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首页> 外文期刊>European Journal of Operational Research >Simulation-based Selectee Lane queueing design for passenger checkpoint screening
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Simulation-based Selectee Lane queueing design for passenger checkpoint screening

机译:基于仿真的Selectee Lane排队设计,用于乘客检查站筛选

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There are two kinds of passenger checkpoint screening lanes in a typical US airport: a Normal Lane and a Selectee Lane that has enhanced scrutiny. The Selectee Lane is not effectively utilized in some airports due to the small amount of passengers selected to go through it. In this paper, we propose a simulation-based Selectee Lane queueing design framework to study how to effectively utilize the Selectee Lane resource. We assume that passengers are classified into several risk classes via some passenger prescreening system. We consider how to assign passengers from different risk classes to the Selectee Lane based on how many passengers are already in the Selectee Lane. The main objective is to maximize the screening system's probability of true alarm. We first discuss a steady-state model, formulate it as a nonlinear binary integer program, and propose a rule-based heuristic. Then, a simulation framework is constructed and a neighborhood search procedure is proposed to generate possible solutions based on the heuristic solution of the steady-state model. Using the passenger arrival patterns from a medium-size airport, we conduct a detailed case study. We observe that the heuristic solution from the steady-state model results in more than 4% relative increase in probability of true alarm with respect to the current practice. Moreover, starting from the heuristic solution, we obtain even better solutions in terms of both probability of true alarm and expected time in system via a neighborhood search procedure.
机译:在典型的美国机场中,有两种类型的旅客检查站检查车道:普通车道和经过严格审查的Select选车道。在某些机场,由于选择通过的旅客数量少,Selectee Lane无法得到有效利用。在本文中,我们提出了一个基于仿真的Selectee Lane排队设计框架,以研究如何有效利用Selectee Lane资源。我们假设通过某种旅客预检系统将旅客分为几类风险。我们考虑如何根据已在Selectee Lane中有多少乘客将不同风险类别的乘客分配到Selectee Lane。主要目的是最大程度地提高筛选系统的真实警报概率。我们首先讨论稳态模型,将其公式化为非线性二进制整数程序,然后提出基于规则的启发式算法。然后,构建了一个仿真框架,并提出了一种邻域搜索程序,以基于稳态模型的启发式解生成可能的解。我们使用中型机场的旅客到达方式,进行了详细的案例研究。我们观察到,相对于当前实践,稳态模型的启发式解决方案导致真实警报概率相对增加了4%以上。此外,从启发式解决方案开始,我们通过邻域搜索过程在系统中发生真正警报的可能性和预期时间方面获得了甚至更好的解决方案。

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