A new resilience-based component importance measure for multi-state networks

Zhaoping Xu, Jose Emmanuel Ramirez-Marquez, Yu Liu and Tangfan Xiahou

Reliability Engineering and System Safety, 2020, vol. 193, issue C

Abstract: Disruptive events such as natural disasters and human errors can have widespread adverse impacts on several networked infrastructures, affecting their functionalities and possibly resulting in large economic losses. It is, therefore, of great significance for these networks to exhibit resilience, defined as the ability of a network to recover from a disruptive event. Inspired by the measures of component importance used in reliability communities, this paper proposes a new resilience-based component importance ranking measure for multi-state networks from the perspective of a post-disaster restoration process. Considering the stochastic nature of disruptive events, the importance measure of each component is evaluated by finding the minimal recovery paths for various disruptive events, and it can be represented by a probability distribution. A stochastic ranking approach is implemented to identify the importance rank of each component in a network. Compared to existing methods, the proposed importance measure not only takes the multi-state characteristics of a network and its components into account but also quantifies the impact of both capacity improvement and recovery time of a component on network resilience. The proposed importance measure is exemplified through case studies in the Seervada Park road network.

Keywords: Network resilience; Multi-state networks; Component importance measure; Minimal recovery paths; Stochastic ranking (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:193:y:2020:i:c:s0951832019303710

DOI: 10.1016/j.ress.2019.106591

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