Maritime transportation plays a significant role in international trade and global supply chains. Ship navigation safety is the foundation of operating maritime business smoothly. Recently, more and more attention has been paid to marine environmental protection. To enhance maritime safety and reduce pollution in the marine environment, various regulations and conventions are proposed by international organizations and local governments. One of the most efficient ways of ensuring that the related requirements are complied with by ships is ship inspection by port state control (PSC). In the procedure of ship inspection, a critical issue for the port state is how to select ships of higher risk for inspection and how to optimally allocate the limited inspection resources to these ships. In this study, we adopt prediction and optimization approaches to address the above issues. We first predict the number of ship deficiencies based on a k nearest neighbor (kNN) model. Then, we propose three optimization models which aim for a trade-off between the reward for detected deficiencies and the human resource cost of ship inspection. Specifically, we first follow the predict-then-optimize framework and develop a deterministic optimization model. We also establish two stochastic optimization models where the distribution of ship deficiency number is estimated by the predictive prescription method and the global prescriptive analysis method, respectively. Furthermore, we conduct a case study using inspection data at the Hong Kong port to compare the performances of the three optimization models, from which we conclude that the predictive prescription model is more efficient and effective for this problem.
Citation: Ran Yan, Ying Yang, Yuquan Du. Stochastic optimization model for ship inspection planning under uncertainty in maritime transportation[J]. Electronic Research Archive, 2023, 31(1): 103-122. doi: 10.3934/era.2023006
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Maritime transportation plays a significant role in international trade and global supply chains. Ship navigation safety is the foundation of operating maritime business smoothly. Recently, more and more attention has been paid to marine environmental protection. To enhance maritime safety and reduce pollution in the marine environment, various regulations and conventions are proposed by international organizations and local governments. One of the most efficient ways of ensuring that the related requirements are complied with by ships is ship inspection by port state control (PSC). In the procedure of ship inspection, a critical issue for the port state is how to select ships of higher risk for inspection and how to optimally allocate the limited inspection resources to these ships. In this study, we adopt prediction and optimization approaches to address the above issues. We first predict the number of ship deficiencies based on a k nearest neighbor (kNN) model. Then, we propose three optimization models which aim for a trade-off between the reward for detected deficiencies and the human resource cost of ship inspection. Specifically, we first follow the predict-then-optimize framework and develop a deterministic optimization model. We also establish two stochastic optimization models where the distribution of ship deficiency number is estimated by the predictive prescription method and the global prescriptive analysis method, respectively. Furthermore, we conduct a case study using inspection data at the Hong Kong port to compare the performances of the three optimization models, from which we conclude that the predictive prescription model is more efficient and effective for this problem.
In this article, we study the existence of infinitely many homoclinic solutions of the following fractional discrete p-Laplacian equations:
(−Δ1)spu(a)+V(a)|u(a)|p−2u(a)=λf(a,u(a)),in Z, | (1.1) |
where s∈(0,1) and p∈(1,∞) are fixed constants, V(a)∈R+, λ is a positive parameter, f(a,⋅) is a continuous function for all a∈Z and (−Δ1)sp is the fractional discrete p-Laplacian given by
(−Δ1)spu(a)=2∑b∈Z,b≠a|u(a)−u(b)|p−2(u(a)−u(b))Ks,p(a−b),in Z, |
where the discrete kernel Ks,p has the following property: There exist two constants 0<cs,p≤Cs,p, such that
{cs,p|d|1+ps≤Ks,p(d)≤Cs,p|d|1+ps,for alld∈Z∖{0};Ks,p(0)=0. | (1.2) |
The fractional operator has received more attention recent decades because of its many applications in the real world. Many scholars have paid attention to this kind of problem, and have produced a lot of classical works, see for example [1,2,3]. As a classical fractional operator, the fractional Laplacian has wide applications in various fields such as optimization, population dynamics and so on. The fractional Laplacian on R can be defined for 0<s<1 and ν∈C∞0(RN) as
(−Δ)sν(x)=CN,sP.V.∫RNν(x)−ν(y)|x−y|N+2sdy,x∈RN, |
where CN,s is a positive constant and P.V. denotes the Cauchy principle value. In various cases involving differential equations, the Laplace operator is replaced by either the fractional Laplace operator or other more general operators, and hence the existence results have been obtained by employing variational approaches, see for instance [4,5,6,7]. These alternative approaches have been found to offer improved descriptions of numerous phenomena observed in the natural world. Correspondingly, it is necessary to give some qualitative results by employing numerical analysis. The nonlocal feature of the fractional Laplacian is one of the important aspects to be considered in numerical methods, which makes it necessary to study the existence of solutions.
