Stochastic measures of resilience and their application to container terminals

•Mathematical Framework for the analysis of system resilience.•Mathematical description of metrics for resilience quantification.•Approach tying vulnerability, survivability and recoverability to network resilience.•Application implement in Container terminals.

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.