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Combined quay crane assignment and quay crane scheduling with crane inter-vessel movement and non-interference constraints

机译:结合码头起重机移动和无干扰约束的组合式码头起重机分配和码头起重机调度

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Integrated models of the quay crane assignment problem (QCAP) and the quay crane scheduling problem (QCSP) exist. However, they have shortcomings in that some do not allow movement of quay cranes between vessels, others do not take into account precedence relationships between tasks, and yet others do not avoid interference between quay cranes. Here, an integrated and comprehensive optimization model that combines the two distinct QCAP and QCSP problems which deals with the issues raised is put forward.The model is of the mixed-integer programming type with the objective being to minimize the difference between tardiness cost and earliness income based on finishing time and requested departure time for a vessel. Because of the extent of the model and the potential for even small problems to lead to large instances, exact methods can be prohibitive in computational time. For this reason an adapted genetic algorithm (GA) is implemented to cope with this computational burden. Experimental results obtained with branch-and-cut as implemented in CPLEX and GA for small to large-scale problem instances are presented. The paper also includes a review of the relevant literature.
机译:存在码头起重机分配问题(QCAP)和码头起重机调度问题(QCSP)的集成模型。但是,它们的缺点是,有些不允许在起重机之间移动码头起重机,有些则没有考虑任务之间的优先关系,而另一些则不能避免码头起重机之间的干扰。在此,提出了一个综合全面的优化模型,该模型结合了两个独特的QCAP和QCSP问题,可以解决所提出的问题。该模型是混合整数编程类型的,目的是最大程度地减少拖延成本和早期性根据完成时间和请求的出发时间计算的收入。由于模型的范围以及即使很小的问题也可能导致大实例的可能性,因此精确的方法可能会在计算时间上令人望而却步。因此,实施了适应性遗传算法(GA)来应对这种计算负担。给出了在CPLEX和GA中实现的小规模到大规模问题实例的分支切割获得的实验结果。本文还包括对相关文献的回顾。

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