海上物流业需求不确定班轮联盟舱位空箱协同配置联合优化

IF 8.8 1区 工程技术 Q1 ECONOMICS
Shaorui Zhou , Xiaorui Liu , Jihong Chen , Min Zhao , Fan Wang , Lingxiao Wu
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引用次数: 0

摘要

随着全球集装箱运输量的增长,集装箱班轮公司之间的合作日益增多。作为班轮联盟内部合作的一种方式,舱位共配已引起广泛关注。然而,由于班轮联盟需要预测未来不确定的需求来制定空箱调度计划,空箱重新定位和共配是必不可少的,但很少被考虑。针对此,本文通过考虑槽位和空箱共享,对槽位和空箱共配问题进行了联合优化。首先,我们提出了一个两阶段的随机规划模型来最小化班轮联盟的总成本。为了解决高维随机规划问题,我们提出了两种新的混合随机学习算法,它们利用网络结构,同时通过历史数据学习自适应逼近目标函数。最后,我们在南亚-东南亚海洋联盟的真实航线数据中对算法进行了测试。计算结果表明,本文提出的算法对需求不确定的班轮联盟的舱位和空箱共配联合优化具有良好的性能,并且从滚动地平线实验中可以得到一些有趣的管理启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint optimization of slot and empty container co-allocation for liner alliances with uncertain demand in maritime logistics industry
With the growth traffic of containerized shipping worldwide, container liners have seen increasing cooperation. Slot co-allocation has drawn wide attention as a way of cooperation within liner alliances. However, due to the need for liner alliances to predict uncertain future demands to formulate empty container scheduling plans, empty container repositioning and co-allocation are essential but seldom considered. In response to this, this paper jointly optimizes the slot and empty container co-allocation issues by considering slot and empty container sharing. First, we proposed a two-stage stochastic programming model to minimize the total cost of the liner alliance. To solve the high-dimensional stochastic programming problem, we then proposed two new hybrid stochastic learning algorithms, which utilize the network structure while adaptively approximating the objective function by learning from historical data. Finally, we tested our algorithm in the real route data of the Ocean Alliance between South Asia and Southeast Asia. Computational results indicate that the proposed algorithms exhibit effective and efficient performance for joint optimization of slot and empty container co-allocation for liner alliances with uncertain demand, and some interesting managerial insights can be drawn from the rolling-horizon experiments.
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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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