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Natural disasters leave the impacted regions with financial burdens both on the individual and governmental levels. Thus, the goal of the associated stakeholders is to maximize the host communities' welfare through minimizing their post-disaster financial burdens. Accordingly, this paper attempts to find a post-disaster insurance plans equilibrium so as to mitigate the financial impacts associated with the natural disasters. Utilizing an evolutionary game theory approach, the equilibrium is investigated between three different players including: resident families purchasing insurance plans; insurance companies offering different insurance plans; and the government agency that implements post disaster relief financial plans. The authors determined a set of decision actions as well as utility functions for the aforementioned stakeholders. Moreover, the authors created a hypothetical sample of 1,000 heterogeneous income level resident families, three insurance companies offering three unique and different insurance plans per company and two post disaster financial relief plans to be utilized by the government agency. The proposed model was implemented on NetBeans IDE 7.4 platform using JAVA programming language on the hypothetical case study simulating resident family evolutionary learning process in reaching an equilibrium. The results indicate that: (1) resident families tend to prefer insurance plans with the least premium value and coverage; (2) insurance plans with the most comprehensive coverage received the least demand; and (3) the evolutionary stable strategy path oscillates between chosen plans and insurers over time as a result of the stochastic and dynamics nature of the factors associated with disaster management. Currently, the authors are working to develop the model further to better account for simultaneous actions by all stakeholders (not only resident families), population growth and changes in financial and income standards. Ultimately, this evolutionary game theory model will be tested on real post natural disasters data representing physical damages in coastal Mississippi Counties post Katrina, so as to determine the significant increase in the host community welfare.

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The goal of sustainable disaster recovery is to regain the built environment's functionality while decreasing the vulnerability of the society to future perturbations. This requires a new generation of decision support tools that integrate the host community's vulnerability assessment while taking into account the stakeholders' interactions, needs, and preferences. The available disaster recovery research focuses on the optimization and reconstruction of isolated projects rather than taking into account the host community's overall vulnerability and welfare. Moreover, the available research did not simultaneously take into account the stakeholders' preferences and needs. To this effect, this paper presents an agent-based model that integrates an environmental vulnerability indicator to better guide the decision-making process of the associated stakeholders. Such an approach will aid urban planners to redevelop societies into a more resilient status. This paper implements a five-step research methodology that comprises: (1) utilizing a comprehensive assessment tool to measure community's environmental vulnerability; (2) developing the objective functions and learning algorithms of the different associated stakeholders; (3) modeling the different attributes and potential strategies interrelated with the different stakeholders; (4) creating an interdependent multiagent-based model that concurrently simulates the aforementioned information; and finally, (5) interpreting and analyzing the results generated from the developed model. The proposed model adopts post-Katrina recovery as the application domain, and thus was tested using the housing and infrastructure recovery projects in three coastal counties in Mississippi. To this end, the model was able to optimize and adapt to the changing vulnerability conditions of the host community. The model also provided an optimal utilization of the infrastructure to decrease the built environment vulnerability to future natural hazards. This provided better outcomes in relation to environmental vulnerability and stakeholders' individual utility functions when compared to the actual implemented disaster recovery plans. For future work, this research will target the integration of other vulnerability indicators. This will lead to more effective representation of the host communities' complex systems, and ultimately achieving a holistic sustainable disaster recovery.

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