i0+1)))+e42s(db(μi0,[T(μi0+1)]α(i0+1)))+e52s(db(μi0+1,[T(μi0)]α(i0)))]τ(U(μi0,μi0+1))F[e1db(μi0,[T(μi0)]α(i0))+e2(db(μi0,[T(μi0)]α(i0)))+e3(db(μi0+1,[T(μi0+1)]α(i0+1)))+se42sdb(μi0,[T(μi0)]α(i0))+se42sdb([T(μi0)]α(i0),[T(μi0+1)]α(i0+1))+2se52s(db(μi0,[T(μi0)]α(i0))]τ(U(μi0,μi0+1)). (4.6)

    Owing to the above hypothesis, this, in turn, yields:

    F[db(μi0+1,[Tμi0+1]α(i0+1))]F[e1db(μi0,[T(μi0)]α(i0))+e2(db(μi0,[T(μi0)]α(i0)))+e3(db(μi0+1,[T(μi0+1)]α(i0+1)))+e4(db([T(μi0)]α(i0),[T(μi0+1)]α(i0+1)))+e5(db(μi0,[T(μi0)]α(i0)))]τ(U(μi0,μi0+1)).

    Since F is super-additive, we can write

    F[db(μi0+1,[Tμi0+1]α(i0+1))](e1+e2+e5)(1e3e4)F[db(μi0,[Tμi0]α(i0))]τ(U(μi01,μi0))(1e3e4).

    From this, By given condition e1+e2+e3+e4+e5=1, we have

    F[db(μi0+1,[Tμi0+1]α(i0+1))]F[db(μi0,[Tμi0]α(i0))]τ(U(μi01,μi0))(1e3e4), (4.7)

    a contradiction. Hence (4.5) holds true. In the light of above hypothesis, Therefore db(μi,[Tμi]α(i)) is a decreasing sequence with respect to real number and it is bounded from below. Suppose that there is Ψ0 such that

    Ψ=limi+db(μi,[Tμi]α(i))=inf{db(μi,[Tμi]α(i)):iN}. (4.8)

    We now to prove that Ψ=0. Suppose, based on contrary that Ψ>0. Then, for every ε>0, there is a natural number j such that

    db(μj,[Tμj]α(j))<Ψ+ε.

    By (Fi),

    F[db(μj,[Tμj]α(j))]<F(Ψ+ε). (4.9)

    Also, by applying (4.3), we have

    12sdb(μj,[Tμj]α(j))db(μj,μj+1),foralliN.

    Since F-FSHR type contraction with respect to ˇD(T,μ0), we have

    F[db(μj+1,[Tμj+1]α(j+1))]=F[d(μj+1,μj+2)]F[ˆHb([T(μj)]α(j),[T(μj+1)]α(j+1))]τ(U(μj,μj+1))F[e1(db(μj,[T(μj)]α(j)))+e2(db(μj,[T(μj)]α(j)))+e3(db(μj+1,[T(μj+1)]α(j+1)))+e42s(db(μj,[T(μj+1)]α(j+1)))+e52s(db(μj+1,[T(μj)]α(j)))]τ(U(μj,μj+1)).

    Due to the above hypothesis, this, in turn, yields:

    F[db(μj+1,[Tμj+1]α(j+1))]F[e1db(μj,[T(μj)]α(j))+e2(db(μj,[T(μj)]α(j)))+e3(db(μj+1,[T(μj+1)]α(j+1)))+se42sdb(μj,[T(μj)]α(j))+se42sdb([T(μj)]α(j),[T(μj+1)]α(j+1))+2se52s(db(μj,[T(μj)]α(j))]τ(U(μj,μj+1))F[e1db(μj,[T(μj)]α(j))+e2(db(μj,[T(μj)]α(j)))+e3(db(μj+1,[T(μj+1)]α(j+1)))+e4(db(μj,[T(μj)]α(j)))+e5(db(μj,[T(μj)]α(j)))]τ(U(μj,μj+1)).

    This implies

    F[db(μj+1,[Tμj+1]α(j+1))]F[db(μj,[Tμj]α(j))]τ(U(μj,μj+1))1e3.

    Since

    12sdb(μj+1,[Tμj+1]α(j+1))db(μj+1,μj+2),foralliN.

    By appealing to above observation, we obtain

    F[db(μj+2,[Tμj+2]α(j+2))]F[db(μj+1,[Tμj+1]α(j))]τ(U(μj+1,μj+2))1e3. (4.10)

    Continuing these fashion, we obtain

    F[db(μj+i,[Tμj+i]α(j+i))]F[db(μj+(i1),[Tμj+(i1)]α(j+(i1)))]τ(U(μj+(i1),μj+i))1e3F[db(μj+(i2),[Tμj+(i2)]α(j+(i2)))]{τ(U(μj+(i2),μj+(i1)))1e3+τ(U(μj+(i1),μj+i))1e3F[db(μj0,[Tμj0]α(j0))](nj0)τ(U(μj01,μj0))1e3<F(Ψ+ε)(nj0)τ(U(μj01,μj0))1e3. (4.11)

    Upon setting i+, we have 

    limi+F[db(μj+i,[Tμj+i]α(j+i))]=.

    Also, in veiw of (Fii), we get

    limi+[db(μj+i,[Tμj+i]α(j+i))]=0.

    So, there is i1N such that db(μj+i,[Tμj+i]α(j+i))<Ψ for all i>i1, which is a contradiction with repect to Ψ. Therefore, we have

    limi+[db(μi,[Tμi]α(i))]=0. (4.12)

    Now, we show that

    limi,m+d(μi,μm)=0. (4.13)

    Let us assume on the contrary that, for every \varepsilon > 0 there are sequences \gamma (i) and \delta (i) in {\mathbb{N}} such that

    \begin{equation} d(\mu _{\gamma _{(i)}},\mu _{\delta _{(i)}})\geq \varepsilon {\rm{, }} d_{b}\left( \mu _{\delta _{(i)-1}},\left[ T\mu _{\gamma _{(i)-1}}\right] _{\alpha \left( \gamma _{(i)-1}\right) }\right) < \varepsilon {\rm{, }}\gamma (i) > \delta (i) > i, \end{equation} (4.14)

    for all i\in {\mathbb{N}} . So, we have

    \begin{eqnarray} d(\mu _{\gamma _{(i)}},\mu _{\delta _{(i)}}) &\leq &sd_{b}\left( \mu _{\gamma _{(i)-1}},\left[ T\mu _{\gamma _{(i)-1}}\right] _{\alpha \left( \gamma _{(i)-1}\right) }\right) +sd_{b}\left( \left[ T\mu _{\gamma _{(i)-1}}\right] _{\alpha \left( \gamma _{(i)-1}\right) },\mu _{\delta _{(i)}}\right) \\ & < &sd_{b}\left( \mu _{\gamma _{(i)}},\left[ T\mu _{\gamma _{(i)-2}}\right] _{\alpha \left( \gamma _{(i)-2}\right) }\right) +s\varepsilon . \end{eqnarray} (4.15)

