Container Relocation and Retrieval Tradeoffs Minimizing Schedule Deviations and Relocations

IF 4.6 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Open Journal of Intelligent Transportation Systems Pub Date : 2024-06-12 DOI:10.1109/OJITS.2024.3413197
Robert Klar;Anders Andersson;Anna Fredriksson;Vangelis Angelakis
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Abstract

Ports are striving to improve operational efficiency in the context of constantly growing volumes of trade. In this context, port terminal storage yard operation is key, since complexity and poor coordination lead to containers stacked without consideration of retrieval schedules, resulting in time- and energy-consuming reshuffling operations. This problem, known as the block relocation (and retrieval) problem (BRP), has recently gained considerable attention. Indeed, there are promising solutions to the BRP. However, the literature views the problem in isolation, optimizing one operational parameter for one of the many port stakeholders. This often leads to efficiency losses since port processes involve different stakeholders and port parts. In this work, we explicitly focus on scheduling trucks for pick-up for hinterland distribution. Appointments are often postponed in order to minimize reshuffling operations, leading to losses for the transport forwarders and decreasing the competitiveness of the port. We discuss the trade-off between minimizing container reshuffling operations while maintaining scheduled time windows for container retrieval. We describe the multi-objective optimization problem as a weighted sum of the two objectives. Given the complexity of the problem, we also present a greedy heuristic. Our results indicate that the number of schedule deviations can be reduced without significantly affecting the number of relocations compared to solutions that consider only the latter. Ideally, a weighting of 0.4 and 0.6 should be applied, reflecting schedule deviations and relocations, respectively, to achieve the highest joint optimization potential. This demonstrates that in complex environments, such as ports, with multiple interacting stakeholders and processes, coordination of solutions yields significant benefits.
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集装箱搬迁和取回的权衡 尽量减少时间表偏差和搬迁
在贸易量不断增长的情况下,港口正在努力提高运营效率。在这种情况下,港口码头堆场的运营是关键,因为复杂性和协调性差会导致集装箱堆放时不考虑检索时间表,从而造成耗时耗力的重新洗牌操作。这个问题被称为 "区块搬迁(和检索)问题"(BRP),最近受到了广泛关注。事实上,BRP 已经有了很好的解决方案。然而,相关文献孤立地看待这个问题,为众多港口利益相关者中的一个优化操作参数。这往往会导致效率损失,因为港口流程涉及不同的利益相关者和港口部分。在这项工作中,我们明确将重点放在为腹地配送安排卡车取货上。为了尽量减少重新洗牌操作,通常会推迟预约,从而导致运输代理公司的损失,并降低港口的竞争力。我们讨论了如何在尽量减少集装箱重新洗牌操作的同时,保持集装箱检索的预定时间窗口之间进行权衡。我们将多目标优化问题描述为两个目标的加权和。考虑到问题的复杂性,我们还提出了一种贪婪启发式。我们的结果表明,与只考虑后者的解决方案相比,可以在不明显影响搬迁数量的情况下减少计划偏差的数量。理想情况下,应采用 0.4 和 0.6 的权重,分别反映进度偏差和重新定位,以实现最高的联合优化潜力。这表明,在港口等复杂环境中,多个利益相关者和流程相互影响,协调解决方案可产生显著效益。
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