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On a parabolic partial differential equation and system modeling a production planning problem

  • We consider a parabolic partial differential equation and system derived from a production planning problem dependent on time. Our goal is to find a closed-form solution for the problem considered in our model. Our new theoretical results can be applied in the real world.

    Citation: Dragos-Patru Covei. On a parabolic partial differential equation and system modeling a production planning problem[J]. Electronic Research Archive, 2022, 30(4): 1340-1353. doi: 10.3934/era.2022070

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  • We consider a parabolic partial differential equation and system derived from a production planning problem dependent on time. Our goal is to find a closed-form solution for the problem considered in our model. Our new theoretical results can be applied in the real world.



    Several years ago, Bensoussan, Sethi, Vickson and Derzko [1] have been considered the case of a factory producing one type of economic goods and observed that it is necessary to solve the simple partial differential equation

    {σ22Δzαs+14|zαs|2+αzαs=|x|2forxRN,zαs=as|x|, (1.1)

    where σ(0,) denotes the diffusion coefficient, α[0,) represents psychological rate of time discount, xRN is the product vector, z:=zαs(x) denotes the value function and |x|2 is the loss function.

    Regime switching refers to the situation when the characteristics of the state process are affected by several regimes (e.g., in finance bull and bear market with higher volatility in the bear market).

    It is important to point out that, when dealing with regime switching, we can describe a wide variety of phenomena using partial differential equations. In [1], the authors Cadenillas, Lakner and Pinedo [2] adapted the model problem in [1] to study the optimal production management characterized by the two-state regime switching with limited/unlimited information and corresponding to the system

    {σ212Δus1+(a11+α1)us1a11us2ρσ212ij2us1xixj|x|2=14|us1|2,xRN,σ222Δus2+(a22+α2)us2a22us1ρσ222ij2us2xixj|x|2=14|us2|2,xRN,us1(x)=us2(x)=as|x|, (1.2)

    where σ1,σ2(0,) denote the diffusion coefficients, α1,α2[0,) represent the psychological rates of time discount from what place the exponential discounting, xRN is the product vector, usr:=usr(x) (r=1,2) denotes the value functions, |x|2 is the loss function, ρ[1,1] is the correlation coefficient and anm (n,m=1,2) are the elements of the Markov chain's rate matrix, denoted by G=[ϑnm]2×2 with

    ϑnn=ann0,ϑnm=anm0andϑ2nn+ϑ2nm0fornm,

    the diagonal elements ϑnn may be expressed as ϑnn=Σmnϑnm.

    Furthermore, in civil engineering, Dong, Malikopoulos, Djouadi and Kuruganti [3] applied the model described in [2] to the study of the optimal stochastic control problem for home energy systems with solar and energy storage devices; the two regimes switching are the peak and the peak energy demands.

    After that, there have been numerous applications of regime switching in many important problems in economics and other fields, see the works of: Capponi and Figueroa-López [4], Elliott and Hamada [5], Gharbi and Kenne [6], Yao, Zhang and Zhou [7] and Wang, Chang and Fang [8] for more details. Other different research studies that explain the importance of regime switching in the real world are [9,10].

    In this paper, we focus on the following parabolic partial differential equation and system, corresponding to (1.1)

    {zt(x,t)σ22Δz(x,t)+14|z(x,t)|2+αz(x,t)=|x|2,(x,t)RN×(0,),z(x,0)=c+zαs(x),forallxRNandfixedc(0,),z(x,t)=as|x|,forallt[0,), (1.3)

    and (1.2) respectively

    {u1tσ212Δu1+(a11+α1)u1a11u2ρσ212ij2u1xixj|x|2=14|u1|2,(x,t)RN×(0,),u2tσ222Δu2+(a22+α2)u2a22u1ρσ222ij2u2xixj|x|2=14|u2|2,(x,t)RN×(0,),(u1(x,0),u2(x,0))=(c1+us1(x),c2+us2(x))forallxRNandforfixedc1,c2(0,),u1t(x,t)=u2t(x,t)=as|x|forallt[0,), (1.4)

    where zαs is the solution of (1.1) and (us1(x),us2(x)) is the solution of (1.2). The existence and the uniqueness for the case of (1.1) is proved by [10] and the existence for the system case of (1.2) by [11].

