A Dynamic Berth Allocation Model Based on Stochastic Consideration
A Dynamic Berth Allocation Model Based on Stochastic Consideration
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DOI：
10.1109/wcica.2006.1714503
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发表时间：
2006-10
期刊：
影响因子：
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通讯作者：
Pengfei Zhou;Haigui Kang;Li Lin
中科院分区：
文献类型：
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作者：
Pengfei Zhou;Haigui Kang;Li Lin
在码头泊位分配中，岸桥装卸时间等输入是随机参数。为了模拟真实的决策过程，建立了动态随机泊位分配模型。为了减少船舶的总等待时间，该模型忽略了“先到先得”的规则，并以概率的方式处理了船舶超过可接受等待时间的相应恶果。由于求解该模型所需的CPU时间超过多项式时间，提出了一种基于遗传算法的遗传算法。考虑到近似最优解的性质，讨论了算法的基本搜索空间的缩减。实验结果表明，该模型能够在真实的随机环境中为停靠集装箱船舶高效、动态地分配泊位，算法在允许的CPU时间内取得了令人满意的结果
When allocating berth in terminal, inputs such as quay-crane handling time are stochastic parameters. A dynamic stochastic berth allocation model was proposed to simulate the real decision-making. To decrease total ship waiting time, the model ignores the "first comes first served" rule, and copes with the corresponding evil consequence of exceeding acceptable waiting time of ships with probability. Since consuming CPU time for solving the model is beyond polynomial time, a heuristics algorithm was developed based on genetic algorithm. And a reduced basic search space for the algorithm was discussed by considering approximate optimal solution properties. The experiment results reveal that the model is capable of allocating berths efficiently and dynamically to calling containerships in real stochastic environments and the algorithm can lead to satisfactory results in allowable CPU time