Let ZH denote a grid of fixed size H>0 on R, i.e., ZH={Ha|a∈Z}. In [8], the definition of the fractional discrete Laplacian on ZH is given by
(−ΔH)sν(a)=∑b∈Z,b≠a(ν(a)−ν(b))KHs(a−b), |
where s∈(0,1), ν∈ℓs={ν:ZH→R|∑ω∈Z|ν(ω)|(1+|ω|)1+2s<∞} and
KHs(a)={4sΓ(1/2+s)√π|Γ(−s)|⋅Γ(|a|−s)H2sΓ(|a|+1+s),a∈Z∖{0},0,a=0. |
The above discrete kernel KHs has the following property: There exist two constants 0<cs≤Cs, such that for all a∈Z∖{0} there holds
csH2s|a|1+2s≤KHs(a)≤CsH2s|a|1+2s. |
In [8], Ciaurri et al. also proved that if ν is bounded then lims→1−(−ΔH)sν(a)=−ΔHν(a), where ΔH is there discrete Laplacian on ZH, i.e.
ΔHν(a)=1H2(ν(a+1)−2ν(a)+ν(a−1)). |
Moreover, under some suitable conditions and H→0, the fractional Laplacian can be approximated by the fractional discrete Laplacian.
Subsequently, let us give some existence results on the fractional difference equations. Xiang et al. [9] first investigated the fractional discrete Laplacian equations based on variational methods:
{(−Δ1)sν(a)+V(a)ν(a)=λf(a,ν(a)),fora∈Z,ν(a)→0,as|a|→∞, | (1.3) |
where f(a,⋅) is a continuous function for all a∈Z, λ>0, V(a)∈R+ and
(−Δ1)sν(a)=2∑b∈Z,b≠a(ν(a)−ν(b))Ks(a−b),in Z. |
Using the mountain pass theorem and Ekeland's variational principle under some suitable conditions, they obtained two homoclinic solutions for problem (1.3). It is evident that when p=2, the discrete fractional p-Laplace operator corresponds to the discrete fractional Laplace operator. After that, Ju et al. [10] studied the following fractional discrete p-Laplacian equations
{(−Δ1)spν(d)+V(d)|ν(d)|p−2ν(d)=λa(d)|ν(d)|q−2ν(d)+b(d)|ν(d)|r−2ν(d),ford∈Z,ν(d)→0,as|d|→∞, | (1.4) |
where a∈ℓpp−q, b∈ℓ∞, 1<q<p<r<∞, λ>0, V(a)∈R+, (−Δ1)sp is the fractional discrete p-Laplacian. Under certain conditions, they employed the Nehari manifold method to achieve the existence of at least two homoclinic solutions for problem (1.4). In [11], Ju et al. investigated the existence of multiple solutions for the fractional discrete p-Laplacian equations with various nonlinear terms via different Clark's theorems. In a recent study conducted by Ju et al. in [12], it was demonstrated that using the fountain theorem and the dual fountain theorem under the same hypotheses, two separate sequences of homoclinic solutions were derived for the fractional discrete Kirchhoff-Schrödinger equations. Based on the findings from [8], it could be deduced that Eq.(1.3) can be reformulated as the renowned discrete version of the Schrödinger equation
−Δμ(ξ)+V(ξ)μ(ξ)=λf(ξ,μ(ξ)),in Z. | (1.5) |
It is worth mentioning that in [13], Agarwal et al. first employed the variational methods to analyze Eq.(1.5). Here, We give some literature on the study of difference equations using the critical point theory, see [14,15,16].
