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  4. A MULTI-STAGED STOCHASTIC OPTIMIZATION MODEL WITH COLUMN GENERATION BASED HEURISTICS FOR HOSPITAL EVACUATIONS DURING HURRICANES

A MULTI-STAGED STOCHASTIC OPTIMIZATION MODEL WITH COLUMN GENERATION BASED HEURISTICS FOR HOSPITAL EVACUATIONS DURING HURRICANES

File(s)
Zhang_cornell_0058_11600.pdf (1.39 MB)
Permanent Link(s)
https://doi.org/10.7298/facs-hr43
https://hdl.handle.net/1813/113061
Collections
Cornell Theses and Dissertations
Author
Zhang, Qian
Abstract

Perpetual hospital evacuations caused by hurricanes require well-informed decision makings to handle uncertainty in future conditions and scarcity in various resources. Simultaneous evacuations from multiple hospitals are more challenging due to additional complexity in evacuation route choices and coordination among both evacuating and receiving hospitals. This thesis addresses above issues by developing a multi-staged stochastic optimization model and column generation based heuristics that considers uncertain future flood, wind and road traffic conditions, limited staff and vehicle resources, and effectiveness of evacuation routes generation. The model determines patient evacuation schedule and corresponding evacuation routes while trading off risk and cost. A comprehensive case study on North Carolina hospitals with Hurricane Isabel is conducted with data and model outputs of previous research. The results highlight the benefits of the model formulation and the heuristics that effectively generates complex evacuation routes and coordinates evacuating hospitals’ efforts while adapting to new information.

Description
89 pages
Date Issued
2022-12
Committee Chair
Nozick, Linda
Committee Member
Gao, H. Oliver
Degree Discipline
Systems Engineering
Degree Name
M.S., Systems Engineering
Degree Level
Master of Science
Type
dissertation or thesis
Link(s) to Catalog Record
https://newcatalog.library.cornell.edu/catalog/15644039

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