    By (4.12), \exists i_{2}\in {\mathbb{N}} such that

    \begin{equation} d_{b}\left( \mu _{\gamma _{(i)-1}},\left[ T\mu _{\gamma _{(i)-1}}\right] _{\alpha \left( \gamma _{(i)-1}\right) }\right) < \varepsilon ,{\rm{ }} d_{b}\left( \mu _{\gamma _{(i)}},\left[ T\mu _{\gamma _{(i)}}\right] _{\alpha \left( \gamma _{(i)}\right) }\right) < \varepsilon ,{\rm{ }}d_{b}\left( \mu _{\delta _{(i)}},\left[ T\mu _{\delta _{(i)}}\right] _{\alpha \left( \delta _{\left( i\right) }\right) }\right) < \varepsilon, \end{equation} (4.16)

    for all i > i_{2} , which together with (4.15) yields

    \begin{equation*} d(\mu _{\gamma _{(i)}},\mu _{\delta _{(i)}}) < 2s\varepsilon )\;{\rm{ for \;all }} \;i > i_{2}. \end{equation*}

    In view of (\mathcal{F}_{i}), we can write

    \begin{equation} \mathcal{F}\left( d(\mu _{\gamma _{(i)}},\mu _{\delta _{(i)}})\right) < \mathcal{F}(2s\varepsilon )\;{\rm{ for\; all }}\;i > i_{2}. \end{equation} (4.17)

    From (4.14) and (4.16), we write

    \begin{equation} \frac{1}{2s}d_{b}\left( \mu _{\gamma _{(i)}},\left[ T\mu _{\gamma _{(i)}}\right] _{\alpha \left( \gamma _{(i)}\right) }\right) < \frac{\varepsilon }{2s} < d(\mu _{\gamma _{(i)}},\mu _{\delta _{(i)}})\;{\rm{ for\; all }}\;i > i_{2}. \end{equation} (4.18)

    Applying the triangle inequality, we find that

    \begin{eqnarray} \epsilon \leq d(\mu _{\gamma _{(i)}},\mu _{\gamma _{(i)}}) &\leq &sd\left( \mu _{\gamma _{(i)}},\mu _{\gamma _{(i)+1}}\right) \\ &+&s^{2}d\left( \mu _{\gamma _{(i)+1}},\mu _{\delta _{(i)+1}}\right) +s^{2}d\left( \mu _{\delta _{(i)+1}},\mu _{\delta _{(i)}}\right) . \end{eqnarray} (4.19)

    Next, if we setting to the limit i\rightarrow +\infty in (4.19) and make use of (4.12), then,

    \begin{equation*} \frac{\epsilon }{s^{2}}\leq \lim\limits_{i\rightarrow +\infty }\inf d\left( \mu _{\gamma _{(i)+1}},\mu _{\delta _{(i)+1}}\right) . \end{equation*}

    Also, there is i_{3}\in {\mathbb{N}} such that

    \begin{equation*} d\left( \mu _{\gamma _{(i)+1}},\mu _{\delta _{(i)+1}}\right) > 0, \end{equation*}

    for all i > i_{3} , that is, d\left(\mu _{\gamma _{(i)+1}}, \mu _{\delta _{(i)+1}}\right) > 0 > 0 for i > i_{3}. Further, from (4.1) and Lemma (2.8), we can write

    \begin{eqnarray} &&\mathcal{F}\left[ d\left( \mu _{\gamma _{(i)+1}},\mu _{\delta _{(i)+1}}\right) \right] \leq \mathcal{F}\left( \hat{H}_{b}\left( \left[ T\mu _{\gamma _{(i)}}\right] _{\alpha \left( \gamma _{(i)}\right) },\left[ T\mu _{\delta _{(i)}}\right] _{\alpha \left( \delta _{(i)}\right) }\right) \right) -\tau (U(\mu _{\gamma \left( i\right) },\mu _{\delta \left( i\right) })) \\ &\leq &\mathcal{F}\left[ e_{1}(d(\mu _{\gamma \left( i\right) },\mu _{\delta \left( i\right) }))+e_{2}\left( d_{b}\left(\mu _{\gamma \left( i\right) }, \left[ T\mu _{\gamma _{(i)}}\right] _{\alpha \left( \gamma _{(i)}\right) }\right) \right) \right. \\ &&+e_{3}\left( d_{b}\left( \mu _{\delta \left( i\right) },\left[ T\mu _{\delta _{(i)}}\right] _{\alpha \left( \delta _{(i)}\right) }\right) \right) +e_{4}\left( d_{b}\left( \mu _{\gamma \left( i\right) },\left[ T\mu _{\delta _{(i)}}\right] _{\alpha \left( \delta _{(i)}\right) }\right) \right) \\ &&\left. +e_{5}\left( d_{b}\left( \mu _{\delta \left( i\right) },\left[ T\mu _{\gamma _{(i)}}\right] _{\alpha \left( \gamma _{(i)}\right) }\right) \right) \right] -\tau (U(\mu _{\gamma \left( i\right) },\mu _{\delta \left( i\right) })) \\ &\leq &\mathcal{F}\left[ e_{1}(d(\mu _{\gamma \left( i\right) },\mu _{\delta \left( i\right) }))+e_{2}\left( d_{b}\left(\mu _{\gamma \left( i\right) }, \left[ T\mu _{\gamma _{(i)}}\right] _{\alpha \left( \gamma _{(i)}\right) }\right) \right) \right. \\ &&+e_{3}\left( d_{b}\left( \mu _{\delta \left( i\right) },\left[ T\mu _{\delta _{(i)}}\right] _{\alpha \left( \delta _{(i)}\right) }\right) \right) +se_{4}\left( d\left( \mu _{\gamma \left( i\right) },\mu _{\delta \left( i\right) }\right) \right) \\ &&+se_{4}\left( d_{b}\left( \mu _{\delta \left( i\right) },\left[ T\mu _{\delta _{(i)}}\right] _{\alpha \left( \delta _{(i)}\right) }\right) \right) +se_{5}\left( d\left( \mu _{\delta \left( i\right) },\mu _{\gamma \left( i\right) }\right) \right) \\ &&\left. +se_{5}\left( d_{b}\left( \mu _{\gamma \left( i\right) },\left[ T\mu _{\gamma _{(i)}}\right] _{\alpha \left( \gamma _{(i)}\right) }\right) \right) \right] -\tau \left( U(\mu _{\gamma \left( i\right) },\mu _{\delta \left( i\right) })\right), \end{eqnarray} (4.20)

    for all i > \max \left \{ i_{1}, i_{2}\right \}. In view of (4.16)–(4.18), inequaility (4.20) yields

