Multi-objective optimization of mitigation strategies for buildings subject to multiple hazards - Gupta, Himadri Sen; Adluri, Tarun; Sanderson, Dylan; González, Andrés D.; Nicholson, Charles D.; Cox, Daniel (International journal of disaster risk reduction, 2024)
Natural hazards can have a devastating impact on communities, leading to social and economic losses. These effects are particularly severe in multi-hazard contexts, where multiple disruptive events occur simultaneously or consecutively (such as earthquakes and tsunamis). To reduce the impact of such events, it is critical to enhance community resilience and make it more capable of withstanding and recovering from diverse types of damage. In this study, we propose a multi-objective optimization model to determine optimal retrofitting strategies to enhance community resilience under multiple hazards. We used the proposed model to analyze the impact of earthquake and tsunami hazards on the community of Seaside, Oregon. It assesses the effectiveness of different retrofitting strategies at the individual building level, considering the conflicting objectives of reducing overall economic loss, population dislocation, and building repair times. Our results demonstrate that retrofitting buildings to achieve higher seismic codes can significantly reduce the impact of natural hazards on structural damage, population dislocation, and building repair times. Additionally, our findings reveal the importance of considering geographical location and mitigation measures when optimizing retrofitting strategies. By considering budget constraints and community resilience metrics, our model identifies the most effective retrofitting strategies for individual buildings of Seaside, which ultimately helps the community make informed decisions about investments to reduce the impact of natural hazards. Overall, this study provides valuable insights into the importance of enhancing community resilience in multi-hazard contexts and showcases the use of a multi-objective optimization model to identify optimal retrofitting strategies.