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Timetable Mapping Model and Dynamic Programming Approach for High-speed Railway Rescheduling

机译:高速铁路时刻表时刻表映射模型及动态规划方法

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In railway systems, rescheduling trains in case of delays or disruptions occur is a critical and challenging task to remain the punctuality of railway traffics. Solving the railway traffic rescheduling problem is complex, computation-intensive and time-consuming from practical and computational perspectives. The problem has typically a very large search space, making it time-consuming to solve even for state-of-the-art optimization solvers. In this paper, a dynamic programming (DP) approach is used to address the issues of high computation costs in rescheduling railways traffics under various delays, in order to map the arrival and departure time of the train to the state of DP, we develop a timetable mapping model for the real-time train rescheduling (TTR) problem. Each section is modeled as a stage in the action space and the state of each stage is represented by the departure sequence of all the trains at the station for timetable mapping. And we further obtain the state transfer equation and construct the Bellman equation with the goal of minimizing the total delay time and use the Bellman equation inverse to derive the solution. Finally, numerical experiments of TTR are conducted. The advantage of the proposed DP is illustrated from the perspective of the strategy compared with the widely used First-Come-First Serve (FCFS) and the First Schedule-First-Serve (FSFS). It shows that the proposed DP can effectively solve the TTR problems, especially for primary delay problems.
机译:在铁路系统中,要在出现延误或干扰的情况下重新安排火车的时间,对于保持铁路运输的准时性是一项至关重要且具有挑战性的任务。从实用和计算的角度来看,解决铁路交通调度问题是复杂的,计算量大且耗时的。该问题通常具有很大的搜索空间,因此即使对于最先进的优化求解器也要花费大量时间来解决。在本文中,动态规划(DP)方法用于解决在各种延误下重新安排铁路交通量时高计算成本的问题,为了将火车的到达和出发时间映射到DP状态,我们开发了一种实时列车重新调度(TTR)问题的时间表映射模型。每个部分都被建模为动作空间中的一个阶段,并且每个阶段的状态都由车站中所有列车的发车顺序表示,以进行时间表映射。然后,我们进一步获得状态转移方程,并以最小化总延迟时间为目标构造Bellman方程,并使用Bellman方程逆来求解。最后,进行了TTR的数值实验。与广泛使用的先来先服务(FCFS)和先调度先服务(FSFS)相比,从策略的角度说明了提议的DP的优势。结果表明,所提出的DP可以有效地解决TTR问题,特别是对于主要的时延问题。

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