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Research on Marine Loading Planning Problem based on Iterative Hierarchical Optimization Method

机译:基于迭代递阶优化方法的船舶装载计划问题研究

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This paper studies on the marine loading planning problem. The objective of this problem is to determine the required vessels and the berth allocation plan with consideration on minimizing the amount of used vessels and overall loading time. Firstly, this problem is modeled as a multi-objective combinational optimization problem. It is transformed into an integer programming problem by using a weighting method. Secondly, this paper proposes an iterative hierarchical optimization method to search the near optimal solution for the combinatorial optimization problem. The optimization of the vessels selection plan and the allocation of vessels to berths are separately resolved. To improve the utilization of each vessel and reduce the overall amount of required vessels, the linear integer programming method is used. The grouped genetic algorithm is applied to find the optimal berth allocation plan. Finally, we demonstrate our algorithm in a large scale marine loading scenario. The experimental results show that our method could solve the complex marine loading planning problem effectively.
机译:本文研究了海上装载计划问题。该问题的目的是在考虑最小化使用的船只数量和总装载时间的情况下确定所需的船只和泊位分配计划。首先,将此问题建模为多目标组合优化问题。通过使用加权方法将其转换为整数规划问题。其次,本文提出了一种迭代层次优化方法,以寻找组合优化问题的近似最优解。船只选择计划的优化和泊位的船只分配分别解决。为了提高每个容器的利用率并减少所需容器的总量,使用了线性整数编程方法。应用分组遗传算法找到最优泊位分配方案。最后,我们在大规模的海上装载场景中演示了我们的算法。实验结果表明,该方法可以有效地解决复杂的海上装载计划问题。

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