Multiobjective Stochastic Inoperability Decision Tree for Infrastructure Preparedness
Publication: Journal of Infrastructure Systems
Volume 20, Issue 2
Abstract
Decision making for managing risks to critical infrastructure systems requires accounting for (1) the uncertain behavior of disruptive events; and (2) the interdependent nature of such systems that lead to large-scale inoperability. This paper integrates a dynamic risk-based interdependency model, the dynamic inoperability input-output model, with a multiobjective decision tree to analyze preparedness decisions. The use of a dynamic model allows for resilience and recovery decisions to be incorporated in the decision-making framework, and uncertainty is accounted for using probability distributions. The multiobjective inoperability decision tree is applied to the study of transportation infrastructure disruptions, namely closures of an inland waterway and an inland waterway port. A data-driven multiregional study of the Port of Catoosa in Oklahoma, along the Mississippi River Navigation System, is discussed and suggests careful consideration when investing larger amounts toward port security.
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Acknowledgments
The authors wish to acknowledge the assistance of Dr. Cameron MacKenzie, Assistant Professor with the Naval Postgraduate School, and Dr. Raghav Pant, Infrastructure Network Analyst with the University of Oxford. This work was supported in part by the U.S. Federal Highway Administration, under awards SAFTEA-LU 1934 and SAFTEA-LU 1702, and the National Science Foundation, Division of Civil, Mechanical, and Manufacturing Innovation, under award 0927299. Further, the suggestions of the reviewers significantly improved this paper.
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Published In
Journal of Infrastructure Systems
Volume 20 • Issue 2 • June 2014
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Aug 30, 2012
Accepted: May 22, 2013
Published online: May 24, 2013
Discussion open until: May 26, 2014
Published in print: Jun 1, 2014
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