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Adjustment of Train Interval Time Based on Dynamic Programming Algorithm

机译:基于动态规划算法的列车间隔时间调整

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The optimization of the tracking interval time is the main research field for improving the railway transportation capacity. At present, tracking interval time of high-speed railway has basically reached the 5-minute or 3-minute in China. To further shorten the train tracking interval time, this paper selects the line gradient parameter as the optimization parameter to establish the multi-stage decision model based on dynamic programming, and uses COADP algorithm (an improved algorithm based on dynamic programming) to optimize the braking distance of the train. Basing on Bellman's theorem, the COADP algorithm optimizes the line gradient reduction program and solves the phase variable optimal solution, state variable optimal solution, optimal decision sequence, optimal index function and optimal value function By obtaining the optimal objective function of the EMU braking distance, the algorithm optimizes the tracking interval time of EMU and enhances the high-speed railway transportation capacity.
机译:跟踪间隔时间的优化是提高铁路运输能力的主要研究领域。目前,中国高速铁路的跟踪间隔时间已基本达到5分钟或3分钟。为了进一步缩短列车的跟踪间隔时间,本文选择直线梯度参数作为优化参数,建立基于动态规划的多阶段决策模型,并采用COADP算法(基于动态规划的改进算法)对制动进行优化。火车的距离。根据Bellman定理,COADP算法优化了线梯度减小程序,并通过获得EMU制动距离的最佳目标函数来求解相位变量最优解,状态变量最优解,最优决策序列,最优指标函数和最优值函数,该算法优化了动车组的跟踪间隔时间,提高了高速铁路的运输能力。

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