In particular, we observe that both the nonlinear terms in [11,12] have the following symmetry condition:
(S) f(a,ν) is odd in ν.
Therefore, in this paper, we consider the nonlinear term without condition (S), and study the existence of multiple homoclinic solutions of problem (1.1). For this, let us first recall if the solution ν of Eq.(1.1) satisfies ν(d)→0 as |d|→∞, then ν is called a homoclinic solution. Suppose that V(a) and f(a,u(a)) in problem (1.1) satisfy the following assumptions:
(V) V∈ℓ1 and there is a constant V0∈(0,infa∈ZV(a)]; (ℓ1 is defined in next section)
(F) |f(a,u)|≤C(|u|p−1+|u|t−1) for any a∈Z and u∈R, where p<t<∞ and C>0 is a constant.
Set
A:=lim infτ→0+max|ζ|≤τ∑a∈ZF(a,ζ(a))τp,B:=lim supτ→0+∑a∈ZF(a,τ(a))τp,θ:=CsV0Cb‖V‖1, |
where F(a,u)=∫u0f(a,η)dη and Cs, Cb will appear in next section. Here we give the main conclusion of our paper as follows.
Theorem 1.1. Suppose that (V) and (F) are satisfied. Furthermore, the following inequality holds: A<θB. Then, for every λ∈(Cb‖V‖1pB,CsV0pA), problem (1.1) possesses infinitely many nontrivial homoclinic solutions. In addition, their critical values and their ℓ∞-norms tend to zero.
The rest of this article is arranged as follows: In Section 2, we introduce some definitions and give some preliminary results. In Section 3, we give the proof of Theorem 1.1. In Section 4, we give an example to demonstrate the main result.
Here we illustrate some notations used in this paper:
● C, Cs,ω, Cs, Cb and C∞ are diverse positive constants.
● ↪ denotes the embedding.
● → denotes the strong convergence.
First we give some basic definitions.
Let 1≤ω≤∞, we give the definition of the space (ℓω,‖⋅‖ω) as follows:
ℓω:={{μ:Z→R|∑a∈Z|μ(a)|ω<∞},if1≤ω<∞;{μ:Z→R|supa∈Z|μ(a)|<∞},ifω=∞; |
‖μ‖ω:={(∑a∈Z|μ(a)|ω)1/ω,if1≤ω<∞;supa∈Z|μ(a)|,ifω=∞. |
Through the corresponding conclusions in [17], we know that ℓω is a Banach space. Moreover, ℓω1↪ℓω2 and ‖μ‖ω2≤‖μ‖ω1 if 1≤ω1≤ω2≤∞.
Next, we give the variational framework and some lemmas of this paper.
The space (Q,‖⋅‖Q) is defined by
Q={σ:Z→R|∑a∈Z∑b∈Z|σ(a)−σ(b)|pKs,p(a−b)+∑d∈ZV(d)|σ(d)|p<∞}; |
‖σ‖pQ=[σ]ps,p+∑d∈ZV(d)|σ(d)|p=∑a∈Z∑b∈Z|σ(a)−σ(b)|pKs,p(a−b)+∑d∈ZV(d)|σ(d)|p. |
Lemma 2.1. (see [10, Lemma 2.1]) If ξ∈ℓω, then [ξ]s,ω≤Cs,ω‖ξ‖ω<∞.
Lemma 2.2. (see [11, Lemma 2.2]) Under the hypothesis (V), (Q,‖⋅‖Q) is a reflexive Banach space, and
‖σ‖:=(∑a∈ZV(a)|σ(a)|p)1/p. |
is an equivalent norm of Q.
