海上运输不确定条件下船舶检验规划的随机优化模型

IF 1 4区 数学 Q1 MATHEMATICS
Ran Yan, Ying Yang, Yuquan Du
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引用次数: 3

摘要

海运在国际贸易和全球供应链中发挥着重要作用。船舶航行安全是航海事业顺利经营的基础。近年来,海洋环境保护越来越受到人们的重视。为了加强海上安全,减少对海洋环境的污染,国际组织和地方政府提出了各种法规和公约。确保船舶遵守相关要求的最有效方法之一是由港口国监督(PSC)进行船舶检验。在船舶检验过程中,港口国面临的一个关键问题是如何选择风险较高的船舶进行检验,并将有限的检验资源最优地分配给这些船舶。在本研究中,我们采用预测和优化的方法来解决上述问题。我们首先基于k近邻(kNN)模型预测船舶缺陷的数量。然后,我们提出了三个优化模型,目的是在检测缺陷的奖励和船舶检验的人力资源成本之间进行权衡。具体而言,我们首先遵循预测-优化框架,并建立了确定性优化模型。建立了两种随机优化模型,分别采用预测处方法和全局规范分析法估计船舶缺陷数的分布。此外,我们以香港口岸的检验数据为例,比较了三种优化模型的性能,得出预测处方模型在解决这一问题上更为高效和有效的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic optimization model for ship inspection planning under uncertainty in maritime transportation
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.
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来源期刊
CiteScore
1.30
自引率
12.50%
发文量
170
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