    \begin{eqnarray} \mathcal{F}\left[ d\left( \mu _{\gamma _{(i)+1}},\mu _{\delta _{(i)+1}}\right) \right] &\leq &\mathcal{F}\left( \hat{H}_{b}\left( \left[ T\mu _{\gamma _{(i)}}\right] _{\alpha \left( \gamma _{(i)}\right) }, \left[ T\mu _{\delta _{(i)}}\right] _{\alpha \left( \delta _{(i)}\right) }\right) \right) \\ &\leq &\mathcal{F}\left[ e_{1}(2s\varepsilon ))+e_{2}\left( d_{b}\left( d(\mu _{\gamma \left( i\right) },\left[ T\mu _{\gamma _{(i)}}\right] _{\alpha \left( \gamma _{(i)}\right) }\right) \right) \right. \\ &&+e_{3}\left( d_{b}\left( \mu _{\delta \left( i\right) },\left[ T\mu _{\delta _{(i)}}\right] _{\alpha \left( \delta _{(i)}\right) }\right) \right) \\ &&+\frac{e_{4}}{2}(s\varepsilon +s\varepsilon )+\frac{e_{5}}{2}(s\varepsilon +\varepsilon ))] \\ &&-\tau \left( U(\mu _{\gamma \left( i\right) },\mu _{\delta \left( i\right) }))\right), \end{eqnarray} (4.21)

    for all i > \max \left \{ i_{1}, i_{2}\right \} . Taking the limit i\rightarrow +\infty in (4.21), we get

    \begin{equation*} \lim\limits_{i\rightarrow +\infty }\mathcal{F}\left[ d\left( \mu _{\gamma _{(i)+1}},\mu _{\delta _{(i)+1}}\right) \right] = -\infty , \end{equation*}

    which by vertue of (\mathcal{F}_{ii}), implies that \lim_{i\rightarrow +\infty }d\left(\mu _{\gamma _{(i)+1}}, \mu _{\delta _{(i)+1}}\right) = 0 . In the light of (4.19), we can write \lim_{i\rightarrow +\infty }d(\mu _{\gamma _{(i)}}, \mu _{\delta _{(i)}}) = 0, which contradicts. Hence (4.13) holds true. Hence \{ \mu _{i}\} is a Cauchy sequence in G. Since G is a complete b -metric-like space, there is a point c\in G such that

    \begin{equation} d(c,c) = \lim\limits_{i\rightarrow +\infty }d(\mu _{i},c) = \lim\limits_{i,j\rightarrow +\infty }d(\mu _{i},\mu _{j}) = 0. \end{equation} (4.22)

    Now, we show futher the following inequatlity

    \begin{equation} \frac{1}{2s}d_{b}\left( \mu _{i},\left[ T\mu _{i}\right] _{\alpha \left( i\right) }\right) < d(\mu _{i},c){\rm{ or }}\frac{1}{2s}d_{b}\left( \mu _{i+1}, \left[ T\mu _{i+1}\right] _{\alpha \left( i+1\right) }\right) < d\left( \mu _{i+1},c\right) . \end{equation} (4.23)

    Assume on the contrary that \exists i_{0}\in {\mathbb{N}} such that

    \begin{equation} \frac{1}{2s}d_{b}(\mu _{i_{0}},\left[ T\mu _{i_{0}}\right] _{\alpha \left( i_{0}\right) })\geq d(\mu _{i_{0}},c),{\rm{ }}\frac{1}{2s}d_{b}\left( \mu _{i_{0+1}},\left[ T\mu _{i_{0}+1}\right] _{\alpha \left( i_{0}+1\right) }\right) \geq d\left( \mu _{i_{0}+1},c\right) . \end{equation} (4.24)

    Then from (4.5) and (4.24), we have

    \begin{eqnarray*} d_{b}\left( \mu _{i_{0}},\left[ T\mu _{i_{0}}\right] _{\alpha \left( i_{0}\right) }\right) &\leq &sd(\mu _{i_{0}},c)+sd_{b}\left( c,\left[ T\mu _{i_{0}}\right] _{\alpha \left( i_{0}\right) }\right) \\ &\leq &\frac{1}{2s}sd_{b}\left( \mu _{i_{0}},\left[ T\mu _{i_{0}}\right] _{\alpha \left( i_{0}\right) }\right) +\frac{1}{2s}sd_{b}\left( \mu _{i_{0+1}}, \left[ T\mu _{i_{0+1}}\right] _{\alpha \left( i_{0+1}\right) }\right) \\ &\leq &\frac{1}{2}d_{b}\left( \mu _{i_{0}},\left[ T\mu _{i_{0}}\right] _{\alpha \left( i_{0}\right) }\right) +\frac{1}{2}d_{b}\left( \mu _{i_{0}},\left[ T\mu _{i_{0}}\right] _{\alpha \left( i_{0}\right) }\right) \\ &\leq &d_{b}\left( \mu _{i_{0}},\left[ T\mu _{i_{0}}\right] _{\alpha \left( i_{0}\right) }\right) , \end{eqnarray*}

    a contradiction. Thus (4.23) holds true. So, we can write

    \begin{eqnarray} \mathcal{F}\left( d_{b}\left( \mu _{i+1},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) \right) &\leq &\mathcal{F}\left[ \hat{H} _{b}(\left[ T(\mu _{i})\right] _{\alpha \left( i\right) },\left[ T\left( c\right) \right] _{\alpha \left( c\right) })\right] -\tau \left( U(\mu _{i},c)\right) \\ &\leq &\mathcal{F}\left[ e_{1}(d(\mu _{i},c))+e_{2}d_{b}\left( \mu _{i},\left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) }\right) \right. \\ &&+e_{3}d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) +\frac{e_{4}}{2s}d_{b}\left( \mu _{i},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) \\ &&\left. +\frac{e_{5}}{2s}d_{b}\left( c,\left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) }\right) \right] -\tau \left( U(\mu _{i},c)\right), \end{eqnarray} (4.25)

    or

    \begin{eqnarray} \mathcal{F}\left( d\left( \mu _{i+2},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) \right) &\leq &\mathcal{F}\left[ \hat{H} _{b}(\left[ T(\mu _{i+1})\right] _{\alpha \left( i+1\right) },\left[ T\left( c\right) \right] _{\alpha \left( c\right) })\right] -\tau \left( U(\mu _{i},c)\right) \\ &\leq &\mathcal{F}\left[ e_{1}(d(\mu _{i+1},c))+e_{2}d_{b}\left( \mu _{i+1}, \left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) }\right) \right. \\ &&+e_{3}d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) +\frac{e_{4}}{2s}\left( \mu _{i+1},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) \\ &&\left. +\frac{e_{5}}{2s}d_{b}\left( c,\left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) }\right) \right] -\tau \left( U(\mu _{i+1},c)\right) . \end{eqnarray} (4.26)

