TY - JOUR
T1 - Stochastic measures of resilience and their application to container terminals
AU - Pant, Raghav
AU - Barker, Kash
AU - Ramirez-Marquez, Jose Emmanuel
AU - Rocco, Claudio M.
PY - 2014/4
Y1 - 2014/4
N2 - Abstract While early research efforts were devoted to the protection of systems against disruptive events, be they malevolent attacks, man-made accidents, or natural disasters, recent attention has been given to the resilience, or the ability of systems to "bounce back," of these events. Discussed here is a modeling paradigm for quantifying system resilience, primarily as a function of vulnerability (the adverse initial system impact of the disruption) and recoverability (the speed of system recovery). To account for uncertainty, stochastic measures of resilience are introduced, including Time to Total System Restoration, Time to Full System Service Resilience, and Time to α%-Resilience. These metrics are applied to quantify the resilience of inland waterway ports, important hubs in the flow of commodities, and the port resilience approach is deployed in a data-driven case study for the inland Port of Catoosa in Oklahoma. The contributions herein demonstrate a starting point in the development of a resilience decision making framework.
AB - Abstract While early research efforts were devoted to the protection of systems against disruptive events, be they malevolent attacks, man-made accidents, or natural disasters, recent attention has been given to the resilience, or the ability of systems to "bounce back," of these events. Discussed here is a modeling paradigm for quantifying system resilience, primarily as a function of vulnerability (the adverse initial system impact of the disruption) and recoverability (the speed of system recovery). To account for uncertainty, stochastic measures of resilience are introduced, including Time to Total System Restoration, Time to Full System Service Resilience, and Time to α%-Resilience. These metrics are applied to quantify the resilience of inland waterway ports, important hubs in the flow of commodities, and the port resilience approach is deployed in a data-driven case study for the inland Port of Catoosa in Oklahoma. The contributions herein demonstrate a starting point in the development of a resilience decision making framework.
KW - Infrastructure systems
KW - Keywords
KW - Recoverability
KW - Resilience
KW - Vulnerability
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U2 - 10.1016/j.cie.2014.01.017
DO - 10.1016/j.cie.2014.01.017
M3 - Article
AN - SCOPUS:84894522167
SN - 0360-8352
VL - 70
SP - 183
EP - 194
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
IS - 1
ER -