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Designing Response Supply Chain Against Bioattacks

Author(s)
Simchi-Levi, David; Trichakis, Nikolaos; Zhang, Yun
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Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/
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Abstract
We study a prescriptive model for end-to-end design of a supply chain for medical countermeasures (MCMs) to defend against bioattacks. We model the defender's MCMs inventory prepositioning and dispensing capacity installation decisions, attacker's move, and defender's adjustable shipment decisions so as to minimize inventory and lifeloss costs subject to population survivability targets. We explicitly account for the strategic interaction between defender's and attacker's actions, assuming information transparency. We consider the affinely adjustable robust counterpart (AARC) to our problem, which enables us to deal with realistic networks comprising millions of nodes. We provide theoretical backing to the AARC performance by proving its optimality under certain conditions. We conduct a high-fidelity case study on the design of an MCMs supply chain with millions of nodes to guard against anthrax attacks in the United States. We calibrate our model using data from a wide variety of sources, including literature and field experiments. We produce policy insights that have been long sought after but elusive until now. ©2019 INFORMS.
Date issued
2019-08
URI
https://hdl.handle.net/1721.1/126166
Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering; Massachusetts Institute of Technology. Institute for Data, Systems, and Society; Massachusetts Institute of Technology. Operations Research Center; Sloan School of Management
Journal
Operations Research
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Citation
Simchi-Levi, David et al., "Designing Response Supply Chain Against Bioattacks." Operations Research 67, 5 (September-October 2019): p. 1246–68 doi. 10.1287/opre.2019.1862 ©2019 Authors
Version: Author's final manuscript
ISSN
1526-5463

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