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为减少集装箱在装船时的翻倒箱次数,针对出口集装箱在堆场贝内箱位分配问题进行研究。以往的研究假设集装箱的重量概率分布在整个集港过程中保持不变,由于该假设与实际情况不相符合,该文考虑了集装箱的重量概率分布随堆存状况可变的情形,使其更加符合实际情况,并构建了一个带约束的随机动态规划模型。在求解算法方面,小规模算例可直接通过动态规划模型求得最优解。针对大规模算例,提出了两阶段的启发式算法:第一阶段基于邻域搜索的启发式算法,设计出各重量组的集装箱在不同堆垛形态下的优先堆放次序;第二阶段设计了基于翻滚策略的箱位堆放局部优化算法。数值计算结果表明:适用于小规模算例的动态规划算法和适用于大规模算例的两阶段启发式算法都能显著改善解质量,减少翻倒箱次数。
In order to reduce the number of overturned containers when the container is loaded, a study was conducted on the distribution of the export containers at the storage location in the bay. Previous researches assume that the weight probability distribution of containers remains the same throughout the process of porting. Because this assumption is not consistent with the actual situation, this paper considers the situation that the weight probability distribution of containers varies with the storage conditions, It meets the actual situation and constructs a stochastic dynamic programming model with constraints. In solving algorithms, small-scale examples can directly obtain the optimal solution through the dynamic programming model. In this paper, a two-stage heuristic algorithm is proposed for large-scale case studies. In the first stage, heuristic algorithm based on neighborhood search is used to design the priority stacking order of containers in different stacks for each weight group. In the second stage, Local Optimization Algorithm of Box Stacking Based on Rolling Strategy. The numerical results show that both the dynamic programming algorithm suitable for small-scale studies and the two-stage heuristic algorithm applicable to large-scale numerical examples can significantly improve the quality of solutions and reduce the number of rollover boxes.