Decision support for long-range, community-based planning to mitigate against and recover from potential multiple disasters

This 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 lo...

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Bibliographic Details
Published in:Decision Support Systems 2016-07, Vol.87, p.13-25
Main Authors: Chacko, Josey, Rees, Loren Paul, Zobel, Christopher W., Rakes, Terry R., Russell, Roberta S., Ragsdale, Cliff T.
Format: Article
Language:English
Subjects:
Communities
Decision support
Decision support systems
Disaster management
Disaster planning
Disaster relief
Disasters
Emergency preparedness
Long term planning
Mathematical models
Mathematical programming
Multi-hazard
Recovery plans
Resilience
Studies
Sustainability
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Summary:This 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. •Our DSS math model plans for risks from multiple, perhaps concurrent, hazard sources.•The DSS model examines dependencies arising under a multi-hazard planning model.•Unlike any other models, we include both long-term mitigation and recovery strategies.•We compare our model with two previous approaches to show benefits of our method.
ISSN:0167-9236
1873-5797
DOI:10.1016/j.dss.2016.04.005