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基于提箱作业的动态决策特点,构建以分组提箱为核心的进口箱提箱动态优化数学模型;基于统计分布规律模拟外部集卡抵港的随机性,提出动态优先提箱概率的概念及计算方法,并以此为基础设计分支定界+启发式算法的双层算法对模型进行求解.通过一系列大规模实验并与诸如IH、OH、RDH、Max-Min等现有算法的比较显示了该动态优化算法在不确定环境下对进口箱提箱作业调度优化的有效性与鲁棒性.
Based on the dynamic decision-making features of suitcase operation, a mathematical model of dynamic optimization of import suitcase with packet suitcase as the core was constructed. Based on the statistical distribution law, the randomness of external card arrival was simulated and the concept and calculation method of dynamic priority suitcase probability This is a two-layer algorithm based on the basic design of branch and bound + heuristic algorithm to solve the model.Compared with the existing algorithms such as IH, OH, RDH and Max-Min through a series of large-scale experiments, the dynamic optimization algorithm The Efficiency and Robustness of Job Box Optimization in Import Suitcase in Uncertain Environment.