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Synchronizing transportation of people with reduced mobility through airport terminals

机译:通过机场终端同步流动性降低的人员

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Navigating through an airport is easy enough for most passengers, but when you are reduced in mobility it is a different story. In this paper we look at an airport at which between 300 and 500 Passengers with Reduced Mobility (PRMs) arrive daily, who need assistance from airport employees in their journey. We want to find a schedule for these employees to support as many PRMs as possible while ensuring a smooth journey with little waiting time. PRMs may not be left unsupervised, except in a lounge. Since the employees are only allowed to work within their own terminal, the tasks of the employees must be synchronized to enable a smooth hand-over of a PRM. Moreover, we want to find a robust schedule to be resistant against minor disturbances. Since we must be able to reschedule in case of a major disturbance, the maximum computation time of our algorithm is restricted to two minutes. This problem was first studied by Reinhardt et al., who present an insertion heuristic, where the order in which the PRMs are considered is modified through local search. We present a decomposition model in which we first determine feasible start times for the tasks describing the journeys of the passengers using Simulated Annealing, after which in each iteration we assign the tasks to the employees using a (heuristic) matching algorithm. Experimental results show that our algorithm is able to ensure smooth, robust connections, while supporting every passenger in the given deterministic instances, which originate from Reinhardt et al. Finally, we present a simulation study to test our approach in a dynamic environment. It turns out that it can easily deal with these disturbances in real time and come up with very good solutions. The code used in the simulation study is freely available at https://github.com/RvanTwist/uu-thesis-prm. (C) 2020 Elsevier Ltd. All rights reserved.
机译:通过机场驾驶对于大多数乘客来说都很容易,但是当你减少移动性时,它是一个不同的故事。在本文中,我们看一个机场,其中300到500名乘客减少了移动性(PRMS),每天需要从机场员工的旅程中获得帮助。我们希望找到这些员工尽可能多地支持尽可能多的PRMS的计划,同时确保等待时间的平稳旅程。除了休息室外,PRMS可能不会留下无人监督。由于员工只允许在自己的终端内工作,因此必须同步员工的任务以使PRM的平滑接收。此外,我们希望找到一个抗弱小扰动的强大进度。由于我们必须能够重新安排,以便在大扰动的情况下,我们算法的最大计算时间仅限于两分钟。首先由Reinhardt等人研究了这个问题,介绍了一个插入启发式,其中通过本地搜索修改了PRMS的顺序。我们介绍了一种分解模型,其中我们首先确定使用模拟退火描述乘客旅程的任务的可行的开始时间,之后在每次迭代中,我们使用(启发式)匹配算法将任务分配给员工。实验结果表明,我们的算法能够确保光滑,强大的连接,同时支持给定的确定性实例中的每个乘客,它来自Reinhardt等人。最后,我们提出了一种在动态环境中测试我们的方法。事实证明,它可以实时地轻松处理这些干扰,并提出非常好的解决方案。模拟研究中使用的代码在https://github.com/rvantwist/uu-thesis-prm上自由使用。 (c)2020 elestvier有限公司保留所有权利。

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