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Hyperpath-based vehicle routing and scheduling method in time-varying networks for airport shuttle service

机译:用于机场班车服务的时变网络中基于超路径的车辆路由和调度方法

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摘要

It is very significant for a reasonable vehicle routing and scheduling in city airport shuttle service to decrease operational costs and increase passenger satisfaction. Most of the existing reports for such problems assumed that the travel time was invariable. However, the ever-increasing traffic congestion often makes it variable. In this study, considering the time-varying networks, a vehicle routing and scheduling method is proposed, where the time-varying feature enables the traveler to select a direction among all the Pareto-optimal paths at each node in response to the knowledge of the time window demands. Such Pareto-optimal paths are referred to hyperpaths herein. To obtain the hyperpaths, an exact algorithm is designed in this study for addressing the bi-criteria shortest paths problem, where the travel time comes to be discontinuous time-varying. Given the techniques that generate all Pareto-optimal solutions exhibiting exponential worst-case computational complexity, embedded in the exact algorithm, a computationally efficient bound strategy is reported on the basis of passenger locations, pickup time windows and arrival time windows. As such, the vehicle routing and scheduling problem viewed as an arc selection model can be solved by a proposed heuristic algorithm combined with a dynamic programming method. A series of experiments by using the practical pickup data indicate that the proposed methods can obtain cost-saving schedules under the condition of time-varying travel times.
机译:在城市机场班车服务中合理安排车辆路线和安排时间以降低运营成本并提高乘客满意度非常重要。现有的有关此类问题的大多数报告都假设行进时间是不变的。但是,不断增加的交通拥堵常常使它变得可变。在这项研究中,考虑到时变网络,提出了一种车辆选路和调度方法,其中时变特征使旅行者能够根据每个节点的知识在每个节点的所有帕累托最优路径中选择一个方向。时间窗口需求。这样的帕累托最优路径在本文中称为超路径。为了获得超路径,在本研究中设计了一种精确的算法来解决双准则最短路径问题,其中旅行时间变为不连续的时变。在精确算法中嵌入给定生成所有表现出指数最坏情况计算复杂性的帕累托最优解的技术后,根据乘客位置,接机时间窗和到达时间窗,报告了一种计算有效的边界策略。这样,可以通过提出的启发式算法与动态规划方法相结合来解决被视为弧选择模型的车辆选路和调度问题。利用实际的皮卡数据进行的一系列实验表明,所提出的方法可以在旅行时间随时间变化的情况下获得节省成本的时间表。

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