Emergency responders are typically notified immediately after a major earthquake strikes. However, a time delay, called the travel time, is usually experienced between the notification and the arrival of the responders on the scene. The reparative work necessary after the responders arrive takes an additional amount of time, called the response time, depending on the nature of the damage and the volume of resources available. In a smart city, the restoration time, which is the sum of the travel and response times, should be minimized. A new discrete-event-based simulation (DEBS) model is presented in this paper to estimate the restoration time needed to bring the situation under control after notifying the response center. The DEBS model not only relaxes restrictive assumptions on travel time made by the Markov chain models from the existing literature, but it can also quantify the impact of resource volumes on restoration times. Additionally, the DEBS model is very useful for training purposes. The DEBS model was employed on a case study from the state of Missouri (U.S.). The experiments demonstrate that numerical results with the model take a short amount of computational time and that it can be implemented on a real-time basis in a smart-city infrastructure.

中文翻译：

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基于离散事件的智慧城市震后恢复性能评估仿真模型

紧急救援人员通常会在发生大地震后立即收到通知。然而，在通知和响应者到达现场之间通常会经历一个时间延迟，称为旅行时间。响应者到达后所需的修复工作需要额外的时间，称为响应时间，具体取决于损坏的性质和可用资源的数量。在智慧城市中，恢复时间，即出行时间和响应时间的总和，应该最小化。本文提出了一种新的基于离散事件的仿真 (DEBS) 模型，以估计在通知响应中心后使情况得到控制所需的恢复时间。DEBS 模型不仅放宽了现有文献中马尔可夫链模型对旅行时间的限制性假设，而且还可以量化资源量对恢复时间的影响。此外，DEBS 模型对于训练非常有用。DEBS 模型用于密苏里州（美国）的案例研究。实验表明，该模型的数值结果需要很短的计算时间，并且可以在智能城市基础设施中实时实施。