Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows

Hiba Baroud, Jose E. Ramirez‐Marquez, Kash Barker and Claudio M. Rocco

Risk Analysis, 2014, vol. 34, issue 7, 1317-1335

Abstract: Given the ubiquitous nature of infrastructure networks in today's society, there is a global need to understand, quantify, and plan for the resilience of these networks to disruptions. This work defines network resilience along dimensions of reliability, vulnerability, survivability, and recoverability, and quantifies network resilience as a function of component and network performance. The treatment of vulnerability and recoverability as random variables leads to stochastic measures of resilience, including time to total system restoration, time to full system service resilience, and time to a specific α% resilience. Ultimately, a means to optimize network resilience strategies is discussed, primarily through an adaption of the Copeland Score for nonparametric stochastic ranking. The measures of resilience and optimization techniques are applied to inland waterway networks, an important mode in the larger multimodal transportation network upon which we rely for the flow of commodities. We provide a case study analyzing and planning for the resilience of commodity flows along the Mississippi River Navigation System to illustrate the usefulness of the proposed metrics.

Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (30)

Downloads: (external link)
https://doi.org/10.1111/risa.12175

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:riskan:v:34:y:2014:i:7:p:1317-1335

Access Statistics for this article

More articles in Risk Analysis from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().