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Supply Location and Transportation Planning for Hurricanes: A Two-stage Stochastic Programming Framework
European Journal of Operational Research (Forthcoming) (2018)
  • Jomon Aliyas Paul
  • Minjiao Zhang, Kennesaw State University
Abstract
We develop a two-stage stochastic programming model with recourse actions for hurricane preparedness.   In  the  first  stage,  it  works  to  optimize  the  locations  of  Points  of  Distribution (PODs), medical supply levels, and transportation capacity, and in the second, transportation decisions  or  flow.   Our  model  minimizes  the  total  social  cost,  comprised  of  deprivation  and commercial logistics costs.  Contrary to the extant literature,  which typically employs robust optimization, we use probability distributions to avoid overly conservative estimates of hurricane impact.  Additionally, our model facilitates the determination of optimal deployment time.  We demonstrate the benefits of our approach in a case study.  As risk attitude goes from optimistic to pessimistic, decision makers increase the number of PODs exponentially to spread the risk around.  A similar trend holds for total costs as a function of hurricane category and its interplay with risk.  Further, for lower strength hurricanes, regardless of risk attitude, the optimal decision is  to  deploy  closer  to  landfall  at  12  hours;  for higher  strength  hurricanes,  resources  are  best deployed earlier, at 36 hours, based on an exponential increase in demand for medical supplies. Deployment  cost  also  increases exponentially  as  landfall  approaches.   These  costs  outweigh deprivation savings from an accurate demand estimate closer to landfall.  However, when budget is limited, risk attitude is found to influence deployment decisions and a funding preference for lower severity-level supplies.


Publication Date
2018
Citation Information
Jomon Aliyas Paul and Minjiao Zhang. "Supply Location and Transportation Planning for Hurricanes: A Two-stage Stochastic Programming Framework" European Journal of Operational Research (Forthcoming) (2018)
Available at: http://works.bepress.com/jomonaliyas_paul/45/