地铁系统故障情况下干预策略评估的随机方法

M. Botte, L. D’Acierno, B. Montella, A. Placido
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引用次数: 13

摘要

智能交通是新概念城市发展模式的关键因素,即所谓的“智慧城市”。我们专注于铁路和地铁运输,提出了一个多维约束优化模型,以进行敏感性分析,以评估在干扰运营情况下恢复解决方案的有效性。事实上,在发生干扰或中断后,必须实施适当的干预策略,以便尽快解决问题并重新建立正常的日常服务条件。本文的具体目标是改进传统的确定性框架,在列车性能和延误上引入随机干扰,以便尽可能接近现实地模拟操作,并使特设目标函数最小化。在那不勒斯(意大利)的一条实际地铁线路上进行了应用,显示了所提出方法的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A stochastic approach for assessing intervention strategies in the case of metro system failures
Smart mobility is a key factor in the new conceptual urban development model, the so-called "smart city". We focus on rail and metro transport, proposing a multidimensional constrained optimisation model to carry out a sensitivity analysis for evaluating the effectiveness of recovery solutions in the case of disturbed operations. Indeed, after the occurrence of a disturbance or disruption, appropriate intervention strategies have to be implemented in order to address the problem and re-establish ordinary daily service conditions as rapidly as possible. The paper specifically aims to improve the traditional deterministic framework, introducing a stochastic disturbance on train performances and delays, in order to simulate operations as closely as possible to reality, with an ad-hoc objective function to be minimised. An application on a real metro line in Naples (Italy) is provided, showing the benefits of the proposed approach.
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