基于短转弯加速策略的地铁走廊需求驱动调度

Tommaso Schettini, O. Jabali, F. Malucelli
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引用次数: 3

摘要

地铁线路的有效管理是公共交通运营商关注的主要问题。传统上,地铁线路是通过定期时刻表运行的,也就是说,列车在所有车站之间有固定的进度表。本文以双向地铁走廊为例,提出了需求驱动的地铁调度策略,并详细阐述了精确求解方法。这样做,我们避免强加任何预定的时间表结构,而是单独控制列车,以最好地满足乘客的需求。我们认为列车可能会短转弯,即列车不需要从一个终点站到另一个终点站,而是可能在到达终点站之前倒车。针对需求驱动的地铁短转弯双向通道调度问题,提出了一个混合整数线性规划公式。此外,我们开发了一种使用切割生成的高效精确算法,用于具有指数数量约束的替代公式,并推导了两类有效不等式。我们评估了提出的公式和算法,考虑了7种可能的切割生成策略,这些策略来自人工生成的线的许多测试实例和来自现实世界线的两个测试平台。通过计算实验,我们证明了所开发算法的有效性以及所提出策略在乘客等待时间方面的附加价值。
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Demand-Driven Timetabling for a Metro Corridor Using a Short-Turning Acceleration Strategy
The efficient management of metro lines is a major concern for public transport operators. Traditionally, metro lines are operated through regular timetables, that is, timetables where trains have a constant headway between all stations. In this paper, we propose a demand-driven metro timetabling strategy and elaborate exact solution methods for the case of a two-directional metro corridor. In doing so, we avoid imposing any predetermined structure to the timetable, and instead control the trains individually to best match passenger demand. We consider that trains may short turn, that is, trains that are not required to serve the line from terminal to terminal, but instead may reverse direction before reaching the terminal. We present a mixed integer linear programming formulation for the demand-driven timetabling problem of a two-directional metro corridor with short turning. Furthermore, we develop an efficient exact algorithm using cut generation for an alternative formulation with an exponential number of constraints, and derive two classes of valid inequalities. We evaluate the proposed formulation and algorithm considering seven possible cut generation strategies on a number of test instances from artificially generated lines and on two test beds derived from real-world lines. Through the computational experiments, we demonstrate the effectiveness of the developed algorithm and the added value of the proposed strategy in terms of passengers’ waiting time.
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