Through Lemma 2.2, we obtain that there exist 0≤Cs≤Cb such that
Cs‖μ‖p≤‖μ‖pQ≤Cb‖μ‖p. | (2.1) |
Lemma 2.3. Under the hypothesis (V), Q↪ℓr is continuous for all p≤r≤∞.
Proof. Using the above conclusions and (V), we can deduce that
‖σ‖r≤‖σ‖p=(∑a∈Z|σ(a)|p)1p≤V−1p0(∑a∈ZV(a)|σ(a)|p)1p,∀σ∈Q. |
As desired.
Lemma 2.4. (see [10, Lemma 2.4]) If W⊂Q is a compact subset, then for ∀ι>0, ∃a0∈N such that
[∑|a|>a0V(a)|ξ(a)|p]1/p<ι,for eachξ∈W. |
For all u∈Q, we define
K(u)=D(u)−λE(u) |
where
D(u)=1p∑a∈Z∑b∈Z|u(a)−u(b)|pKs,p(a−b)+1p∑d∈ZV(d)|u(d)|p=1p‖u‖pQ |
and
E(u)=∑d∈ZF(d,u(d)). |
Clearly
infQD(μ)=infQ1p‖μ‖pQ=D(0)=0. | (2.2) |
Lemma 2.5. (see [10, Lemma 2.5]) Under the hypothesis (V), then D(σ)∈C1(Q,R) with
⟨D′(σ),ξ⟩=∑a∈Z∑b∈Z|σ(a)−σ(b)|p−2(σ(a)−σ(b))(ξ(a)−ξ(b))Ks,p(a−b)+∑d∈ZV(d)|σ(d)|p−2σ(d)ξ(d), |
for all σ,ξ∈Q.
Lemma 2.6. (see [12, Lemma 2.6]) Under the hypotheses (V) and (F), then E(σ)∈C1(Q,R) with
⟨E′(σ),ξ⟩=∑d∈Zf(d,σ(d))ξ(d) |
for all σ,ξ∈Q.
Combining Lemma 2.5 and Lemma 2.6, we know that K(σ)∈C1(Q,R).
Lemma 2.7. Under the hypotheses (V) and (F), then for ∀λ>0, every critical point of K is a homoclinic solution of problem (1.1).
Proof. Assume σ be a critical point of K, we get for ∀ξ∈Q
∑a∈Z∑b∈Z|σ(a)−σ(b)|p−2(σ(a)−σ(b))(ξ(a)−ξ(b))Ks,p(a−b)+∑a∈ZV(a)|σ(a)|p−2σ(a)ξ(a)=λ∑a∈Zf(a,σ(a))ξ(a). | (2.3) |
For each a∈Z, we define ed∈Q as follows:
ed(a):={0,ifa≠d;1,ifa=d. |
Taking ξ=ed in (2.3), we have
2∑b∈Z,b≠a|u(a)−u(b)|p−2(u(a)−u(b))Ks,p(a−b)+V(a)|u(a)|p−2u(a)=λf(a,σ(a)). |
So σ is a solution of problem (1.1). Moreover, by Lemma 2.3 and σ∈Q, we know σ(a)→0 as |a|→∞. Thus, σ is a homoclinic solution of problem (1.1).
In this section, we shall use the following Thoerem 3.1 to prove our main result. In fact, this theorem is a special version of Ricceri's variational principle [18, Lemma 2.5].
Theorem 3.1. (see [19, Lemma 2.1]) Let Q be a reflexive Banach space, K(μ):=D(μ)+λE(μ) for each μ∈Q, where D,E∈C1(Q,R), D is coercive, and λ is a real positive parameter. For every γ>infQD(μ), let
η(γ):=infμ∈D−1((−∞,γ))(supν∈D−1((−∞,γ))E(ν))−E(μ)γ−D(μ), |
and
ρ:=lim infγ→(infQD(μ))+η(γ) |
If ρ<+∞, then for every λ∈(0,1ρ), the following conclusions holds only one:
(a) there exists a global minimum of D which is a local minimum of K.
