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A Dynamic Hybrid Berth Allocation Problem with Routing Constraints in Bulk Ports

机译:批量端口中路由约束的动态混合泊位分配问题

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The Berth Allocation Problem (BAP) is considered as one of the most important operational problems in the seaside area of ports. It refers to the problem of assigning a set of vessels to a given berth layout within a given time horizon. In this paper, we study the dynamic and hybrid case of the BAP in the context of bulk ports with multiple quays, different water depths, and heterogeneous loading equipment, considering routing constraints (routes between storage hangars and berths). This study is motivated by the operations of OCP Group, a world leader in the phosphate industry, at the bulk port of Jorf Lasfar in Morocco, recognized as the largest ore port in Africa. The objective of the problem is to enhance the coordination between the berthing and yard activities, besides maximizing the difference between the despatch money and the demurrage charges of all berthed vessels. We propose an integer linear programming model formulated with predicates, which ensures maximum flexibility in the implementation of the model. Finally, the proposed model is tested and validated through numerical experiments based on instances inspired by real bulk port data. The results show that the model can be used to solve to optimality instances with up to 40 vessels within reasonable computational time.
机译:泊位分配问题(BAP)被认为是港口海滨领域最重要的业务问题之一。它是指在给定的时间范围内将一组船只分配给给定的泊位布局的问题。在本文中,考虑到路由约束(存储机库和泊位之间的路线),我们研究了在散装端口的上下文中研究了散装端口的动态和混合案例。本研究采用苏哥州摩洛哥的散装港,磷酸盐行业世界领导者的OCP集团的运作,被认为是非洲最大的矿港。问题的目的是提高Berthing和Yard活动之间的协调,除了最大化发货资金和所有拆除船只的统治费用之间的差异。我们提出了一个包含谓词的整数线性编程模型,可确保模型实现中的最大灵活性。最后,通过基于由真实批量端口数据的知识的实例通过数值实验进行测试和验证所提出的模型。结果表明,该模型可用于在合理的计算时间内在最多40个血管上解决最优性的情况。

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