    From the mathematical point of view the problem (1.3) has been extensively studied when the space RN is replaced by a bounded domain and when α=0. In particular, some great results can be found in the old papers of Barles, Porretta [12] and Tchamba [13]. More recently, but again for the case of a bounded domain, α=0 and in the absence of the gradient term, the problem (1.3) has been also discussed by Alves and Boudjeriou [14]. The interest of these authors [12,13,14] is to give an asymptotic stable solution at infinity for the considered equation, i.e., a solution which tends to the stationary Dirichlet problem associated with (1.3) when the time go to infinity.

    Next, we propose to find a similar result as of [12,13,14], for the case of equation (1.3) and system (1.4) that model some real phenomena. More that, our first interest is to provide a closed form solution for (1.3) and (1.4). Our second objective is inspired by the paper of [14,15], and it is to solve the parabolic partial differential equation

    {zt(x,t)σ22Δz(x,t)+14|z(x,t)|2=|x|2,inBR×[0,T),z(x,T)=0,for|x|=R, (1.5)

    where T< and BR is a ball of radius R>0 with origin at the center of RN.

    Let us finish our introduction and start with the main results.

    We use the change of variable

    u(x,t)=ez(x,t)2σ2, (2.1)

    in

    zt(x,t)σ22Δz(x,t)+14|z(x,t)|2+αz(x,t)=|x|2

    to rewrite (1.3) and (1.5) in an equivalent form

    {ut(x,t)σ22Δu(x,t)+αu(x,t)lnu(x,t)+12σ2|x|2u(x,t)=0,if(x,t)Ω×(0,T)u(x,T)=u1,0,onΩ,u(x,0)=ec+zαs(x)2σ2,forxΩ=RN,c(0,) (2.2)

    where

    u1,0={1ifΩ=BR,i.e.,|x|=R,T<,0ifΩ=RN,i.e.,|x|,T=.

    Our first result is the following.

    Theorem 2.1. Assume Ω=BR, N3, T< and α=0.There exists a unique radially symmetric positive solution

    u(x,t)C2(BR×[0,T))C(¯BR×[0,T]),

    of (2.2) increasing in the time variable and such that

    limtTu(x,t)=us(x), (2.3)

    where usC2(BR)C(¯BR) is the unique positive radially symmetric solution of theDirichlet problem

    {σ22Δus=(12σ2|x|2+1)us,inBR,us=1,onBR, (2.4)

    which will be proved. In addition,

    z(x,t)=2σ2(tT)2σ2lnus(|x|),(x,t)¯BR×[0,T],

    is the unique radially symmetric solution of the problem (1.5).

    Instead of the existence results discussed in the papers of [12,13,14], in our proof of the Theorem 2.1 we give the numerical approximation of solution u(x,t).

    The next results refer to the entire Euclidean space RN and present closed-form solutions.

    Theorem 2.2. Assume Ω=RN, N1, T=, α>0 and c(0,) is fixed. There exists aunique radially symmetric solution

    u(x,t)C2(RN×[0,)),

    of (2.2), increasing in the time variable and such that

    u(x,t)uαs(x)astforallxRN, (2.5)

    where uαsC2(RN) is the uniqueradially symmetric solution of the stationary Dirichlet problem associatedwith (2.2)

    {σ22Δuαs=αuαslnuαs+12σ2|x|2uαs,inRN,uαs(x)0,as|x|. (2.6)

    Moreover, the closed-form radially symmetric solution of the problem (1.3) is

    z(x,t)=ceαt+B|x|2+D,(x,t)RN×[0,),c(0,), (2.7)

    where

    B=1Nσ2(12Nσ2α2+412Nασ2),D=12α(Nσ2α2+4Nασ2). (2.8)

    The following theorem is our main result regarding the system (1.4).

    Theorem 2.3. Suppose that N1, α1,α2(0,) and\ a11,a22[0,) with a211+a2220. Then, the system (1.4) has a uniqueradially symmetric convex solution

    (u1(x,t),u2(x,t))C2(RN×[0,))×C2(RN×[0,)),

    of quadratic form in the x variable and such that

    (u1(x,t),u2(x,t))(us1(x),us2(x))astuniformlyforallxRN, (2.9)

    where

    (us1(x),us2(x))C2(RN)×C2(RN)

    is the radially symmetric convex solution of quadratic form in the xvariable of the stationary system (1.2) which exists from the resultof [11].

