Formulation of a parametric systems design framework for disaster response planning

Systems design framework;Community resilience;Disaster planning;Disaster recovery planning;Parametric systems;Humanitarian logistics

Mma, Stephanie Weiya ; Aerospace Engineering

University:Georgia Institute of Technology

Department:Aerospace Engineering

关键词: Systems design framework;    Community resilience;    Disaster planning;    Disaster recovery planning;    Parametric systems;    Humanitarian logistics;   

Others  :  https://smartech.gatech.edu/bitstream/1853/42919/1/mma_stephanie_w_201112_phd.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

The occurrence of devastating natural disasters in the past several years have prompted communities, responding organizations, and governments to seek ways to improve disaster preparedness capabilities locally, regionally, nationally, and internationally.A holistic approach to design used in the aerospace and industrial engineering fields enables efficient allocation of resources through applied parametric changes within a particular design to improve performance metrics to selected standards.In this research, this methodology is applied to disaster preparedness, using a community's time to restoration after a disaster as the response metric.A review of the responses from Hurricane Katrina and the 2010 Haiti earthquake, among other prominent disasters, provides observations leading to some current capability benchmarking. A need for holistic assessment and planning exists for communities but the current response planning infrastructure lacks a standardized framework and standardized assessment metrics.Within the humanitarian logistics community, several different metrics exist, enabling quantification and measurement of a particular area's vulnerability.These metrics, combined with design and planning methodologies from related fields, such as engineering product design, military response planning, and business process redesign, provide insight and a framework from which to begin developing a methodology to enable holistic disaster response planning.The developed methodology was applied to the communities of Shelby County, TN and pre-Hurricane-Katrina Orleans Parish, LA. Available literature and reliable media sources provide information about the different values of system parameters within the decomposition of the community aspects and also about relationships among the parameters.The community was modeled as a system dynamics model and was tested in the implementation of two, five, and ten year improvement plans for Preparedness, Response, and Development capabilities, and combinations of these capabilities.For Shelby County and for Orleans Parish, the Response improvement plan reduced restoration time the most.For the combined capabilities, Shelby County experienced the greatest reduction in restoration time with the implementation of Development&Response capability improvements, and for Orleans Parish it was thePreparedness&Response capability improvements.Optimization of restoration time with community parameters was tested by using a Particle Swarm Optimization algorithm.Fifty different optimized restoration times were generated using the Particle Swarm Optimization algorithm and ranked using the Technique for Order Preference by Similarity to Ideal Solution.The optimization results indicate that the greatest reduction in restoration time for a community is achieved with a particular combination of different parameter values instead of the maximization of each parameter.