    Now, let us now examine the following cases:

    Case 1. Assume that (4.25) holds true. From (4.25), we have

    \begin{eqnarray} \mathcal{F}\left( d_{b}\left( \mu _{i+1},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) \right) &\leq &\mathcal{F}\left[ \hat{H} _{b}(\left[ T(\mu _{i})\right] _{\alpha \left( i\right) },\left[ T\left( c\right) \right] _{\alpha \left( c\right) })\right] -\tau \left( U(\mu _{i},c)\right) \\ &\leq &\mathcal{F}\left[ e_{1}(d(\mu _{i},c))+e_{2}d_{b}\left( \mu _{i},\left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) }\right) \right. \\ &&+e_{3}d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) +\frac{e_{4}}{2}d_{b}\left( \mu _{i},c\right) \\ &&+\frac{e_{4}}{2}d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) +\frac{e_{5}}{2}d\left( c,\mu _{i}\right) \\ &&\left. +\frac{e_{5}}{2}d_{b}\left( \mu _{i},\left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) }\right) \right] -\tau \left( U(\mu _{i},c)\right) . \end{eqnarray} (4.27)

    By (4.12) and (4.22), there is i_{4}\in {\mathbb{N}} such that for some \varepsilon _{1} > 0

    \begin{equation} d(c,\mu _{i}) < \varepsilon _{1}{\rm{, }}d_{b}(\mu _{i},\left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) }) < \varepsilon _{1},\;{\rm{ for }}\; i > i_{4}. \end{equation} (4.28)

    From (4.27) and (4.28), we have

    \begin{eqnarray} \mathcal{F}\left( d_{b}\left( \mu _{i+1},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) \right) &\leq &\mathcal{F}\left[ \hat{H} _{b}(\left[ T(\mu _{i})\right] _{\alpha \left( i\right) },\left[ T\left( c\right) \right] _{\alpha \left( c\right) })\right] -\tau \left( U(\mu _{i},c)\right), \\ &\leq &\mathcal{F}\left[ e_{1}(d(\mu _{i},c))+e_{2}d_{b}\left( \mu _{i},\left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) }\right) \right. \\ &&+e_{3}d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) +\frac{e_{4}}{2}\left( \varepsilon _{1}\right) \\ &&+\frac{e_{4}}{2}d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) +e_{5}\left( \varepsilon _{1}\right) \\ &&-\tau \left( U(\mu _{i},c)\right), \end{eqnarray} (4.29)

    for all i > i_{4}. Taking the limit as i\rightarrow +\infty in (4.29), we find that \lim_{i\rightarrow +\infty }\mathcal{F}\left(d_{b}\left(\mu _{i+1}, \left[ T\left(c\right) \right] _{\alpha \left(c\right) }\right) \right) = -\infty . By means of (\mathcal{F}_{ii}), we have

    \begin{equation*} \lim\limits_{i\rightarrow +\infty }d_{b}(\mu _{i+1},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }) = 0. \end{equation*}

    On the other hand, we see that

    \begin{equation*} d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) \leq d\left( c,\mu _{i+1}\right) +d_{b}\left( \mu _{i+1},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) . \end{equation*}

    Further, in the light of above hypothesis with respect to G\ni c\longmapsto d_{b}(c, \left[ T\left(\mu _{i}\right) \right] _{\alpha \left(i\right) }) is \check{D}(T, \mu _{0}) -fuzzy dynamic lower semi-continuous, we have

    \begin{equation*} d_{b}(c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) })\leq \lim\limits_{n\rightarrow +\infty }\inf d_{b}(c,\left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) })+0 = 0. \end{equation*}

    Also, the closedness of \left[ T\left(c\right) \right] _{\alpha \left(c\right) } implies that c\in \left[ T\left(c\right) \right] _{\alpha \left(c\right) } which means that c is a fuzzy fixed point of T.

    Case 2. Assume that (4.26) holds true. From (4.26), we can write

    \begin{eqnarray} \mathcal{F}\left( d_{b}\left( \mu _{i+2},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) \right) &\leq &\mathcal{F}\left[ \hat{H} _{b}(\left[ T(\mu _{i+1})\right] _{\alpha \left( i+1\right) },\left[ T\left( c\right) \right] _{\alpha \left( c\right) })\right] -\tau \left( U(\mu _{i+1},c)\right) \\ &\leq &\mathcal{F}\left[ e_{1}(d(\mu _{i+1},c))+e_{2}d_{b}\left( \mu _{i+1}, \left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) }\right) \right. \\ &&+e_{3}d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) +\frac{e_{4}}{2}d\left( \mu _{i+1},c\right) \\ &&+\frac{e_{4}}{2}d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) +\frac{e_{5}}{2}d\left( c,\mu _{i+1}\right) \\ &&\left. +\frac{e_{5}}{2}d_{b}\left( \mu _{i+1},\left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+!\right) }\right) \right] -\tau \left( U(\mu _{i+1},c)\right) . \end{eqnarray} (4.30)

    From (4.12) and (4.22), there is i_{5}\in {\mathbb{N}} such that for some \varepsilon _{2} > 0

    \begin{equation} d(c,\mu _{i+1}) < \varepsilon _{2}{\rm{, }}d_{b}(\mu _{i+1},\left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) }) < \varepsilon _{2},{\rm{ for }}i > i_{5}. \end{equation} (4.31)

    Now, from (4.30) and (4.31), we have

    \begin{eqnarray} \mathcal{F}\left( d_{b}\left( \mu _{i+2},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) \right) &\leq &\mathcal{F}\left[ \hat{H} _{b}(\left[ T(\mu _{i+1})\right] _{\alpha \left( i+1\right) },\left[ T\left( c\right) \right] _{\alpha \left( c\right) })\right] -\tau \left( U(\mu _{i+1},c)\right) \\ &\leq &\mathcal{F}\left[ e_{1}(d(\mu _{i+1},c))+e_{2}d_{b}\left( \mu _{i+1}, \left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) }\right) \right. \\ &&+e_{3}d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) +\frac{e_{4}}{2}\left( \varepsilon _{1}\right) \\ &&+\frac{e_{4}}{2}d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) +e_{5}\left( \varepsilon _{1}\right) \\ &&-\tau \left( U(\mu _{i+1},c)\right) . \end{eqnarray} (4.32)

    for all i > i_{5}. Taking the limit as i\rightarrow +\infty in (4.32), we see that \lim_{i\rightarrow +\infty }\mathcal{F}\left(d_{b}\left(\mu _{i+2}, \left[ T\left(c\right) \right] _{\alpha \left(c\right) }\right) \right) = -\infty . By means of (\mathcal{F}_{ii}), we have

    \begin{equation*} \lim\limits_{i\rightarrow +\infty }d_{b}(\mu _{i+2},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }) = 0. \end{equation*}