    Our results complete the following four main works: Bensoussan, Sethi, Vickson and Derzko [1], Cadenillas, Lakner and Pinedo [2], Canepa, Covei and Pirvu [15] and Covei [10], which deal with a stochastic control model problem with the corresponding impact for the parabolic case (see [13,16] for details).

    To prove our Theorem 2.1, we use a lower and upper solution method and the comparison principle that can be found in [17].

    Lemma 2.1. If, there exist ¯u(x), u_(x)C2(BR)C(¯BR) two positive functions satisfying

    {σ22Δ¯u(x)+(12σ2|x|2+1)¯u(x)0σ22Δu_(x)+(12σ2|x|2+1)u_(x)inBR,¯u(x)=1=u_(x)onBR,

    then

    ¯u(x)u_(x)0forallx¯BR,

    and there exists

    u(x)C2(BR)C(¯BR),

    a solution of (2.4) such that

    u_(x)u(x)¯u(x),x¯BR,

    where u_(x) and ¯u(x) arerespectively, called a lower solution and an upper solution of (2.4).

    The corresponding result of Lemma 2.1 for the parabolic equations can be found in the work of Pao [18] and Amann [19]. To achieve our goal, complementary to the works [12,13,14,15] it can be used the well known books of Gilbarg and Trudinger [20], Sattinger [17], Pao [18] and a paper of Amann [19]. Further on, we can proceed to prove Theorem 2.1.

    By a direct calculation, if there exists and is unique, usC2(BR)C(¯BR), a positive solution of the stationary Dirichlet problem (2.4) then

    u(x,t)=etTus(x),(x,t)¯BR×[0,T],

    is the solution of the problem (2.2) and

    z(x,t)=2σ2(tT)2σ2lnus(x),(x,t)¯BR×[0,T],

    is the solution of the problem (1.5) belonging to

    C2(BR×[0,T))C(¯BR×[0,T]).

    We prove that (2.4) has a unique radially symmetric solution. The existence of solution for (2.4) is obtained by a standard monotone iteration and the lower and the upper solution method, Lemma 2.1. Hence, starting from the initial iteration

    u0s(x)=eR2|x|22σ2,

    we construct a sequence {uks(x)}k1 successively by

    {σ22Δuks(x)=(12σ2|x|2+1)uk1s(x),inBR,uks(x)=1,onBR, (3.1)

    and this sequence will be pointwise convergent to a solution us(x) of (2.4).

    Indeed, since for each k the right-hand side of (3.1) is known, the existence theory for linear elliptic boundary-value problems implies that {uks(x)}k1 is well defined, see [20].

    Let us prove that {uks(x)}k1 is a pointwise convergent sequence to a solution of (2.4) in ¯BR. To do this, first we prove that {uks(x)}k1 is monotone nondecreasing of k. We apply the mathematical induction by verifying the first step, k=1.

    {σ22Δu1s(x)σ22Δu0s(x),inBR,u1s(x)=1=u0s(x),onBR.

    Now, by the standard comparison principle, Lemma 2.1, we have

    u0s(x)u1s(x)in¯BR.

    Moreover, the induction argument yields the following

    u0s(x)=eR2|x|22σ2...uks(x)uk+1s(x)...in¯BR, (3.2)

    i.e., {uks(x)}k1 is a monotone nondecreasing sequence.

    Next, using again Lemma 2.1, we find

    u_s(x):=u0s(x)=eR2|x|22σ2...uks(x)uk+1s(x)...¯us(x):=1in¯BR, (3.3)

    where we have used

    σ22Δu_s(x)=u_s(x)σ22(|x|2+σ2σ4+N1σ2)u_s(x)(12σ2|x|2+1)σ22Δ¯us(x)=σ22Δ1=0¯us(x)(12σ2|x|2+1)

    i.e., Lemma 2.1 confirm.Thus, in view of the monotone and bounded property in (3.3) the sequence {uks(x)}k1 converges. We may pass to the limit in (3.3) to get the existence of a solution

    us(x):=limkuks(x)in¯BR,

    associated to (2.4), which satisfies

    u_s(x)us(x)¯us(x)in¯BR.

