Cloud manufacturing (CM) establishes a collaborative manufacturing services chain among dispersed producers, which enables the efficient satisfaction of personalized manufacturing requirements. To further strengthen this effect, the manufacturing service composition and optimal selection (SCOS) in CM, as a NP-hard combinatorial problem, is a crucial issue. Quality of service (QoS) attributes of manufacturing services, as the basic criterion of functions and capabilities, are decisive criterions of SCOS. However, most traditional QoS attributes of CM ignore the dynamic equilibrium of manufacturing services and only rely on initial static characterizations such as reliability and availability. In a high uncertainty and dynamicity environment, a major concern is the equilibrium of manufacturing services for recovering their functions after dysfunctional damage. Therefore, this paper proposes a hybrid resilience-aware global optimization (HRGO) approach to address the SCOS problem in CM. This approach helps manufacturing demanders to acquire efficient, resilient, and satisfying manufacturing services. First, the problem description and resilience measurement method on resilience-aware SCOS is modeled. Then, a services filter strategy, based on the fuzzy similarity degree, is introduced to filter redundant and unqualified candidate services. Finally, a modified non-dominated sorting genetic algorithm (MNSGA-III) is proposed, based on diversity judgment and dualtrack parallelism, to address combination optimization processing in SCOS. A series of experiments were conducted, the results show the proposed method is more preferable in optimal services searching and more efficient in scalability.
Citation: Hao Song, Xiaonong Lu, Xu Zhang, Xiaoan Tang, Qiang Zhang. A HRGO approach for resilience enhancement service composition and optimal selection in cloud manufacturing[J]. Mathematical Biosciences and Engineering, 2020, 17(6): 6838-6872. doi: 10.3934/mbe.2020355
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Cloud manufacturing (CM) establishes a collaborative manufacturing services chain among dispersed producers, which enables the efficient satisfaction of personalized manufacturing requirements. To further strengthen this effect, the manufacturing service composition and optimal selection (SCOS) in CM, as a NP-hard combinatorial problem, is a crucial issue. Quality of service (QoS) attributes of manufacturing services, as the basic criterion of functions and capabilities, are decisive criterions of SCOS. However, most traditional QoS attributes of CM ignore the dynamic equilibrium of manufacturing services and only rely on initial static characterizations such as reliability and availability. In a high uncertainty and dynamicity environment, a major concern is the equilibrium of manufacturing services for recovering their functions after dysfunctional damage. Therefore, this paper proposes a hybrid resilience-aware global optimization (HRGO) approach to address the SCOS problem in CM. This approach helps manufacturing demanders to acquire efficient, resilient, and satisfying manufacturing services. First, the problem description and resilience measurement method on resilience-aware SCOS is modeled. Then, a services filter strategy, based on the fuzzy similarity degree, is introduced to filter redundant and unqualified candidate services. Finally, a modified non-dominated sorting genetic algorithm (MNSGA-III) is proposed, based on diversity judgment and dualtrack parallelism, to address combination optimization processing in SCOS. A series of experiments were conducted, the results show the proposed method is more preferable in optimal services searching and more efficient in scalability.
G. Caginalp introduced in [1] and [2] the following phase-field systems:
∂u∂t+Δ2u−Δf(u)=−Δθ, | (1.1) |
∂θ∂t−Δθ=−∂u∂t, | (1.2) |
where
Equations (1.1) and (1.2) are based on the total free energy
ψ(u,θ)=∫Ω(12|∇u|2+F(u)−uθ−12θ2)dx, | (1.3) |
where
H=−∂θψ, | (1.4) |
where
H=u+θ. | (1.5) |
The gouverning equations for
∂u∂t=Δ∂uψ, | (1.6) |
∂H∂t=−divq, | (1.7) |
where
q=−∇θ, | (1.8) |
we obtain (1.1) and (1.2).
Now, one drawback of the Fourier law is that it predicts that thermal signals propagate with an infinite speed, which violates causality (the so-called "paradox of heat conduction", see, e.g. [5]). Therefore, several modifications of (1.8) have been proposed in the literature to correct this unrealistic feature, leading to a second order in time equation for the temperature.
