Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows

TLDR

Given the ubiquity of infrastructure networks, there is a global need to understand, quantify, and plan for their resilience to disruptions. The study defines network resilience in terms of reliability, vulnerability, survivability, and recoverability, quantifies it as a function of component and network performance, and proposes optimizing strategies using a Copeland‑Score adaptation. By modeling vulnerability and recoverability as random variables, the authors derive stochastic resilience metrics—time to total restoration, time to full service, and time to a specified α% resilience—and apply these measures, along with a Copeland‑Score–based optimization, to inland waterway networks. A case study on the Mississippi River Navigation System demonstrates the practical utility of the proposed resilience metrics for planning commodity flow resilience.

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.