    Furthermore, the convergence of {uks(x)} is uniformly to us(x) in ¯BR and us(x) has a radial symmetry, see [15] for arguments of the proof. The regularity of solution us(x) is a consequence of classical results from the theory of elliptic equations, see Gilbarg and Trudinger [20]. The uniqueness of us(x) follows from a standard argument with the use of Lemma 2.1 and we omit the details.

    Clearly, u(x,t) is increasing in the time variable. The regularity of u(x,t) follows from the regularity of us(x). Letting tT we see that (2.3) holds. The solution of the initial problem (1.5) is saved from (2.1).

    Finally, we prove the uniqueness for (2.2). Let

    u(x,t),v(x,t)C2(BR×[0,T))C(¯BR×[0,T]),

    be two solutions of the problem (2.2), i.e., its hold

    {ut(x,t)σ22Δu(x,t)+12σ2|x|2u(x,t)=0,if(x,t)BR×[0,T),u(x,T)=1,onBR,

    and

    {vt(x,t)σ22Δv(x,t)+12σ2|x|2v(x,t)=0,if(x,t)BR×[0,T),v(x,T)=1,onBR.

    Setting

    w(x,t)=u(x,t)v(x,t),inBR×[0,T],

    and subtracting the two equations corresponding to u and v we find

    {wt(x,t)=σ22Δw(x,t)12σ2|x|2w(x,t),if(x,t)BR×[0,T),w(x,T)=0,onBR.

    Let us prove that u(x,t)v(x,t)0 in ¯BR×[0,T]. If the conclusion were false, then the maximum of

    w(x,t),inBR×[0,T),

    is positive. Assume that the maximum of w in ¯BR×[0,T] is achieved at (x0,t0). Then, at the point (x0,t0)BR×[0,T), where the maximum is attained, we have

    wt(x0,t0)0,Δw(x0,t0)0,w(x0,t0)=0,

    and

    0wt(x0,t0)=σ22Δw(x0,t0)12σ2|x|2w(x0,t0)<0

    which is a contradiction. Reversing the role of u and v we obtain that u(x,t)v(x,t)0 in ¯BR×[0,T]. Hence u(x,t)=v(x,t) in ¯BR×[0,T]. The proof of Theorem 2.1 is completed.

    Finally, our main result, Theorem 2.2 will be obtained by a direct computation.

    In view of the arguments used in the proof of Theorem 2.1 and the real world phenomena, we use a purely intuitive strategy in order to prove Theorem 2.2.

    Indeed, for the verification result in the production planning problem, we need z(x,t) to be almost quadratic with respect to the variable x.

    More exactly, we observe that there exists and is unique

    u(x,t)=eh(t)+B|x|2+D2σ2,(x,t)RN×[0,),withB,D(0,),

    that solve (2.2), where

    h(0)=c, (4.1)

    and B, D are given in (2.8). The condition (4.1) is used to obtain the asymptotic behaviour of solution to the stationary Dirichlet problem associated with (2.2). Then our strategy is reduced to find B,D(0,) and the function h which depends of time and c(0,) such that

    12h(t)σ2σ22[Bσ4(σ2B|x|2)(N1)Bσ2]+α(h(t)+B|x|2+D2σ2)+12σ2|x|2=0,

    or, after rearranging the terms

    |x|2(1αBB2)+Nσ2BαDh(t)αh(t)=0,

    where (4.1) holds. Now, by a direct calculation we see that the system of equations

    {1αBB2=0Nσ2BαD=0h(t)αh(t)=0h(0)=c

    has a unique solution that satisfies our expectations, namely,

    u(x,t)=eceαt+B|x|2+D2σ2,(x,t)RN×[0,), (4.2)

    where B and D are given in (2.8), is a radially symmetric solution of the problem (2.2). The uniqueness of the solution is followed by the arguments in [10] combined with the uniqueness proof in Theorem 2.1. The justification of the asymptotic behavior and regularity of the solution can be proved directly, once we have a closed-form solution. Finally, the closed-form solution in (2.7) is due to (2.1)–(4.2) and the proof of Theorem 2.2 is completed.