In particular, we considered in [15] (see also [19] the Maxwell-Cattaneo law)
(1+η∂∂t)q=−∇θ,η>0, | (1.9) |
which leads to
η∂2θ∂t2+∂θ∂t−Δθ=−η∂2u∂t2−∂u∂t. | (1.10) |
Green and Naghdi proposed in [21] an alternative treatment for a thermomechanical theory of deformable media. This theory is based on an entropy balance rather than the usual entropy inequality and is proposed in a very rational way. If we restrict our attention to the heat conduction, we recall that proposed three different theories, labelled as type Ⅰ, type Ⅱ and type Ⅲ, respectively. In particular, when type Ⅰ is linearized, we recover the classical theory based on the Fourier law. The linearized versions of the two other theories are decribed by the constitutive equation of type Ⅱ (see [12])
q=−k∇α,k>0, | (1.11) |
where
α(t)=∫tt0θ(τ)dτ+α0 | (1.12) |
is called the thermal displacement variable. It is pertinent to note that these theories have received much attention in the recent years.
If we add the constitutive equation (1.9) to equation (1.7), we then obtain the following equations for
∂2α∂t2−kΔα=−∂u∂t. | (1.13) |
Our aim in this paper is to study the model consisting the equation (1.1) (
We consider the following initial and boundary value problem (for simplificity, we take
∂u∂t+Δ2u−Δf(u)=−Δ∂α∂t, | (2.1) |
∂2α∂t2−Δα=−∂u∂t, | (2.2) |
u=Δu=α=0onΓ, | (2.3) |
u|t=0=u0,α|t=0=α0,∂α∂t|t=0=α1, | (2.4) |
where
We make the following assumptions:
f is of class C2(R),f(0)=0, | (2.5) |
f′(s)⩾−c0,c0⩾0,s∈R, | (2.6) |
f(s)s⩾c1F(s)−c2⩾−c3,c1>0,c2,c3⩾0,s∈R, | (2.7) |
where
We futher assume that
u0∈H10(Ω)∩H2(Ω). | (2.8) |
Remark 2.1. We take here, for simplicity, Dirichlet boundary conditions. However, we can obtain the same results for Neumann boundary conditions, namely,
∂u∂ν=∂Δu∂ν=∂α∂ν=0onΓ, | (2.9) |
where
∂¯u∂t+Δ2¯u−Δ(f(u)−⟨f(u)⟩)=−Δ∂¯α∂t, | (2.10) |
∂2¯α∂t2−Δ¯α=−∂¯u∂t, | (2.11) |
where
v↦(‖(−Δ)−12¯v‖2+⟨v⟩2)12, |
where, here,
⟨.⟩=1vol(Ω)⟨.,1⟩H−1(Ω),H1(Ω). |
Furthermore,
v↦(‖¯v‖2+⟨v⟩2)12, |
v↦(‖∇¯v‖2+⟨v⟩2)12, |
and
v↦(‖Δ¯v‖2+⟨v⟩2)12 |
are norms in
|f(s)|⩽ϵF(s)+cϵ,∀ϵ>0,s∈R, | (2.12) |
which allows to deal with term
We denote by
Throughout this paper, the same letters
The estimates derived in this section are formal, but they can easily be justified within a Galerkin scheme.
