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Title: Stochastic Optimization of Large-Scale Patient Evacuation Before Hurricanes
The total cost for weather-related disasters in the US increases over time, and hurricanes usually create the most damage. One of the challenges, which is present in almost every major hurricane event, is the patient evacuation mission. We propose a comprehensive modeling and methodological framework for a large-scale patient evacuation problem when an area is faced with a forecasted disaster such as a hurricane. In this work, we integrate a hurricane scenario generation scheme using publicly available surge level forecasting software and a scenario-based stochastic integer program to make decisions on patient movements, staging area locations and positioning of emergency medical vehicles with an objective of minimizing the total expected cost of evacuation and the setup cost of staging areas. The hurricane scenario generation scheme incorporates the uncertainties in the hurricane intensity, direction, forward speed and tide level. To demonstrate the modeling approach, we apply real-world data from the Southeast Texas region in our experiments. We highlight the importance of operation time limits, the number of available resources and an accurate forecast on forthcoming hurricanes in determining the locations of staging areas and patient evacuation decisions.  more » « less
Award ID(s):
1940308
NSF-PAR ID:
10291201
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
IISE Annual Conference
Page Range / eLocation ID:
1682-1687
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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