Ant Colony Optimization Algorithm applied to train operation adjustment of Urban Transit
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摘要: 当城市轨道交通列车在行车过程中由于设备故障、乘客拥挤等情况发生晚点时，需要对列车时刻表进行调整，使之尽快恢复正点运行。本文以调整区段内总晚点时间最小为目标函数，提出了基于蚁群优化算法的列车调整模型，在Visual C++ 6.0编程环境下，以深圳地铁6号线为例，对模型的实用性进行了验证。Abstract: It is necessary to adjust the train timetable and let the train recovery on time as soon as possible when the train of Urban Transit in the process of operation is late due to equipment fault, passengers congestion, etc. Taking the minimum total delay time as the objective function, this article proposed a train adjustment model based on Ant Colony Optimization (ACO) Algorithm. Shenzhen Metro Line 6 was taken as an example to verify the practicality of the model under the Visual C++ 6.0 programming environment.
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