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Title: Integrated Hurricane Relief Logistics and Evacuation Planning under Forecast Uncertainty: A Case Study for Hurricane Florence
In this paper, we study an integrated hurricane relief logistics and evacuation planning (HRLEP) problem. We propose stochastic optimization models and methods that integrate the hurricane relief item pre-positioning problem and the hurricane evacuation planning problem, which are often treated as separate problems in the literature, by incorporating the forecast information as well as the forecast errors (FE). Specifically, we fit historical FE data into an auto-regressive model of order one (AR-1), from which we generate FE realizations to create evacuation demand scenarios. We compare a static decision policy based on the proposed stochastic optimization model with a dynamic policy obtained by applying this model in a rolling-horizon (RH) procedure. We conduct a preliminary numerical experiment based on real-world data to validate the value of stochastic optimization and the value of the dynamic policy based on the RH procedure.  more » « less
Award ID(s):
2045744
NSF-PAR ID:
10428837
Author(s) / Creator(s):
;
Editor(s):
Babski-Reeves, K.; Eksioglu, B.; Hampton, D.
Date Published:
Journal Name:
Proceedings of the IISE Annual Conference & Expo 2023
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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