Evolutionary methodology for aseismic decision support
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One of the fundamental long-term goals of earthquake engineering research is to enable the development of disaster-resilient communities. The innovative engineering technologies and associated design guidelines are certainly beneficial. However, decisions about enhancing seismic safety in critical facilities requires more than engineering choices about which technology or what guideline is most appropriate. Such decisions are made in the context of organizational goals and strategy, financial capacity, choices about how safe is safe enough, and driving forces in the social, economic, and political environment. In this dissertation, a complex adaptive evolutionary framework is developed, which integrates artificial earthquake models, state of the art understanding of structural response, alternative means for mitigating the risk, normative organizational behavioral models and economic loss estimation models. Starting from a probabilistic seismic model, different retrofitting alternatives are evaluated. Genetic algorithms are used to find the most robust optimized solutions considering the uncertainties of the seismic environment. The decision processes and criteria of healthcare organizations are investigated. Based upon this investigation, the system dynamic behavioral models of acute care hospitals are developed. Multidisciplinary approaches are used to address the complex socio-technical problems in the model. Parameter estimation and sensitivity analysis have been done to improve the robustness of the model. Then in a certain period of life cycle, different policy scenarios and earthquake scenarios are input into this model. The loss estimation model is also introduced to evaluate the economic loss of the hospital organization due to seismic events. The cost-benefit effects and some other socio-economical impacts are analyzed. Again genetic algorithms are applied to pick the most robust policy sets. A case study for a west coast demonstration hospital shows the proposed evolutionary decision support methodology has the potential to help decision makers in healthcare organizations make more informed choices about mitigating the likely consequences of earthquakes.