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An intelligent optimization approach for storage space allocation at seaports: A case study

机译:港口仓储空间分配的智能优化方法:案例研究

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Storage space allocation problem at container terminals is NP-hard combinatorial optimization problem. This paper proposes a new approach based on genetic algorithm to optimize the solution for storage space allocation problem in container terminal at seaports. A new mathematical model is formulated to avoid bottlenecks in container yard operations, and to minimize vessels service time in port. Also, a simulation model using discrete event simulation tool is conducted to optimize the solution for storage space allocation problem is presented in this study. The proposed approach is applied on a real case study data of container terminal at Damietta port. The computational results show the effectiveness of the proposed approach.
机译:集装箱码头的存储空间分配问题是NP难组合优化问题。提出了一种基于遗传算法的海港集装箱码头仓储空间分配问题优化方案。制定了新的数学模型,以避免集装箱堆场运营中的瓶颈,并最大程度地减少船舶在港口的服务时间。此外,本研究还提出了使用离散事件仿真工具的仿真模型,以优化存储空间分配问题的解决方案。该方法被应用于达米埃塔港集装箱码头的真实案例研究数据。计算结果表明了该方法的有效性。

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