  The United States Coast Guard is charged with the coordination of all search
and rescue missions in maritime regions within the United States purview. Given
the size of the Pacific Ocean and the limited resources available to respond to
search and rescue missions in this region, the service seeks to posture its
aligned fleet of maritime and aeronautical assets to reduce the expected
response time for such missions. Leveraging historic event records for the
region of interest, we propose and demonstrate a two-stage solution approach.
In the first stage, we develop and apply a stochastic zonal distribution model
to evaluate spatiotemporal trends for emergency event rates and corresponding
response strategies to inform the probabilistic modeling of future rescue
events respective locations, frequencies, and demands for support. In the
second stage, the results from the aforementioned analysis enable the
parameterization and solution of a integer linear programming formulation to
identify the best locations at which to station limited heterogeneous search
and rescue assets. Considering both the 50th and 75th percentile levels of
forecast event and asset demand distributions using 7.5 years of historical
event data, our models identify asset location strategies that respectively
yield a 9.6 percent and 17.6 percent increase in coverage over current asset
basing when allowing locations among current homeports and airports, as well as
respective 67.3 percent and 57.4 percent increases in coverage when considering
a larger set of feasible basing locations.
  Keywords: search and rescue, spatiotemporal forecasting, location-allocation
modeling, p-median location problem, multi-objective optimization
