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Scenario-Based Allocation of Emergency Resources in Metro Emergencies: A Model Development and a Case Study of Nanjing Metro

机译:基于场景的地铁紧急情况下的应急资源分配:南京地铁的模型开发和案例研究

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摘要

As metro systems are becoming more and more widely used, all kinds of emergencies happen from time to time. A series of cases indicate that inefficient emergency response is a dominating cause of tremendous casualties and losses. The fast and valid allocation of emergency resources after the occurrence of metro emergencies has become a key point in improving the sustainability of metro operations. However, few studies have attempted to determine the allocation of emergency resources in metro emergencies. In this study, considering the unpredictability of different emergency scenarios in the metro system, the scenario-response mode was applied in the resource allocation decision. In this mode, a metro emergency scenario framework was first constructed through the identification of metro emergency elements. Next, a multi-objective model was established for the allocation of emergency resources in the metro emergency rescue process using a scenario-based analysis. The model aims to minimize both the penalty costs due to delays and the sum of allocation costs. The particle swarm optimization algorithm was adopted to solve the model. Eventually, a fire accident scenario at Nanjing Metro was applied to verify the feasibility and validity of the presented model and algorithm. The research results not only enrich and improve metro emergency management theoretically, but also enhance metro emergency rescue ability in practice.
机译:由于地铁系统越来越广泛地使用,因此各种紧急情况发生。一系列案例表明,低效的应急响应是巨大伤亡和损失的主导原因。在地铁紧急情况发生后,紧急资源的快速有效分配已成为提高地铁业务可持续性的关键点。然而,很少有研究试图确定地铁紧急情况下的紧急资源分配。在本研究中,考虑到地铁系统中不同紧急情况的不可预测性,在资源分配决策中应用了场景响应模式。在此模式下,首先通过确定地铁应急元素来构建地铁紧急情况框架。接下来,使用基于场景的分析建立了用于在地铁应急救援过程中的紧急资源分配的多目标模型。该模型旨在最大限度地减少由于延误和分配成本总和的罚金成本。采用粒子群优化算法来解决模型。最终,应用了南京地铁的火灾事故情景,以验证所提出的模型和算法的可行性和有效性。研究结果不仅在理论上丰富和改善了地铁应急管理,而且在实践中提高了地铁应急救援能力。

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  • 作者

    Ying Lu; Shuqi Sun;

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  • 年度 2020
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  • 原文格式 PDF
  • 正文语种 eng
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