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Abstract Coastal communities are increasingly vulnerable to hurricanes, which cause billions of dollars in damage annually through wind, storm surge, and flooding. Mitigation efforts are essential to reduce these impacts but face significant challenges, including uncertainties in hazard prediction, damage estimation, and recovery costs. Resource constraints and the disproportionate burden borne by socioeconomically vulnerable groups further complicate retrofitting strategies. This study presents a probabilistic methodology to assess and mitigate hurricane risks by integrating hazard analysis, building fragility, and economic loss assessment. The methodology prioritizes retrofitting strategies using a risk‐informed, equity‐focused approach. Multi‐objective optimization balances cost‐effectiveness and risk reduction while promoting fair resource allocation among socioeconomic groups. The novelty of this study lies in its direct integration of equity as an objective in resource allocation through multi‐objective optimization, its comprehensive consideration of multi‐hazard risks, its inclusion of both direct and indirect losses in cost assessments, and its use of probabilistic hazard analysis to incorporate varying time horizons. A case study of the Galveston testbed demonstrates the methodology's potential to minimize damage and foster equitable resilience. Analysis of budget scenarios and trade‐offs between cost and equity underscores the importance of comprehensive loss assessments and equity considerations in mitigation and resilience planning. Key findings highlight the varied effectiveness of retrofitting strategies across different budgets and time horizons, the necessity of addressing both direct and indirect losses, and the importance of multi‐hazard considerations for accurate risk assessments. Multi‐objective optimization underscores that equitable solutions are achievable even under constrained budgets. Beyond a certain point, achieving equity does not necessarily increase expected losses, demonstrating that more equitable solutions can be implemented without compromising overall cost‐effectiveness. 

Every year, floods cause substantial economic losses worldwide with devastating impacts on buildings and physical infrastructures throughout communities. Techniques are available to mitigate flood damage and subsequent losses, but the ability to weigh such strategies with respect to their benefits from a community resilience perspective is limited in the literature. Investing in flood mitigation is critical for communities to protect the physical and socioeconomic systems that depend on them. While there are multiple mitigation options to implement at the building level, this paper focuses on determining the optimal flood mitigation strategy for buildings to minimize flood losses within a community. In this research, a mixed integer linear programming model is proposed for studying the effects and trade-offs associated with pre-event short-term and long-term mitigation strategies to minimize the expected economic losses associated with floods. The capabilities of the proposed model are illustrated for Lumberton, North Carolina (NC), a small, socially diverse inland community on the Lumber River. The mathematically optimal building-level flood mitigation plan is provided based on the available budget, which can significantly minimize the total expected direct economic loss of the community. The results reveal important correlations among investment quantity, building-level short- and long-term mitigation measures, flood depths of various locations, and buildings’ structure. Additionally, this study shows the trade-offs between short- and long-term mitigation measures based on available budget by providing decision support to building owners regarding mitigation measures for their buildings.