Abstract：
Effective relief reduces damages and protects people during natural disasters, such as earthquakes. This research proposes a data-driven model based on sustainability, taking into account the pre and post-crisis simultaneously. Real data was used to validate the model in various earthquake scenarios. The study addresses questions regarding the amount and allocation of relief goods during earthquakes. This research is carried out in two phases: simulation and modeling. The purpose of the simulation phase is to estimate the number of relief goods in different scenarios. Additionally, in the modeling phase, a data-based multi-objective model is presented, considering sustainability, to minimize the lack of relief goods, the number of untreated wounded, and supply chain costs. Using the dynamic simulation system, and after designing the structure of the earthquake effects on urban infrastructure, the actions and effects of the earthquake on vital arteries are investigated in different scenarios, and scenarios with a higher degree of risk are identified. The results showed that the highest and lowest demands for relief goods were related to the \"Mosha-day fault\" and \"North Tehran-night fault\" scenarios, respectively.
摘要：
有效的救济减少了自然灾害中的损失并保护了人们，比如地震。本研究提出了一种基于可持续性的数据驱动模型，同时考虑到危机前和危机后。实际数据用于在各种地震场景中验证模型。该研究解决了地震期间救灾物资的数量和分配问题。本研究分两个阶段进行：仿真和建模。模拟阶段的目的是估计不同情况下的救援物资数量。此外,在建模阶段，提出了一种基于数据的多目标模型，考虑到可持续性，尽量减少救援物资的缺乏，未经治疗的伤员人数，和供应链成本。使用动态仿真系统，在设计了地震对城市基础设施的影响结构之后，在不同的情况下研究了地震对重要动脉的作用和影响，并识别出风险程度较高的场景。结果显示,对救援物资的最高和最低需求与\"摩沙日断层\"和\"北德黑兰夜间断层\"情景有关,分别。
