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Exploring Recovery Strategies for Optimal Interdependent Infrastructure Network Resilience

Authors:
Yasser Almoghathawi at King Fahd University of Petroleum and Minerals
Yasser Almoghathawi
Andres Gonzalez at University of Oklahoma
Andres Gonzalez
Kash Barker at University of Oklahoma
Kash Barker
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Infrastructure networks such as power, communication, gas, water, and transportation rely on one another for their proper functioning. Such infrastructure networks are subject to diverse disruptive events, including random failures, malevolent attacks, and natural disasters, which could significantly affect their performance and adversely impact economic productivity. Moreover, the proliferation of interdependencies among infrastructure networks has increased the complexity associated with recovery planning after a disruptive event. Consequently, providing solution approaches to restore interdependent networks following the occurrence of a disruptive event has attracted many researchers in the last decade. The goal of this paper is to help decision makers plan for recovery following the occurrence of a disruptive event, to procure strategies that center not only on recovering the system promptly, but also such that the weighted average performance of the system is maximized during the recovery process (i.e., enhancing its resilience). Accordingly, this paper studies the interdependent network restoration problem (INRP) and proposes a resilience-driven multi-objective optimization model to solve it. The proposed model aims to: (i) prioritize the restoration of the disrupted components for each infrastructure network, and (ii) assign and schedule the prioritized networks components to the available work crews, such that the resilience of the system of interdependent infrastructure networks is enhanced considering the physical interdependency among them. The proposed model is formulated using mixed-integer programming (MIP) with the objectives of: (i) enhancing the resilience of the system of interdependent infrastructure networks, and (ii) minimizing the total costs associated with the restoration process (i.e., flow, restoration, and disruption costs). Moreover, the proposed model considers partial disruptions and recovery of the disrupted network components, and partial dependence between nodes in different networks. The proposed model is illustrated through a system of interdependent infrastructure networks after multiple hypothetical earthquakes in Shelby County, TN, United States.
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Exploring Recovery Strategies for Optimal
Interdependent Infrastructure Network Resilience
Yasser Almoghathawi
1
&Andrés D. González
2
&Kash Barker
2
#The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021
Abstract
Infrastructure networks such as power, communication, gas, water, and transportation rely
on one another for their proper functioning. Such infrastructure networks are subject to
diverse disruptive events, including random failures, malevolent attacks, and natural disas-
ters, which could significantly affect their performance and adversely impact economic
productivity. Moreover, the proliferation of interdependencies among infrastructure net-
works has increased the complexity associated with recovery planning after a disruptive
event. Consequently, providing solution approaches to restore interdependent networks
following the occurrence of a disruptive event has attracted many researchers in the last
decade. The goal of this paper is to help decision makers plan for recovery following the
occurrence of a disruptive event, to procure strategies that center not only on recovering the
system promptly, but also such that the weighted average performance of the system is
maximized during the recovery process (i.e., enhancing its resilience). Accordingly, this
paper studies the interdependent network restoration problem (INRP) and proposes a
resilience-driven multi-objective optimization model to solve it. The proposed model aims
to: (i) prioritize the restoration of the disrupted components for each infrastructure network,
and (ii) assign and schedule the prioritized networks components to the available work
crews, such that the resilience of the system of interdependent infrastructure networks is
enhanced considering the physical interdependency among them. The proposed model is
formulated using mixed-integer programming (MIP) with the objectives of: (i) enhancing
the resilience of the system of interdependent infrastructure networks, and (ii) minimizing
the total costs associated with the restoration process (i.e., flow, restoration, and disruption
costs). Moreover, the proposed model considers partial disruptions and recovery of the
disrupted network components, and partial dependence between nodes in different net-
works. The proposed model is illustrated through a system of interdependent infrastructure
networks after multiple hypothetical earthquakes in Shelby County, TN, United States.
Keywords Interdependent networks .Resilience .Restoration .Optimization
https://doi.org/10.1007/s11067-020-09515-4
*Kash Barker
kashbarker@ou.edu
Extended author information available on the last page of the article
Accepted: 18 December 2020 / Published online: 19 February 2021
Networks and Spatial Economics (2021) 21:229–260
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
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