(b) there exists a sequence {μm} of pairwise distinct critical points (local minima) of K, with limm→∞D(μm)=infQD(μ), which converges to a global minimum of D.
Remark 3.1. Obviously, ρ≥0. In addition, when ρ=0, we think that 1ρ=+∞.
Proof of Theorem 1.1. Let us recall
A=lim infτ→0+max|ζ|≤τ∑a∈ZF(a,ζ(a))τp,B=lim supτ→0+∑a∈ZF(a,τ(a))τp,θ=CsV0Cb‖V‖1, |
where F(a,u)=∫u0f(a,ω)dω. Fix λ∈(Cb‖V‖1pB,CsV0pA) and set K,D,E as in Section 2. By Lemma 2.2, Lemma 2.5 and Lemma 2.6, we know Q be a reflexive Banach space and D,E∈C1(Q,R). Because of
D(μ)=1p∑a∈Z∑b∈Z|μ(a)−μ(b)|pKs,p(a−b)+1p∑d∈ZV(d)|μ(d)|p=1p‖μ‖pQ→+∞ |
as ‖μ‖Q→+∞, i.e. D is coercive. Now, we show that ρ<+∞. For this purpose, let {δn} be a positive sequence such that limn→∞δn=0 and
limn→∞max|ζ|≤δn∑a∈ZF(a,ζ(a))δpn=A. |
Put
γn:=CsV0pδpn, |
for all n∈N. Clearly, limn→∞γn=0. For n>0 is big enough, by Lemma 2.2 and (2.1), we can derive that
D−1((−∞,γn))⊂{ν∈Q:|ν(d)|≤δn,d∈Z}. | (3.1) |
Since D(0)=E(0)=0, for each n large enough, by (3.1), we get
η(γn)=infμ∈D−1((−∞,γn))(supν∈D−1((−∞,γn))∑a∈ZF(a,ν(a)))−E(μ)γn−D(μ)≤(supν∈D−1((−∞,γn))∑a∈ZF(a,ν(a)))−E(0)γn−D(0)=supν∈D−1((−∞,γn))∑a∈ZF(a,ν(a))γn≤max|w|≤δn∑a∈ZF(a,w(a))γn=pmax|w|≤δn∑a∈ZF(a,w(a))CsV0δpn. |
Therefore, by (2.2), we acquire that
ρ=lim infγ→(infQD(μ))+η(γ)=lim infγn→0+η(γn)≤limn→∞η(γn)≤limn→∞pmax|w|≤δn∑a∈ZF(a,w(a))CsV0δpn=pACsV0. | (3.2) |
From (3.2), we get
λ∈(Cb‖V‖1pB,CsV0pA)⊂(0,1ρ). |
Next, we verify that 0 is not a local minimum of K. First, suppose that B=+∞. Choosing M such that M>Cb‖V‖1pλ and let {hn} be a sequence of positive numbers, with limn→∞hn=0, there exists n1∈N such that for all n≥n1
∑a∈ZF(a,hn)>Mhpn. | (3.3) |
Therefore, let {ln} be a sequence in Q defined by
ln(a):=hn,for alla∈Z. |
It is easy to infer that ‖ln(a)‖Q→0 as n→∞. By (V), (2.1) and (3.3), we obtain
K(ln)=D(ln)−λE(ln)=1p‖ln‖pQ−λ∑a∈ZF(a,ln)=1p‖ln‖pQ−λ∑a∈ZF(a,hn)≤Cbp‖ln‖p−λ∑a∈ZF(a,hn)=Cbp∑a∈ZV(a)|ln(a)|p−λ∑a∈ZF(a,hn)=Cbp(∑a∈ZV(a))|hn|p−λ∑a∈ZF(a,hn)<Cbp‖V‖1hpn−λMhpn=(Cbp‖V‖1−λM)hpn. |
So, K(ln)<0=K(0) for each n≥n1 big enough. Next, suppose that B<+∞. Since λ>Cb‖V‖1pB, there exists ε>0 such that ε<B−Cb‖V‖1pλ. Hence, also choosing {hn} be a sequence of positive numbers, with limn→∞hn=0, there is n2∈N such that for all n≥n2
