  Despite the wide range of possible scenarios in the aftermath of a disruptive
event, each community can make choices to improve its resilience, or its
ability to bounce back. A resilient community is one that has prepared for, and
can thus absorb, recover from, and adapt to the disruptive event. One important
aspect of the recovery phase is assessing the extent of the damage in the built
environment through post-event building inspections. In this paper, we develop
and demonstrate a resilience-based methodology intended to support rapid
post-event decision-making about inspection priorities with limited
information. The method uses the basic characteristics of the building stock in
a community (floor area, number of stories, type of construction and
configuration) to assign structure-specific fragility functions to each
building. For an event with a given seismic intensity, the probability of each
building reaching a particular damage state is determined, and is used to
predict the actual building states and priorities for inspection. Losses are
computed based on building usage category, estimated inspection costs, the
consequences of erroneous decisions, and the potential for unnecessary
restrictions in access. The aim is to provide a means for a community to make
rapid cost-based decisions related to inspection of their building inventory.
We pose the decision problem as an integer optimization problem that attempts
to minimize the expected loss to the community. The advantages of this approach
are that it: (i) is simple, (ii) requires minimal inventory data, (iii) is
easily scalable, and (iv) does not require significant computing power. Use of
this approach before the hazard event can also provide a community with the
means to plan and allocate resources in advance of an event to achieve the
desirable resiliency goals of the community.