We rewrite (2.1) in the equivalent form
(−Δ)−1∂u∂t−Δu+f(u)=∂α∂t. | (3.1) |
We multiply (3.1) by
ddt(‖∇u‖2+2∫ΩF(u)dx)+2‖∂u∂t‖2−1=2((∂α∂t,∂u∂t)). | (3.2) |
We then multiply (2.2) by
ddt(‖∇α‖2+‖∂α∂t‖2)=−2((∂α∂t,∂u∂t)). | (3.3) |
Summing (3.2) and (3.3), we find a differential inequality of the form
dE1dt+c‖∂u∂t‖2−1⩽c′,c>0, | (3.4) |
where
E1=‖∇u‖2+2∫ΩF(u)dx+‖∇α‖2+‖∂α∂t‖2 |
satisfies
E1⩾c(‖u‖H1(Ω)+∫ΩF(u)dx+‖α‖2H1(Ω)+‖∂α∂t‖2)−c′,c>0, | (3.5) |
hence estimates on
We multiply (3.1) by
12ddt‖Δu‖2+‖∂u∂t‖2=((Δf(u),∂u∂t))−((Δ∂α∂t,∂u∂t)), |
which yields, owing to (2.5) and the continuous embedding
ddt‖Δu‖2+‖∂u∂t‖2⩽Q(‖u‖H2(Ω))−2((Δ∂α∂t,∂u∂t)). | (3.6) |
Multiplying also (2.2) by
ddt(‖Δα‖2+‖∇∂α∂t‖2)=2((Δ∂α∂t,∂u∂t)). | (3.7) |
Summing then (3.6) and (3.7), we obtain
ddt(‖Δu‖2+‖Δα‖2+‖∇∂α∂t‖2)+‖∂u∂t‖2⩽Q(‖u‖H2(Ω)). | (3.8) |
In particular, setting
y=‖Δu‖2+‖Δα‖2+‖∇∂α∂t‖2, |
we deduce from (3.8) an inequation of the form
y′⩽Q(y). | (3.9) |
Let z be the solution to the ordinary differential equation
z′=Q(z),z(0)=y(0). | (3.10) |
It follows from the comparison principle that there exists
y(t)⩽z(t),∀t∈[0,T0], | (3.11) |
hence
‖u(t)‖2H2(Ω)+‖α(t)‖2H2(Ω)+‖∂α∂t(t)‖2H1(Ω)⩽Q(‖u0‖H2(Ω),‖α0‖H2(Ω),‖α1‖H1(Ω)),t⩽T0. | (3.12) |
We now differentiate (3.1) with respect to time and have, noting that
(−Δ)−1∂∂t∂u∂t−Δ∂u∂t+f′(u)∂u∂t=Δα−∂u∂t. | (3.13) |
We multiply (3.13) by
ddt(t‖∂u∂t‖2−1)+32t‖∇∂u∂t‖2⩽ct(‖∂u∂t‖2+‖∇α‖2)+‖∂u∂t‖2−1, |
hence, noting that
ddt(t‖∂u∂t‖2−1)+t‖∇∂u∂t‖2⩽ct(‖∂u∂t‖2−1+‖∇α‖2)+‖∂u∂t‖2−1. | (3.14) |
In particular, we deduce from (3.4), (3.12), (3.14) and Gronwall's lemma that
‖∂u∂t‖2−1⩽1tQ(‖u0‖H2(Ω),‖α0‖H2(Ω),‖α1‖H1(Ω)),t∈(0,T0]. | (3.15) |
Multiplying then (3.13) by
ddt‖∂u∂t‖2−1+‖∇∂u∂t‖2⩽c(‖∂u∂t‖2−1+‖∇α‖2). | (3.16) |
It thus follows from (3.4), (3.16) and Gronwall's lemma that
‖∂u∂t‖2−1⩽ectQ(‖u0‖H2(Ω),‖α0‖H2(Ω),‖α1‖H1(Ω))‖∂u∂t(T0)‖2−1,t⩾T0, | (3.17) |
hence, owing to (3.15),
‖∂u∂t‖2−1⩽ectQ(‖u0‖H2(Ω),‖α0‖H2(Ω),‖α1‖H1(Ω)),t⩾T0. | (3.18) |
We now rewrite (3.1) in the forme
−Δu+f(u)=hu(t),u=0onΓ, | (3.19) |
for
hu(t)=−(−Δ)−1∂u∂t+∂α∂t | (3.20) |
satisfies, owing to (3.4) and (3.18)
‖hu(t)‖⩽ectQ(‖u0‖H2(Ω),‖α0‖H2(Ω),‖α1‖H1(Ω)),t⩾T0. | (3.21) |
We multiply (3.19) by
‖∇u‖2⩽c‖hu(t)‖2+c′. | (3.22) |
Then, multipying (3.19) by
‖Δu‖2⩽c(‖hu(t)‖2+‖∇u‖2). | (3.23) |
We thus deduce from
‖u(t)‖2H2(Ω)⩽ectQ(‖u0‖H2(Ω),‖α0‖H2(Ω),‖α1‖H1(Ω)),t⩾T0, | (3.24) |
and, thus, owing to (3.12)
‖u(t)‖2H2(Ω)⩽ectQ(‖u0‖H2(Ω),‖α0‖H2(Ω),‖α1‖H1(Ω)),t⩾0. | (3.25) |
Returning to (3.7), we have
ddt(‖Δα‖2+‖∇∂α∂t‖2)⩽‖Δ∂α∂t‖2+‖∂u∂t‖2. | (3.26) |
Noting that it follows from (3.4), (3.16) and (3.18) that
∫tT0(‖Δ∂α∂t‖2+‖∂u∂t‖2)dτ⩽ectQ(‖u0‖H2(Ω),‖α0‖H2(Ω),‖α1‖H1(Ω)),t⩾T0, | (3.27) |
we finally deduce from (3.12) and
‖u(t)‖2H2(Ω)+‖α(t)‖2H2(Ω)+‖∂α∂t(t)‖2H1(Ω)⩽ectQ(‖u0‖H2(Ω),‖α0‖H2(Ω),‖α1‖H1(Ω)),t⩾0. | (3.28) |
We first have the following.