    Consequently,

    \begin{equation*} d_{b}\left( c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) \leq d\left( c,\mu _{i+2}\right) +d_{b}\left( \mu _{i+2},\left[ T\left( c\right) \right] _{\alpha \left( c\right) }\right) . \end{equation*}

    Further, in view of above fashion with respect to G\ni c\longmapsto d_{b}(c, \left[ T\left(\mu _{i}\right) \right] _{\alpha \left(i\right) }) is \check{D}(T, \mu _{0}) -fuzzy dynamic lower semi-continuous, we have

    \begin{equation*} d_{b}(c,\left[ T\left( c\right) \right] _{\alpha \left( c\right) })\leq \lim\limits_{i\rightarrow +\infty }\inf d_{b}(c,\left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) })+0 = 0. \end{equation*}

    Also, the closedness of \left[ T\left(c\right) \right] _{\alpha \left(c\right) }, which implies that c\in \left[ T\left(c\right) \right] _{\alpha \left(c\right) } . Hence, c is a fuzzy fixed point of T.

    Corollary 4.4. Let \left(G, d\right) be a b -metric-like space with s\geq 1 . Assume that T:G\rightarrow \mu (G) is a F-fuzzy Suzuki-Kannan (abbr., F-FSK) type contraction with respect to fuzzy dynamic system \check{D} \left(\left[ T\mu \right] _{\alpha }, \mu _{0}\right) and \alpha :G\rightarrow \lbrack 0, 1] such that \left[ T\left(\mu _{i}\right) \right] _{\alpha \left(i\right) } are nonempty closed subsets of G. Assume that for some \mathcal{F}\in \nabla _{\digamma } and \tau :(0, +\infty)\rightarrow (0, +\infty) such that

    \begin{equation*} \frac{1}{2s}d_{b}\left( \mu _{i-1},\left[ T\left( \mu _{i-1}\right) \right] _{\alpha \left( i-1\right) }\right) \leq d\left( \mu _{i-1},\mu _{i}\right) , \end{equation*}

    we have

    \begin{equation*} \tau (U(\mu _{i-1},\mu _{i}))+\mathcal{F}\left[ \hat{H}_{b}\left( \left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) },\left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) }\right) \right] \leq \mathcal{F}(U(\mu _{i-1},\mu _{i})), \end{equation*}

    where

    \begin{equation*} U(\mu _{i-1},\mu _{i}) = e_{2}d_{b}\left( \mu _{i-1},\left[ T\left( \mu _{i-1}\right) \right] _{\alpha \left( i-1\right) }\right) +e_{3}d_{b}\left( \mu _{i},\left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) }\right), \end{equation*}

    for all \mu _{i}\in \check{D}\left(\left[ T\mu \right] _{\alpha }, \mu _{0}\right) , \hat{H}_{b}\left(\left[ T\left(\mu _{i}\right) \right] _{\alpha \left(i\right) }, \left[ T\left(\mu _{i+1}\right) \right] _{\alpha \left(i+1\right) }\right) > 0 , where e_{2}, e_{3}\in \left[ 0, 1\right] such that e_{1}+e_{2} = 1 . Assume that \left(i\right) \left(iii\right) are satisfied. Then T has a fuzzy fixed point.

    Corollary 4.5. Let \left(G, d\right) be a b -metric-like space with s\geq 1 . Assume that T:G\rightarrow \mu (G) is a F-fuzzy Suzuki-Chatterjea (abbr., F-FSC) type contraction with respect to fuzzy dynamic system \check{D} \left(\left[ T\mu \right] _{\alpha }, \mu _{0}\right) and \alpha :G\rightarrow \lbrack 0, 1] such that \left[ T\left(\mu _{i}\right) \right] _{\alpha \left(i\right) } are nonempty closed subsets of G. Assume that for some \mathcal{F}\in \nabla _{\digamma } and \tau :(0, +\infty)\rightarrow (0, +\infty) such that

    \begin{equation*} \frac{1}{2s}d_{b}\left( \mu _{i-1},\left[ T\left( \mu _{i-1}\right) \right] _{\alpha \left( i-1\right) }\right) \leq d\left( \mu _{i-1},\mu _{i}\right) , \end{equation*}

    we have

    \begin{equation*} \tau (U(\mu _{i-1},\mu _{i}))+\mathcal{F}\left[ \hat{H}_{b}\left( \left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) },\left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) }\right) \right] \leq \mathcal{F}(U(\mu _{i-1},\mu _{i})), \end{equation*}

    where

    \begin{equation*} U(\mu _{i-1},\mu _{i}) = e_{4}d_{b}\left( \mu _{i-1},\left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) }\right) +e_{5}d_{b}\left( \mu _{i}, \left[ T\left( \mu _{i-1}\right) \right] _{\alpha \left( i-1\right) }\right), \end{equation*}

    for all \mu _{i}\in \check{D}\left(\left[ T\mu \right] _{\alpha }, \mu _{0}\right) , \hat{H}_{b}\left(\left[ T\left(\mu _{i}\right) \right] _{\alpha \left(i\right) }, \left[ T\left(\mu _{i+1}\right) \right] _{\alpha \left(i+1\right) }\right) > 0 , where e_{4}, e_{5}\in \lbrack 0, \frac{1}{2}) . Assume that \left(i\right) \left(iii\right) are satisfied. Then T has a fuzzy fixed point.

    Corollary 4.6. Let \left(G, d\right) be a b -metric-like space with s\geq 1 . Assume that T:G\rightarrow \mu (G) is a F-fuzzy Suzuki-Banach (abbr., F-FSB) type contraction with respect to fuzzy dynamic system \check{D} \left(\left[ T\mu \right] _{\alpha }, \mu _{0}\right) and \alpha :G\rightarrow \lbrack 0, 1] such that \left[ T\left(\mu _{i}\right) \right] _{\alpha \left(i\right) } are nonempty closed subsets of G. Assume that for some \mathcal{F}\in \nabla _{\digamma } and \tau :(0, +\infty)\rightarrow (0, +\infty) such that

    \begin{equation*} \frac{1}{2s}d_{b}\left( \mu _{i-1},\left[ T\left( \mu _{i-1}\right) \right] _{\alpha \left( i-1\right) }\right) \leq d\left( \mu _{i-1},\mu _{i}\right) , \end{equation*}

    we have

    \begin{equation*} \tau (d(\mu _{i-1},\mu _{i}))+\mathcal{F}\left[ \hat{H}_{b}\left( \left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) },\left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) }\right) \right] \leq \mathcal{F}(e_{1}d(\mu _{i-1},\mu _{i})), \end{equation*}

    for all \mu _{i}\in \check{D}\left(\left[ T\mu \right] _{\alpha }, \mu _{0}\right) , \hat{H}_{b}\left(\left[ T\left(\mu _{i}\right) \right] _{\alpha \left(i\right) }, \left[ T\left(\mu _{i+1}\right) \right] _{\alpha \left(i+1\right) }\right) > 0 , where e_{1}\in \lbrack 0, 1) . Assume that \left(i\right) and \left(ii\right) are satisfied. Then T has a fuzzy fixed point.

