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

•A new resilience-based component importance measure for networks is put forth.•The multi-state characteristic of networks is taken account in the new measure.•Both capacity improvement and recovery time of a component are jointly quantified.•A stochastic ranking approach is used to identify importa...

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Veröffentlicht in:Reliability engineering & system safety 2020-01, Vol.193, p.106591, Article 106591
Hauptverfasser: Xu, Zhaoping, Ramirez-Marquez, Jose Emmanuel, Liu, Yu, Xiahou, Tangfan
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container_title Reliability engineering & system safety
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creator Xu, Zhaoping
Ramirez-Marquez, Jose Emmanuel
Liu, Yu
Xiahou, Tangfan
description •A new resilience-based component importance measure for networks is put forth.•The multi-state characteristic of networks is taken account in the new measure.•Both capacity improvement and recovery time of a component are jointly quantified.•A stochastic ranking approach is used to identify importance rank of components. 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.
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subjects Component importance measure
Component reliability
Economic conditions
Economic impact
Human error
Measurement methods
Minimal recovery paths
Multi-state networks
Natural disasters
Network resilience
Probability distribution
Ranking
Recovery time
Reliability engineering
Resilience
Restoration
Roads
Stochastic processes
Stochastic ranking
Stochasticity
Transportation networks
title A new resilience-based component importance measure for multi-state networks
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