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Minimum cost berth allocation problem in maritime logistics: new mixed integer programming models

机译:海上物流的最低费用泊位分配问题:新的混合整数规划模型

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The berth allocation problem (BAP) involves decisions on how to allocate the berth space and to sequence maritime vessels that are to be loaded and unloaded at a container terminal involved in the maritime logistics. As the berth is a critical resource in a container terminal, an effective use of it is highly essential tohave efficient berthing and servicing of vessels, and to optimize the associated costs. This study focuses on the minimum cost berth allocation problem (MCBAP) at a container terminal where the maritime vessels arrive dynamically. The objective comprises the waiting time penalty, tardiness penalty, handling cost and benefit of early service completion of vessels. This paper proposes three computationally efficient mixed integer linear programming (MILP) models for the MCBAP. Through numerical experiments, the proposed MILP models arecompared to an existing model in the literature to evaluate their computational performance. The computational study with problem instances of various problem characteristics demonstrates the computational efficiency of the proposed models.
机译:泊位分配问题(BAP)涉及如何分配泊位空间以及如何对将在海上物流涉及的集装箱码头装卸的海上船舶进行排序的决定。由于泊位是集装箱码头中的重要资源,因此有效利用泊位对于高效泊位和维修船舶以及优化相关成本至关重要。这项研究的重点是海上船舶动态到达的集装箱码头的最小费用泊位分配问题(MCBAP)。目标包括等待时间的罚款,拖延时间的罚款,装卸成本以及船舶提早服务的收益。本文为MCBAP提出了三个计算有效的混合整数线性规划(MILP)模型。通过数值实验,将提出的MILP模型与文献中的现有模型进行比较,以评估其计算性能。对具有各种问题特征的问题实例的计算研究证明了所提出模型的计算效率。

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