    Corollary 4.7. Let \left(G, d\right) be a b -metric-like space with s\geq 1 . Assume that T:G\rightarrow \mu (G) is a F-fuzzy Banach (abbr., F-FB) type contraction with respect to fuzzy dynamic system \check{D} \left(\left[ T\mu \right] _{\alpha }, \mu _{0}\right) and \alpha :G\rightarrow \lbrack 0, 1] such that \left[ T\left(\mu _{i}\right) \right] _{\alpha \left(i\right) } are nonempty closed subsets of G. Assume that for some \mathcal{F}\in \nabla _{\digamma } and \tau :(0, +\infty)\rightarrow (0, +\infty) such that

    \begin{equation*} \tau (d(\mu _{i-1},\mu _{i}))+\mathcal{F}\left[ \hat{H}_{b}\left( \left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) },\left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) }\right) \right] \leq \mathcal{F}(e_{1}d(\mu _{i-1},\mu _{i})) \end{equation*}

    for all \mu _{i}\in \check{D}\left(\left[ T\mu \right] _{\alpha }, \mu _{0}\right) , \hat{H}_{b}\left(\left[ T\left(\mu _{i}\right) \right] _{\alpha \left(i\right) }, \left[ T\left(\mu _{i+1}\right) \right] _{\alpha \left(i+1\right) }\right) > 0 , where e_{1}\in \lbrack 0, 1) . Assume that \left(i\right) and \left(ii\right) are satisfied. Then T has a fuzzy fixed point.

    Example 4.8. Let G = {\mathbb{R}}^{+}\cup \left \{ 0\right \} and d:G\times G\rightarrow {\mathbb{R}}^{+}\cup \left \{ 0\right \} be a function defined by

    \begin{equation*} d\left( \mu _{1},\mu _{2}\right) = \left( \max \left \{ \mu _{1},\mu _{2}\right \} \right) ^{2}. \end{equation*}

    Clearly, \left(d, G\right) is a complete b -metric-like space with s = \frac{4}{3} . Define a fuzzy mapping T:G\rightarrow F(G) by

    \begin{equation*} T\left( \mu \right) \left( \mu ^{\prime }\right) = \left \{ \begin{array}{l} 1,\;{\rm{ if }}\;0\leq \mu ^{\prime }\leq \frac{\mu }{4}; \\ \frac{1}{2},\;{\rm{ if }}\;\frac{\mu }{4} < \mu ^{\prime }\leq \frac{\mu }{3}; \\ \frac{1}{4},\;{\rm{ if }}\;\frac{\mu }{3} < \mu ^{\prime }\leq \frac{\mu }{2}; \\ 0,\;{\rm{ if }}\;\frac{\mu }{2} < \mu ^{\prime }\leq 1. \end{array} \right. \end{equation*}

    Define \mathcal{F}:{\mathbb{R}}^{+}\rightarrow {\mathbb{R}} and \tau :{ \mathbb{R}}^{+}\rightarrow {\mathbb{R}}^{+} by \mathcal{F}(\mu) = \ln (\mu) and

    \begin{equation*} \tau (h) = \left \{ \begin{array}{l} \ln (1),\quad {\rm{ for }}\;\mu = 0,1; \\ \frac{1}{100},\quad {\rm{ for }}\;\mu \in (1,+\infty ). \end{array} \right. \end{equation*}

    For all \mu \in \check{D}\left(\left[ T\mu \right] _{\alpha }, \mu _{0}\right), there is \alpha \left(\mu \right) = 1 such that \left[ T\mu \right] _{\alpha \left(\mu \right) } = \left[ 0, \frac{\mu }{2}\right]. Then we have

    \begin{equation*} \frac{1}{2s}d_{b}\left( \mu _{i},\left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) }\right) \leq d\left( \mu _{i},\mu _{i+1}\right) , \end{equation*}

    setting e_{2} = e_{3} = e_{4} = e_{4} = 0 and e_{1} = 1 , we obtain

    \begin{equation*} \tau (d(\mu _{i},\mu _{i+1}))+\mathcal{F}\left[ \hat{H}_{b}\left( \left[ T\left( \mu _{i}\right) \right] _{\alpha \left( i\right) },\left[ T\left( \mu _{i+1}\right) \right] _{\alpha \left( i+1\right) }\right) \right] \leq \mathcal{F}(\alpha d(\mu _{i},\mu _{i+1})). \end{equation*}

    Hence all the required possible hypothesis of Corollary 4.6 are satisfied, Thus T has a fuzzy fixed point.

    Fuzzy differential equations and fuzzy integral equations have always been of key importance in dynamical programming and engineering problems. Therefore, various authors used different techniques for solving an fuzzy differential equations and fuzzy integral equations. Among those, Hukuhara differentiability for fuzzy valued function is the most celebrated problem. This section renders solution of a fuzzy differential equations. For this we explore Hukuhara differentiability for fuzzy functions and fuzzy initial valued problem in the setting of b -metric-like space.

    Definition 5.1. A function g: {\mathbb{R}} \rightarrow \left[ 0, 1\right] is called a fuzzy real number if

    \left(i\right) g is normal, i.e., there is \mu _{0}\in {\mathbb{R}} in such a way that g\left(\mu _{0}\right) = 1 ;

    \left(ii\right) ga is fuzzy convex, i.e., g\left(\beta \left(\mu _{1}\right) +\left(1-\beta \right) \mu _{2}\right) \geq \min \left \{ g\left(\mu _{1}), g\left(\mu _{2}\right) \right) \right \} , 0\leq \beta \leq 1 , for all \mu _{1}, \mu _{2}\in {\mathbb{R}} ;

    \left(iii\right) g is upper semi-continuous;

    \left(iiii\right) \left[ g\right] ^{0} = cl\left \{ \mu \in R:g\left(\mu \right) > 0\right \} is compact.

