The Multi-phase spatial meta-heuristic algorithm for public health
  emergency transportation
  The delivery of Medical Countermeasures(MCMs) for mass prophylaxis in the
case of a bio-terrorist attack is an active research topic that has interested
the research community over the past decades. The objective of this study is to
design an efficient algorithm for the Receive Reload and Store Problem(RSS) in
which we aim to find feasible routes to deliver MCMs to a target population
considering time, physical, and human resources, and capacity limitations. For
doing this, we adapt the p-median problem to the POD-based emergency response
planning procedures and propose an efficient algorithm solution to perform the
p-median in reasonable computational time. We present RE-PLAN, the Response
PLan Analyzer system that contains some RSS solutions developed at The Center
for Computational Epidemiology and Response Analysis (CeCERA) at the University
of North Texas. Finally, we analyze a study case where we show how the
computational performance of the algorithm can impact the process of decision
making and emergency planning in the short and long terms.
