Chacko, JoseyRees, Loren P.Zobel, Christopher W.Rakes, Terry R.Russell, Roberta S.Ragsdale, Cliff T.2017-03-142017-03-142016-07-010167-9236http://hdl.handle.net/10919/76651This paper discusses a new mathematical model for community-driven disaster planning that is intended to help decision makers exploit the synergies resulting from simultaneously considering actions focusing on mitigation and efforts geared toward long-term recovery. The model is keyed on enabling long-term community resilience in the face of potential disasters of varying types, frequencies, and severities, and the approach’s highly iterative nature is facilitated by the model’s implementation in the context of a Decision Support System. Three examples from Mombasa, Kenya, East Africa, are discussed and compared in order to demonstrate the advantages of the new mathematical model over the current ad hoc mitigation and long-term recovery planning approaches that are typically used.13 - 25 (13) page(s)In CopyrightTechnologyComputer Science, Artificial IntelligenceComputer Science, Information SystemsOperations Research & Management ScienceComputer ScienceDecision supportResilienceSustainabilityMathematical programmingDisaster planningMulti-hazardTERRORISM APPLICATIONSHAZARDSRISKRESILIENCEMANAGEMENTFRAMEWORKMODELSSECURITYEQUITYASSETArticle - Refereedhttps://doi.org/10.1016/j.dss.2016.04.00587Zobel, CW [0000-0002-0952-7322]