    Note that, for \alpha \in (0, 1],

    \begin{equation*} \left[ g\right] ^{\alpha } = cl\left \{ \mu \in R:g\left( \mu \right) > \alpha \right \} = \left[ g_{s_{1}}^{\alpha },g_{s_{2}}^{\alpha }\right], \end{equation*}

    expresses \alpha -cut of the fuzzy set g. For g\in P^{1} , where P^{1} represents the family of fuzzy real numbers, one can write \left[ g\right] ^{\alpha }\in C_{c}\left({\mathbb{R}}\right) for all \alpha \in \left[ 0, 1\right] , where C_{c}\left(R\right) denotes the set of all compact and convex subsets of \mathbb{R} . The supremum on P^{1} endowed with the b -metric-like is defined by

    \begin{equation*} d^{\ast }(g_{1},g_{2}) = \sup\limits_{\alpha \in \left[ 0,1\right] }\left[ \left \vert g_{1,s_{1}}^{\alpha }-g_{2,s_{1}}^{\alpha }\right \vert +\left \vert g_{1,s_{2}}^{\alpha }-g_{2,s_{2}}^{\alpha }\right \vert \right] ^{2}, \end{equation*}

    for all g_{1}, g_{2}\in P^{1}, g_{1, s_{1}}^{\alpha }-g_{2, s_{1}}^{\alpha } = diam\left(\left[ g\right] \right). Consider the continuous fuzzy function defined on \left[ 0, \Gamma \right] , for \Gamma > 0 as C\left(\left[ 0, \Gamma \right], P^{1}\right) endowed with the complete b -metric-like with respect to b -metric-like as:

    \begin{equation*} d(g_{1},g_{2}) = \sup\limits_{\mu \in \left[ 0,1\right] }\left[ d^{\ast }(g_{1},g_{2}) \right], \end{equation*}

    for all g_{1}, g_{2}\in C^{1}\left(\left[ 0, \Gamma \right], P^{1}\right). Consider the fuzzy initial valued problem:

    \begin{equation} \left \{ \begin{array}{l} g^{\prime }\left( \mu \right) = f\left( \mu ,g\left( \mu \right) \right) , {\rm{ }}\mu \in I = \left[ 0,\Gamma \right] ; \\ g\left( 0\right) = 0, \end{array} \right. \end{equation} (5.1)

    where g^{\prime } is the Hukuhara differentiability and f is the fuzzy function, i.e., f:I\times P^{1}\rightarrow P^{1} is continuous. Denote the set of all continuous fuzzy functions f:I\rightarrow P^{1} which have continuous derivatives by C^{1}\left(I, P^{1}\right). A family \mu \in C^{1}\left(I, P^{1}\right) is a solution of fuzzy initial valued problem (5.1) if and only if

    \begin{equation} g\left( \mu \right) = g_{0}\Theta _{E}\left( -1\right) _{0}^{\mu }f\left( r,g\left( r\right) \right) dr,{\rm{ }}\mu \in I = \left[ 0,\Gamma \right] , \end{equation} (5.2)

    where (5.2) is called a fuzzy Volterra integral equation.

    Theorem 5.2. Let f:I\times P^{1}\rightarrow P^{1} be a continuous function such that

    \begin{equation*} g < g^{\prime }\;implies\;f\left( \mu ,g\left( \mu \right) \right) < f\left( \mu ,g^{\prime }\left( \mu \right) \right), \end{equation*}

    for g, g^{\prime }\in P^{1} , In addition, assume that \tau :(0, +\infty)\rightarrow (0, +\infty) such that

    \begin{equation*} \left[ \left \vert f\left( \mu ,g\left( \mu \right) \right) -f\left( \mu ,g^{\prime }\left( \mu \right) \right) \right \vert \right] ^{2}\leq \tau e^{-\tau }\max\limits_{\mu \in I}\left( d^{\ast }(g_{1}\left( \mu \right) ,g_{2}\left( \mu \right) )e^{-\tau \mu }\right) , \end{equation*}

    where g < g^{\prime } for all \mu \in I and g, g^{\prime }\in P^{1}. Then the FIVP (5.1) has a fuzzy solution with respect to C^{1}\left(I, P^{1}\right).

    Proof. Let \tau :(0, +\infty)\rightarrow (0, +\infty) and the family C^{1}\left(I, P^{1}\right) endow with the b -metric-like as:

    \begin{equation*} d_{\tau }(g,g^{\prime }) = \sup\limits_{\mu \in \left[ 0,1\right] }\left[ d^{\ast }(g\left( \mu \right) ,g^{\prime }\left( \mu \right) )e^{-\tau \mu }\right], \end{equation*}

    for all g, g^{\prime }\in C^{1}\left(I, P^{1}\right). Let S:G\rightarrow (0, 1] . Due to (5.2) for g\in G, one can write

    \begin{equation*} Y_{g}\left( \mu \right) = g_{0}\Theta _{E}\left( -1\right) _{0}^{\mu }f\left( r,g\left( r\right) \right) dr,{\rm{ }}\mu \in I. \end{equation*}

    Assume that g < g . Then we have

    \begin{eqnarray*} Y_{g}\left( \mu \right) & = &g_{0}\Theta _{E}\left( -1\right) _{0}^{\mu }f\left( r,g\left( r\right) \right) dr \\ & < &g_{0}\Theta _{E}\left( -1\right) _{0}^{\mu }f\left( r,g^{\prime }\left( r\right) \right) dr \\ & = &Y_{g^{\prime }}\left( \mu \right) . \end{eqnarray*}

    This implies Y_{g}\left(\mu \right) \neq Y_{g^{\prime }}\left(\mu \right) . Assume a fuzzy mapping T:G\rightarrow P^{G} is defined by

    \begin{equation*} \left \{ \begin{array}{c} \eta _{Tg}\left( t\right) = \left \{ \begin{array}{l} Y\left( g\right) ,{\rm{ }}t\left( \mu \right) = Y_{g}\left( \mu \right); \\ 0,\;{\rm{ otherwise}}. \end{array} \right. \\ \eta _{Tg^{\prime }}\left( t\right) = \left \{ \begin{array}{l} Y\left( g^{\prime }\right) ,{\rm{ }}t\left( \mu \right) = Y_{g^{\prime }}\left( \mu \right); \\ 0,\;{\rm{ otherwise.}} \end{array} \right. \end{array} \right. \end{equation*}

    Owing to \alpha \left(g\right) = S\left(g\right) and \alpha \left(g^{\prime }\right) = S\left(g^{\prime }\right), we have

    \begin{equation*} \left[ Tg\right] _{\alpha \left( g\right) } = \left \{ t\in G:Tg\left( \mu \right) \geq S\left( g\right) \right \} = Y_{g}\left( \mu \right), \end{equation*}

    and on the same fashion, we have

    \begin{equation*} \left[ Tg^{\prime }\right] _{\alpha \left( g^{\prime }\right) } = \left \{ t\in G:Tg^{\prime }\left( \mu \right) \geq S\left( g^{\prime }\right) \right \} = Y_{g^{\prime }}\left( \mu \right) . \end{equation*}