    One way of solving this system of partial differential equation of parabolic type (1.4) is to show that the system (1.4) is solvable by

    (u1(x,t),u2(x,t))=(h1(t)+β1|x|2+η1,h2(t)+β2|x|2+η2), (5.1)

    for some unique β1,β2,η1,η2(0,) and h1(t), h2(t) are suitable chosen such that

    h1(0)=c1andh2(0)=c2. (5.2)

    The main task for the proof of existence of (5.1) is performed by proving that there exist

    β1,β2,η1,η2,h1,h2,

    such that

    {h1(t)2β1Nσ212+(a11+α1)[h1(t)+β1|x|2+η1]a11[h2(t)+β2|x|2+η2]|x|2=14(2β1|x|)2,h2(t)2β2Nσ222+(a22+α2)[h2(t)+β2|x|2+η2]a22[h1(t)+β1|x|2+η1]|x|2=14(2β2|x|)2,

    or equivalently, after grouping the terms

    {|x|2[a11β2+(a11+α1)β1+β211]β1Nσ21a11η2+(a11+α1)η1+h1(t)+(a11+α1)h1(t)a11h2(t)=0,|x|2[a22β1+(a22+α2)β2+β221]β2Nσ22a22η1+(a22+α2)η2+h2(t)+(a22+α2)h2(t)a22h1(t)=0,

    where h1(t), h2(t) must satisfy (5.2). Now, we consider the system of equations

    {a11β2+(a11+α1)β1+β211=0a22β1+(a22+α2)β2+β221=0β1Nσ21a11η2+(a11+α1)η1=0β2Nσ22a22η1+(a22+α2)η2=0h1(t)+(a11+α1)h1(t)a11h2(t)=0h2(t)+(a22+α2)h2(t)a22h1(t)=0. (5.3)

    To solve (5.3), we can rearrange those equations 1, 2 in the following way

    {a11β2+(a11+α1)β1+β211=0a22β1+(a22+α2)β2+β221=0. (5.4)

    We distinguish three cases:

    1.in the case a22=0 we have an exact solution for (5.4) of the form

    β1=12α112a11+12α21+a2114a11(12α212α22+4)+2α1a11+4β2=12α2+12α22+4

    2.in the case a11=0 we have an exact solution for (5.4) of the form

    β1=12α1+12α21+4β2=12α212a22+12α22+a2224a22(12α112α21+4)+2α2a22+4

    3.in the case a110 and a220, to prove the existence and uniqueness of solution for (5.4) we will proceed as follows. We retain from the first equation of (5.4)

    β1=12α21+2α1a11+a211+4β2a11+412a1112α1.

    and from the second equation

    β2=12α22+2α2a22+a222+4β1a22+412a2212α2.

    The existence of β1, β2(0,) for (5.4) can be easily proved by observing that the continuous functions f1,f2:[0,)R defined by

    f1(β1)=a11(12α22+2α2a22+a222+4β1a22+412a2212α2)+(a11+α1)β1+β211,f2(β2)=a22(12α21+2α1a11+a211+4β2a11+412a1112α1)+(a22+α2)β2+β221,

    have the following properties

    f1()=andf2()=, (5.5)

    respectively

    f1(0)=a11(12α22+2α2a22+a222+412a2212α2)1<0,f2(0)=a22(12α21+2α1a11+a211+412a1112α1)1<0. (5.6)

    The observations (5.5) and (5.6) imply

    {f1(β1)=0f2(β2)=0

    has at least one solution (β1,β2)(0,)×(0,) and furthermore it is unique (see also, the references [21,22] for the existence and the uniqueness of solutions).

    The discussion from cases 1–3 show that the system (5.4) has a unique positive solution. Next, letting

    (β1,β2)(0,)×(0,),

    be the unique positive solution of (5.4), we observe that the equations 3, 4 of (5.3) can be written equivalently as a system of linear equations that is solvable and with a unique solution

    (a11+α1a11a22a22+α2)(η1η2)=(β1Nσ21β2Nσ22). (5.7)

    By defining

    Ga,α:=(a11+α1a11a22a22+α2),

    we observe that

    G1a,α=(α2+a22α1α2+α2a11+α1a22a11α1α2+α2a11+α1a22a22α1α2+α2a11+α1a22α1+a11α1α2+α2a11+α1a22).

    Using the fact that G1a,α has all ellements positive and rewriting (5.7) in the following way

    (η1η2)=G1a,α(β1Nσ21β2Nσ22),

    we can see that there exist and are unique η1, η2(0,) that solve (5.7). Finally, the equations 5, 6, 7 of (5.3) with initial condition (5.2) can be written equivalently as a solvable Cauchy problem for a first order system of differential equations

    {(h1(t)h2(t))+Ga,α(h1(t)h2(t))=(00),h1(0)=c1andh2(0)=c2, (5.8)

    with a unique solution and then (5.1) solve (1.4). The rest of the conclusions are easily verified.