Theorem 4.1. We assume that
u,α∈L∞(0,T;H10(Ω)∩H2(Ω)),∂u∂t∈L2(0,T;H−1(Ω))and∂α∂t∈L∞(0,T;H10(Ω)). |
Proof. The proof is based on (3.28) and, e.g., a standard Galerkin scheme.
We have, concerning the uniqueness, the following.
Theorem 4.2. We assume that the assumptions of Theorem
Proof. Let
(u,α,∂α∂t)=(u(1),α(1),∂α(1)∂t)−(u(2),α(2),∂α(2)∂t) |
and
(u0,α0,α1)=(u(1)0,α(1)0,α(1)1)−(u(2)0,α(2)0,α(2)1). |
Then,
∂u∂t+Δ2u−Δ(f(u(1))−f(u(2)))=−Δ∂α∂t, | (4.1) |
∂2α∂t2−Δα=−∂u∂t, | (4.2) |
u=α=0on∂Ω, | (4.3) |
u|t=0=u0,α|t=0=α0,∂α∂t|t=0=α1. | (4.4) |
We multiply (4.1) by
ddt(‖∇u‖2+‖∇α‖2+‖∂α∂t‖2)+‖∂u∂t‖2−1⩽‖∇(f(u(1))−f(u(2)))‖2. | (4.5) |
Furthermore,
‖∇(f(u(1))−f(u(2))‖=‖∇(∫10f′(u(1)+s(u(2)−u(1)))dsu)‖⩽‖∫10f′(u(1)+s(u(2)−u(1)))ds∇u‖+‖∫10f″(u(1)+s(u(2)−u(1)))(∇u(1)+s∇(u(2)−u(1)))dsu‖⩽Q(‖u(1)0‖H2(Ω),‖u(2)0‖H2(Ω),‖α(1)0‖H1(Ω),‖α(2)0‖H1(Ω),‖α(1)1‖H1(Ω),‖α(2)1‖H1(Ω))×(‖∇u‖+‖|u||∇u(1)|‖+‖|u||∇u(2)|‖)⩽Q(‖u(1)0‖H2(Ω),‖u(2)0‖H2(Ω),‖α(1)0‖H1(Ω),‖α(2)0‖H1(Ω),‖α(1)1‖H1(Ω),‖α(2)1‖H1(Ω))‖∇u‖. | (4.6) |
We thus deduce from (4.5) and (4.6) that
ddt(‖∇u‖2+‖∇α‖2+‖∂α∂t‖2)+‖∂u∂t‖2−1⩽Q(‖u(1)0‖H2(Ω),‖u(2)0‖H2(Ω),‖α(1)0‖H1(Ω),‖α(2)0‖H1(Ω),‖α(1)1‖H1(Ω),‖α(2)1‖H1(Ω))‖∇u‖2. | (4.7) |
In particular, we have a differential inequality of the form
dE2dt⩽QE2, | (4.8) |
where
E2=‖∇u‖2+‖∇α‖2+‖∂α∂t‖2 |
satisfies
E2⩾c(‖u‖2H1(Ω)+‖α‖2H1(Ω)+‖∂α∂t‖2)−c′. | (4.9) |
It follows from
‖u(t)‖2H1(Ω)+‖α(t)‖2H1(Ω)+‖∂α∂t(t)‖2⩽ceQt(‖u0‖2H1(Ω)+‖α0‖2H1(Ω)+‖α1‖2),t⩾0, | (4.10) |
hence the uniqueness, as well as the continuous dependence with respect to the initial data in the
The authors wish to thank the referees for their careful reading of the paper and useful comments.
All authors declare no conflicts of interest in this paper.
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