∑a∈ZF(a,hn)>(B−ε)hpn. | (3.4) |
Arguing as before and by choosing {ln} in Q as above, we get
K(ln)=D(ln)−λE(ln)=1p‖ln‖pQ−λ∑a∈ZF(a,ln)=1p‖ln‖pQ−λ∑a∈ZF(a,hn)≤Cbp‖ln‖p−λ∑a∈ZF(a,hn)=Cbp∑a∈ZV(a)|ln(a)|p−λ∑a∈ZF(a,hn)=Cbp(∑a∈ZV(a))|hn|p−λ∑a∈ZF(a,hn)<Cbp‖V‖1hpn−λ(B−ε)hpn=(Cbp‖V‖1−λ(B−ε))hpn. |
So, K(ln)<0=K(0) for each n≥n2 big enough. In general, 0 is not a local minimum of K. By Theorem 3.1, (a) is not valid, then we have a sequence {μn}⊂Q of critical points of K such that
limn→∞D(μn)=limn→∞1p‖μn‖Q=infQD(μ)=0 |
and
limn→∞K(μn)=infQD(μ)=0. |
By Lemma 2.3, we gain
‖μn‖∞≤C∞‖μn‖Q→0 |
as n→∞. By Lemma 2.7, the problem (1.1) admits infinitely many nontrivial homoclinic solutions. In addition, their critical values and their ℓ∞-norms tend to zero. This completes the proof.
Here, we give an example of a nonlinear term which can apply Theorem 1.1.
Example 4.1. We define
Ψ(n):=1333n,forn∈N+; |
Φ(n):=1333n−1,forn∈N+; |
χ(n):=13(p+1)33n−3,forn∈N+. |
Obviously, we know that Φ(n+1)<Ψ(n)<Φ(n) for all n∈N+ and limn→∞Ψ(n)=limn→∞Φ(n)=0. Set
f(a,u)=0,∀a∈Z∖N+. |
And for each a∈N+, let f(a,⋅) is a nonnegative continuous function such that
f(a,u)=0,∀u∈R∖(Ψ(a),Φ(a))and∫Φ(a)Ψ(a)f(a,η)dη=χ(a). |
There are many nonlinear terms that satisfy the above conditions. Here we give one of them as an example.
f(a,u)=∑n∈N+χ(n)2((u+Φ(n)+Ψ(n)2)2Φ2(n)−Ψ2(n))e{n}×[Ψ(n),Φ(n)](a,u) |
where eM×N is the indicator function on M×N. Then
A=lim infτ→0+max|ζ|≤τ∑a∈ZF(a,ζ(a))τp≤limn→∞max|ζ|≤Ψ(n)∑a∈ZF(a,ζ(a))Ψp(n)=limn→∞∑∞a=n+1F(a,ζ(a))Ψp(n)=limn→∞∑∞a=n+1χ(a)Ψp(n)≤limn→∞3χ(n+1)Ψp(n)=0 |
and
B=lim supτ→0+∑a∈ZF(a,ζ(a))τp≥limn→∞∑a∈ZF(a,ζ(a))Φp(n)≥limn→∞F(n,ζ(n))Φp(n)≥limn→∞χ(n)Φp(n)=+∞. |
Now it is easy to see that all the assumptions of Theorem 1.1 are satisfied, hence the corresponding conclusion can be delivered by Theorem 1.1.
B. Zhang was supported by the National Natural Science Foundation of China (No. 12171152), the Shandong Provincial Natural Science Foundation, PR China (No. ZR2023MA090) and the Cultivation Project of Young and Innovative Talents in Universities of Shandong Province.
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
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