Decision support for prioritizing critical societal services in optimal post-disaster critical lifeline recovery

Critical societal services, such as health care, education, law enforcement, and emergency response, are key to societal well-being and safety. Disruption to these services may arise from direct damage to the buildings from which the services are provided, or indirectly as a consequence of damage to supporting lifelines. The order in which lifeline elements are restored post-disaster affects not only the timing for restoring the lifeline services to its customers, but also the timing for restoring critical services that rely on these lifelines. In this paper, a mathematical formulation of the problem of prioritizing critical societal services in lifeline service restoration treated by multiple, specialized crews and exact algorithmic approach for its solution are proposed. Two approaches to accelerate the solution algorithm for use in realistic settings, where efficiency and scalability are essential, are presented. The developed techniques can be embedded in a decision support tool for real-time application with real-time information. To illustrate the proposed modeling and solution methodology and assess its efficiency for large, complex multi-lifeline applications, numerical experiments were run on a synthetic yet real-world network involving three key lifelines, including power, water, and transportation, as well as two hospitals that rely on them. The analysis of this case study shows that cross-lifeline collaboration in prioritization and scheduling in restoration action affects not only the return of services from the individual lifelines, but also of critical services on which, particularly in disaster settings, lives may depend.