Multi-objective Optimization for Exploring the Effectiveness of Building Mitigation Towards Reducing Urban Conflagrations

The impact of wildfires on communities has been devastating in recent years. With the advent of climate change, the frequency and intensity of wildfire events will rise. The increasing population in the wildland–urban interface (WUI) has further amplified the exposure of communities to such events. In this study, we demonstrate the application of a graph-based framework for modeling fire propagation through a heterogeneous fuel and evaluating the impact of different passive fire intervention strategies on a community. We utilize an optimization framework to determine the most effective intervention strategy based on the priority given to either performance, cost, or both. The performance is measured by minimizing the mean vulnerability of the community after applying intervention strategies to individual buildings, and the cost is calculated as the normalized cost of implementing a particular strategy for the entire community. Four distinct communities across the United States are selected to demonstrate the applicability of the proposed fire intervention framework. The results show that optimal intervention strategies depend on the extent to which performance and cost are prioritized. Furthermore, the optimal strategies are also affected by the characteristics of a community, as variations in the optimal strategy are observed for the four communities considered.