Dynamic railway junction rescheduling using population based ant colony optimisation
Dynamic railway junction rescheduling using population based ant colony optimisation
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DOI：
10.1109/ukci.2014.6930174
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发表时间：
2014-10
期刊：
影响因子：
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通讯作者：
Jayne Eaton;Shengxiang Yang
中科院分区：
文献类型：
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作者：
Jayne Eaton;Shengxiang Yang
扰动后的有效重调度是铁路行业关注的重要问题。极端的延误可能导致火车公司和不满意的客户面临巨额罚款。由于这是一个动态的问题，这个问题变得更加严重;当受到干扰的列车等待重新安排时，可能会有更多的故障列车到达。新列车可能具有与现有列车不同的优先级，因此重新调度问题是随时间变化的动态问题。本研究的目的是应用人口为基础的蚁群优化算法来解决这个动态的铁路枢纽重新调度问题，使用模拟器模拟在现实世界中的英国铁路网络的交界处。结果是有希望的：该算法表现良好，特别是当动态变化是一个高的幅度和频率。
Efficient rescheduling after a perturbation is an important concern of the railway industry. Extreme delays can result in large fines for the train company as well as dissatisfied customers. The problem is exacerbated by the fact that it is a dynamic one; more timetabled trains may be arriving as the perturbed trains are waiting to be rescheduled. The new trains may have different priorities to the existing trains and thus the rescheduling problem is a dynamic one that changes over time. The aim of this research is to apply a population-based ant colony optimisation algorithm to address this dynamic railway junction rescheduling problem using a simulator modelled on a real-world junction in the UK railway network. The results are promising: the algorithm performs well, particularly when the dynamic changes are of a high magnitude and frequency.