    Next, we present an application.

    Application 1. Suppose there is one machine producing two products (see [23,24], for details). We consider a continuous time Markov chain generator

    (12121212),

    and the time-dependent production planning problem with diffusion σ1=σ2=12 and let α1=α2=12 the discount factor. Under these assumptions, we can write the system (5.4) with our data

    {β21+β112β21=0β2212β1+β21=0

    which has a unique positive solution

    β1=14(171),β2=14(171).

    On the other hand, the system (5.7) becomes

    (112121)(η1η2)=(β1β2),

    which has a unique positive solution

    η1=43β1+23β2=12(171),η2=23β1+43β2=12(171).

    Finally, the system in (5.8) becomes

    {(h1(t)h2(t))+(112121)(h1(t)h2(t))=(00),h1(0)=c1andh2(0)=c2,

    which has the solution

    h1(t)=s1e12ts2e32t,h2(t)=s1e12t+s2e32t,withs1,s2R.

    Next, from

    h1(0)=c1andh2(0)=c2,

    we have

    {s1s2=c1s1+s2=c2s1=12c1+12c2,s2=12c212c1,

    and finally

    {h1(t)=12(c1+c2)e12t12(c2c1)e32t,h2(t)=12(c1+c2)e12t+12(c2c1)e32t,

    from where we can write the unique solution of the system (1.4) in the form (5.1).

    Let us point that in Theorem 2.3 we have proved the existence and the uniqueness of a solution of quadratic form in the x variable and then the existence of other different types of solutions remain an open problem.

    Some closed-form solutions for equations and systems of parabolic type are presented. The form of the solutions is unique and tends to the solutions of the corresponding elliptic type problems that were considered.

    The author is grateful to the anonymous referees for their useful suggestions which improved the contents of this article.

    The authors declare there is no conflict of interest.



