Integrating the Social Vulnerability of Host Communities and the Objective Functions of Associated Stakeholders during Disaster Recovery Processes using Agent-Based Modeling

Disaster recovery requires the participation of the stakeholders to repair the impacted community. Nevertheless, disaster recovery remains understudied within the context of emergency management. Various models have been developed to address disaster recovery. However, those models neither considered the stakeholders\u27 needs and preferences, nor the vulnerability of the host community. This paper presents a decision-making framework for disaster recovery that uses a bottom-up approach to capture the needs of the impacted residents and decreases the social vulnerability of host communities. The authors developed the following research methodology: (1) use a well-established community specific social vulnerability assessment tool to evaluate the society vulnerability; (2) model the multisector stakeholders through a root-to-grass technique that captures their objectives, strategies, and learning behaviors; (3) simulate the recovery progress of the impacted community using an agent-based simulation toolkit; and (4) interpret the results to provide the decision makers with optimal recovery strategies. The restorations efforts in the aftermath of hurricane Katrina in three coastal counties in Mississippi were used as the problem domain. Accordingly, the proposed model was implemented on a multiagent-based simulation toolkit with geographic information system (GIS) abilities. This research optimized the budget for the State Disaster Recovery Coordinator and the residents\u27 insurance plans choices. As such, this study provided better social vulnerability indices than the existing conditions currently found in the areas under investigation. Further, this research provided higher disaster recovery rates within the studied host communities. For future work, other vulnerability dimensions will be simultaneously integrated into the model to provide a more accurate depiction of sustainable disaster recovery processes