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A Decision Model for Berth Allocation Under Uncertainty Considering Service Level Using an Adaptive Differential Evolution Algorithm

机译:服务水平不确定的泊位分配决策模型的自适应差分进化算法

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This paper focuses on the berth allocation problem, which is to determine where and when the vessels to be loaded and unloaded at a terminal within a given planning horizon, with consideration of uncertain factors, mainly including the arrival and operation time of the calling vessels. Based on the concept of service level which is commonly used in the inventory system, a decision model is constructed to minimize the cost of baseline schedule, which includes delay cost and nonoptimal berthing location cost. According to the specific characteristics of the model, the upper and lower bounds are found. And due to the NP-hardness of the constructed model, an adaptive differential evolution is employed to solve the problem. Finally, extensive numerical experiments are conducted to test the performance of the proposed models and solution approaches.
机译:本文着重于泊位分配问题,即在考虑不确定因素的情况下,确定给定计划范围内在码头上何处装货和何时卸货,主要包括停靠船只的到达和操作时间。基于库存系统中常用的服务水平概念,构建决策模型以最大程度地减少基线计划的成本,其中包括延迟成本和非最佳停泊位置成本。根据模型的特定特征,找到上下限。并且由于构造模型的NP硬度,采用自适应差分进化来解决该问题。最后,进行了广泛的数值实验,以测试所提出的模型和求解方法的性能。

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