    Therefore,

    \begin{eqnarray*} \hat{H}_{b}\left( \left[ Tg\right] _{\alpha \left( g\right) },\left[ Tg^{\prime }\right] _{\alpha \left( g^{\prime }\right) }\right) & = &\max \left \{ \begin{array}{c} \sup\limits_{g\in \left[ Tg\right] _{\alpha \left( g\right) }}\inf\limits_{g^{\prime }\in \left[ Tg^{\prime }\right] _{\alpha \left( g^{\prime }\right) }}d\left( g,g^{\prime }\right) , \\ \sup\limits_{g^{\prime }\in \left[ Tg^{\prime }\right] _{\alpha \left( g^{\prime }\right) }}\inf\limits_{g\in \left[ Tg\right] _{\alpha \left( g\right) }}d\left( g,g^{\prime }\right), \end{array} \right \} \\ &\leq &\max \left \{ \sup\limits_{\mu \in I}\left[ \left \vert Y_{g}\left( \mu \right) \right \vert +\left \vert Y_{g^{\prime }}\left( \mu \right) \right \vert \right] ^{2}\right \} \\ & = &\sup\limits_{\mu \in I}\left[ \left \vert Y_{g}\left( \mu \right) \right \vert +\left \vert Y_{g^{\prime }}\left( \mu \right) \right \vert \right] ^{2} \\ & = &\sup\limits_{\mu \in I}\left[ \left \vert g_{0}\Theta _{E}\left( -1\right) _{0}^{\mu }f\left( r,g\left( r\right) \right) dr\right \vert +\left \vert g_{0}\Theta _{E}\left( -1\right) _{0}^{\mu }f\left( r,g^{\prime }\left( r\right) \right) dr\right \vert \right] ^{2} \\ & = &\sup\limits_{\mu \in I}\left[ g_{0}\Theta _{E}\left( -1\right) _{0}^{\mu }\left( \left \vert f\left( r,g\left( r\right) \right) dr\right \vert +\left \vert f\left( r,g^{\prime }\left( r\right) \right) dr\right \vert \right) \right] ^{2}. \end{eqnarray*}

    Then, in view of above hypothesis we have:,

    \begin{eqnarray*} \hat{H}_{b}\left( \left[ Tg\right] _{\alpha \left( g\right) },\left[ Tg^{\prime }\right] _{\alpha \left( g^{\prime }\right) }\right) &\leq &\sup\limits_{\mu \in I}\left[ \left \vert _{0}^{\mu }f\left( r,g\left( r\right) \right) \right \vert +\left \vert _{0}^{\mu }f\left( r,g^{\prime }\left( r\right) \right) \right \vert dr\right] ^{2} \\ &\leq &\sup\limits_{\mu \in I}\left[ \left \vert _{0}^{\mu }f\left( r,g\left( r\right) \right) \right \vert ^{\frac{1}{2}}+\left \vert _{0}^{\mu }f\left( r,g^{\prime }\left( r\right) \right) \right \vert ^{\frac{1}{2}}dr\right] ^{2} \\ &\leq &\sup\limits_{\mu \in I}\left \{ _{0}^{\mu }\tau e^{-\tau }\left \vert g\left( r\right) -g^{\prime }\left( r\right) \right \vert e^{-\tau r}e^{\tau r}dr\right \} \\ & = &\tau e^{-\tau }\frac{1}{\tau }d_{\tau }(g,g^{\prime })e^{\tau r}. \end{eqnarray*}

    By appealing to the above fashion, we obtain

    \begin{equation*} \hat{H}_{b}\left( \left[ Tg\right] _{\alpha \left( g\right) },\left[ Tg^{\prime }\right] _{\alpha \left( g^{\prime }\right) }\right) e^{-\tau r}\leq e^{-\tau }d_{\tau }(g,g^{\prime }), \end{equation*}

    or equivalently,

    \begin{equation*} \hat{H}_{b}\left( \left[ Tg\right] _{\alpha \left( g\right) },\left[ Tg^{\prime }\right] _{\alpha \left( g^{\prime }\right) }\right) \leq e^{-\tau }d_{\tau }(g,g^{\prime }). \end{equation*}

    Owing to logarithms, we have

    \begin{equation*} \ln \left( \hat{H}_{b}\left( \left[ Tg\right] _{\alpha \left( g\right) },\left[ Tg^{\prime }\right] _{\alpha \left( g^{\prime }\right) }\right) \right) \leq \ln \left( e^{-\tau }d_{\tau }(g,g^{\prime })\right) , \end{equation*}

    Owing to the above speculation, this, in turn, yields:

    \begin{equation*} \tau\left(d_{\tau }\left(g,g^{\prime }\right)\right)+\ln \left( \hat{H}_{b}\left( \left[ Tg\right] _{\alpha \left( g\right) },\left[ Tg^{\prime } \right] _{\alpha \left( g^{\prime }\right) }\right) \right) \leq \ln \left( d_{\tau }(g,g^{\prime })\right) . \end{equation*}

    Due to \mathcal{F} -contraction, with the setting \mathcal{F}\left(\mu \right) = \ln \mu, for all \mu \in C^{1}\left(I, P^{1}\right) , we have

    \begin{equation*} \tau\left(d_{\tau }\left(g,g^{\prime }\right)\right)+\mathcal{F}\left( \hat{H}_{b}\left( \left[ Tg\right] _{\alpha \left( g\right) },\left[ Tg^{\prime } \right] _{\alpha \left( g^{\prime }\right) }\right) \right) \leq \mathcal{F} \left( d_{\tau }(g,g^{\prime })\right) . \end{equation*}

    It follows that there is c\in C^{1}\left(I, P^{1}\right) such that c\in \left[ Tc\right] _{\alpha \left(c\right) }. Hence all the possible hypothesis of Corollary 4.7 are satisfied and consequently fuzzy initial valued problem (5.1) has a fuzzy solution c\in C^{1}\left(I, P^{1}\right) in C^{1}\left(I, P^{1}\right).

    The article regards with new approach of fuzzy dynamic process on b -metric-like space, specifically the mapping of set-valued (extended) fuzzy intervals endowed with the b -metric-like. After we just adopt the standard setting of fuzzy dynamic process in b -metric-like space which defines convergence theorems in generalized \mathcal{F} -contraction via expectations of fuzzy Suzuki-type contraction mappings. Subsequently, corollaries are originated from the main result. To explain the example in the main section, a graphically interpretation has been created that best illustrates the fuzzy dynamic process to the readers. At the end, gives an application of our results in solving Hukuhara differentiability through the fuzzy initial valued problem and fuzzy functions. The pivotal role of Hukuhara differentiability in fuzzy dynamic process is stated. In future, this methodology can be inspected intuitionistic fuzzy and picture fuzzy sets the fuzzy dynamic process for a hybrid pair of mappings can be examined.

    All the authors have equal contribution, read and approved the final manuscript. The authors S. Subhi, N. Mlaiki and W. Shatanawi would like to thank Prince Sultan University for paying the publication fees for this work through TAS LAB.

    The authors declare that they have no conflicts of interests.



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