Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows

This article describes the application of stochastic measures of network resilience to waterway commodity flows. The authors define network resilience along dimensions of reliability, vulnerability, survivability, and recoverability; they quantify network resilience as a function of component and network performance. They describe a means to optimize network resilience strategies by adapting the Copeland Score for nonparametric stochastic ranking. They next present a case study of the Mississippi River Navigation System to demonstrate the use of these stochastic measures in a real-world setting that has national economic impact. The National Waterway Network (NWN) is composed of links, which represent either a shipping lane or simply a path in open water, and nodes, which are facilities such as a port, lock, dam, or an intermodal terminal. A subset of the nation’s entire waterway network of 6,906 links, the Mississippi River Navigation System includes 3,046 links and 1,545 nodes. The case study analyzes the resilience of a known number of links that might go completely inoperable due to a disruptive event, such as a drought, flood, or hurricane. The authors conclude that their methodologies can be useful for the decision-making authorities and risk managers overseeing the reliability and resilience of critical infrastructures to disruptive events. They stress that minimizing the time to full recovery can decrease the economic losses incurred by the closure of a few sections in the waterway network.

Language

  • English

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  • Accession Number: 01545495
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 30 2014 9:34AM