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Two-stage stochastic programming model for generating container yard template under uncertainty and traffic congestion

机译:不确定和交通拥挤情况下生成集装箱堆场模板的两阶段随机规划模型

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摘要

Yard template is a space assignment at the tactical level, which is kept unchanged within a long period of time and significantly impacts the handling efficiency of a container terminal. This paper addresses a yard template planning problem considering uncertainty and traffic congestion. A two-stage stochastic programming model is formulated for minimizing the risk of containers with no available slots in the designated yard area and minimizing total transportation distances. The first-stage model is formulated for assigning vessels in each block without considering the physical location properties of blocks, and the second-stage model is formulated for designating physical locations to all blocks. Subsequently, a solving framework based on genetic algorithm is proposed for solving the first-stage model, and the CPLEX (a commercial solver) is used for solving the second-stage model. Finally, numerical experiments and scenario analysis are conducted to validate the effectiveness of the proposed model and the efficiency of the proposed solution approach. Yard template;
机译:堆场模板是战术级别的空间分配,可在很长一段时间内保持不变,并显着影响集装箱码头的装卸效率。本文针对考虑不确定性和交通拥堵的院子模板规划问题。制定了一个两阶段的随机规划模型,以最大程度地减少指定堆场中没有可用插槽的集装箱风险,并缩短总运输距离。制定第一阶段模型以在不考虑区块的物理位置属性的情况下为每个区块分配船只,制定第二阶段模型以指定所有区块的物理位置。随后,提出了一种基于遗传算法的求解框架,用于求解第一阶段模型,并使用CPLEX(商用求解器)求解第二阶段模型。最后,进行了数值实验和情景分析,以验证所提出模型的有效性和所提出解决方案方法的效率。码模板;

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