    [1] A. Bensoussan, S. P. Sethi, R. Vickson, N. Derzko, Stochastic production planning with production constraints, SIAM J. Control Optim., 22 (1984), 920–935. https://doi.org/10.1137/0322060 doi: 10.1137/0322060
    [2] A. Cadenillas, P. Lakner, M. Pinedo, Optimal production management when demand depends on the business cycle, Oper. Res., 61 (2013), 1046–1062. https://doi.org/10.1287/opre.2013.1181 doi: 10.1287/opre.2013.1181
    [3] J. Dong, A. Malikopoulos, S. M. Djouadi, T. Kuruganti, Application of optimal production control theory for home energy management in a micro grid, 2016 American Control Conference (ACC), IEEE, (2016), 5014–5019.
    [4] A. Capponi, J. E. Figueroa-López, Dynamic Portfolio Optimization with a Defaultable Security and Regime-Switching, Math. Finance, 24 (2012), 207–249. https://doi.org/10.1111/j.1467-9965.2012.00522.x doi: 10.1111/j.1467-9965.2012.00522.x
    [5] R. Elliott, A. S. Hamada, Option pricing using a regime switching stochastic siscount factor, Int. J. Theor. Appl. Finance, 17 (2014), 1–26. https://doi.org/10.1142/S0219024914500204 doi: 10.1142/S0219024914500204
    [6] A. Gharbi, J. P. Kenne, Optimal production control problem in stochastic multiple-product multiple-machine manufacturing systems, IIE Trans., 35 (2003), 941–952. https://doi.org/10.1080/07408170309342346 doi: 10.1080/07408170309342346
    [7] D. D. Yao, Q. Zhang, X. Y. Zhou, A Regime-Switching Model for European Options, Stochastic Processes. Optimization, and Control Theory: applications in Financial Engineering, Queueing Networks, and Manufacturing systems, Springer, Boston, MA.
    [8] C. F. Wang, H. Chang, Z. M. Fang, Optimal Portfolio and Consumption Rule with a CIR Model Under HARA Utility, J. Oper. Res. Soc. China, 6 (2018), 107–137. https://doi.org/10.1007/s40305-017-0189-8 doi: 10.1007/s40305-017-0189-8
    [9] D. P. Covei, E. C. Canepa, T. A. Pirvu, Stochastic production planning with regime switching, J. Ind. Manag. Optim., 2022 (2022), 1–17. https://doi.org/10.3934/jimo.2022013 doi: 10.3934/jimo.2022013
    [10] D. P. Covei, An elliptic partial differential equation modeling the production planning problem, J. Appl. Anal. Comput., 11 (2021), 903–910. https://doi.org/10.11948/20200112 doi: 10.11948/20200112
    [11] D. P. Covei, T. A. Pirvu, A stochastic control problem with regime switching, Carpathian J. Math., 37 (2021), 427–440. https://doi.org/10.37193/CJM.2021.03.06 doi: 10.37193/CJM.2021.03.06
    [12] G. Barles, A. Porretta, T. T. Tchamba, On the large time behavior of solutions of the Dirichlet problem for subquadratic viscous Hamilton–Jacobi equations, J. Math. Pures Appl., 94 (2010), 497–519. https://doi.org/10.1016/j.matpur.2010.03.006 doi: 10.1016/j.matpur.2010.03.006
    [13] T. T. Tchamba, Large Time Behavior of Solutions of Viscous Hamilton-Jacobi Equations with Superquadratic Hamiltonian, Asymptot. Anal., 66 (2010), 161–186. https://doi.org/10.3233/ASY-2009-0965 doi: 10.3233/ASY-2009-0965
    [14] C. O. Alves, T. Boudjeriou, Existence of solution for a class of heat equation with double criticality, J. Math. Anal. Appl., 504 (2021), 125–403. https://doi.org/10.1016/j.jmaa.2021.125403 doi: 10.1016/j.jmaa.2021.125403
    [15] E. C. Canepa, D. P. Covei, T. A. Pirvu, A Stochastic production planning problem, Fixed Point Theory Appl., 23 (2022), 179–198. https://doi.org/10.24193/fpt-ro.2022.1.11 doi: 10.24193/fpt-ro.2022.1.11
    [16] G. dos Reis, D. Šiška, Stochastic Control and Dynamic Asset Allocation, Partial lecture notes, School of Mathematics, University of Edinburgh, 2020. Available from: https://www.maths.ed.ac.uk/dsiska/LecNotesSCDAA.pdf.
    [17] D. H. Sattinger, Topics in Stability and Bifurcation Theory, Lecture Notes in Mathematics, 309, Springer, Berlin, Heidelberg, 1973. https://doi.org/10.1007/BFb0060079
    [18] C. V. Pao, Nonlinear Parabolic and Elliptic Equations, Springer, Boston, MA, 1992. https://doi.org/10.1007/978-1-4615-3034-3
    [19] H. Amann, Quasilinear parabolic systems under nonlinear boundary conditions, Arch. Ration. Mech. Anal., 92 (1986), 153–192. https://doi.org/10.1007/BF00251255 doi: 10.1007/BF00251255
    [20] D. Gilbarg, N. S. Trudinger, Elliptic Partial Differential Equations of Second Order, Berlin: Springer-Verlag, 1983. https://doi.org/10.1007/978-3-642-61798-0
    [21] I. Győri, F. Hartung, N. A. Mohamady, Existence and uniqueness of positive solutions of a system of nonlinear algebraic equations, Period. Math. Hung., 75 (2017), 114–127. https://doi.org/10.1007/s10998-016-0179-3 doi: 10.1007/s10998-016-0179-3
    [22] I. Győri, F. Hartung, N. A. Mohamady, Boundedness of positive solutions of a system of nonlinear delay differential equations, Discrete Contin. Dyn. Syst. B, 23 (2018), 809–836. https://doi.org/10.1007/s10998-016-0179-3 doi: 10.1007/s10998-016-0179-3
    [23] L. Sheng, Y. Zhu, K. Wang, Uncertain dynamical system-based decision making with application to production-inventory problems, Appl. Math. Model., 56 (2018), 275–288. https://doi.org/10.1016/j.apm.2017.12.006 doi: 10.1016/j.apm.2017.12.006
    [24] M. K. Ghosh, A. Arapostathis, S. I. Marcus, Optimal Control of Switching Diffusions with Application to Flexible Manufacturing Systems, SIAM J. Control Optim., 31 (1992), 1183–1204. https://doi.org/10.1137/0331056 doi: 10.1137/0331056
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