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Reliable shortest path problems in stochastic time-dependent networks

机译:随机时变网络中可靠的最短路径问题

摘要

This study investigates the time-dependent reliable shortest path problem (TD-RSPP), which is commonly encountered in congested urban road networks. Two variants of TD-RSPP are considered in this study. The first variant is to determine the earliest arrival time and associated reliable shortest path for a given departure time, referred to as the "forward" TD-RSPP. The second problem is to determine the latest departure time and associated reliable shortest path for a given preferred arrival time, referred as the "backward" TD-RSPP. It is shown in this article that TD-RSPP is not reversible. The backward TD-RSPP cannot be solved by the algorithms designed for the forward problem using the reverse search from destination to origin. In this study, two efficient solution algorithms are proposed to solve the forward and backward TD-RSPP exactly and the optimality of proposed algorithms is rigorously proved. The proposed solution algorithms have potential applications in both advanced traveler information systems and stochastic dynamic traffic assignment models.
机译:本研究调查了在拥挤的城市道路网络中经常遇到的时变可靠最短路径问题(TD-RSPP)。在这项研究中考虑了TD-RSPP的两个变体。第一种方案是确定给定出发时间的最早到达时间和相关的可靠最短路径,称为“前向” TD-RSPP。第二个问题是确定给定首选到达时间的最新出发时间和相关的可靠最短路径,称为“后退” TD-RSPP。本文显示TD-RSPP是不可逆的。使用从目的地到起点的反向搜索,为前向问题设计的算法无法解决后向TD-RSPP问题。本文研究了两种有效的求解算法,分别精确地解决了前向和后向TD-RSPP问题,并严格证明了所提算法的最优性。提出的解决方案算法在高级旅行者信息系统和随机动态交通分配模型中都有潜在的应用。

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