不确定条件下自动化集装箱码头的堆场模板生成

IF 8.3 1区 工程技术 Q1 ECONOMICS
Mingzhong Huang , Junliang He , Hang Yu , Yu Wang
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引用次数: 0

摘要

本文探讨了在船舶抵达时间表不确定的情况下,自动化集装箱码头的堆场模板生成问题。由于堆场是码头运营的核心,因此堆场管理直接影响到大多数设备的效率。堆场模板作为战术层面的堆场管理策略,为每周靠港的船舶分配堆场空间。通过分析各种设备的操作要求,制定出以堆场为决策单元的堆场模板。由于堆场模板将长期运行,因此必须考虑潜在的不确定性。这样,堆场模板就能在整个运营期间有效地管理堆场。因此,我们制定了一个两阶段随机编程模型,以生成不确定情况下的堆场模板。设计了一种具有多种加速策略的改进 Benders 分解算法来求解所提出的模型。通过数值实验验证了所提算法的效率。此外,还获得了一些管理启示,如不确定的船舶抵达时间表对基于堆栈的堆场模板的影响,以及不确定情况下堆栈策略的比较分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stack-based yard template generation in automated container terminals under uncertainty
This paper addresses yard template generation problem in automated container terminals when the vessel arrival schedule is uncertain. Since the yard is central to terminal operations, yard management directly affects the efficiency of most equipment. Yard template functions as a tactical-level yard management strategy, allocating yard space to vessels that call at the port on a weekly basis. By analyzing the operational requirements of the various equipment, a yard template is developed in which the stack is the decision unit. Since the yard template will be in operation for an extended period of time, it is critical to account for potential uncertainty. This allows the yard template to effectively manage the yard throughout its duration. Accordingly, a two-stage stochastic programming model is formulated to generate yard template under uncertainty. An improved Benders decomposition algorithm with multiple acceleration strategies is designed to solve the proposed model. The efficiency of the proposed algorithm is validated by numerical experiments. Moreover, some management insights are obtained, such as the impact of uncertain vessel arrival schedule on stack-based yard template and a comparative analysis of stacking strategies in the context of uncertainty.
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来源期刊
CiteScore
16.20
自引率
16.00%
发文量
285
审稿时长
62 days
期刊介绍: Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management. Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.
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