Data-driven modeling using system dynamics simulation to provide relief in earthquake based on different scenarios.

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.