Date Published: February 14, 2018
Publisher: Public Library of Science
Author(s): Aybike Ulusan, Ozlem Ergun, Zhengbing He.
Due to the ubiquitous nature of disruptive extreme events, functionality of the critical infrastructure systems (CIS) is constantly at risk. In case of a disruption, in order to minimize the negative impact to the society, service networks operating on the CIS should be restored as quickly as possible. In this paper, we introduce a novel network science inspired measure to quantify the criticality of components within a disrupted service network and develop a restoration heuristic (Cent-Restore) that prioritizes restoration efforts based on this measure. As an illustrative case study, we consider a road network blocked by debris in the aftermath of a natural disaster. The debris obstructs the flow of relief aid and search-and-rescue teams between critical facilities and disaster sites, debilitating the emergency service network. In this context, the problem is defined as finding a schedule to clear the roads with the limited resources. First, we develop a mixed-integer programming model for the problem. Then we validate the efficiency and accuracy of the Cent-Restore heuristic on randomly generated instances by comparing it to the model. Furthermore, we use Cent-Restore to recommend real-time restoration plans for disrupted road networks of Boston and Manhattan and analyze the performance of the plans over time through resilience curves. We compare Cent-Restore to the current restoration guidelines proposed by FEMA and other strategies that prioritize the restoration efforts based on different measures. As a result we confirm the importance of including specific post-disruption attributes of the networks to create effective restoration strategies. Moreover, we explore the relationship between a service network’s resilience and its topological and operational characteristics under different disruption scenarios. The methods and insights provided in this work can be extended to other disrupted large-scale critical infrastructure systems in which the ultimate goal is to enable the functions of the overlaying service networks.
Critical infrastructure systems (CIS) underpin almost every aspect of the modern society by providing the essential functions through overlaying service networks. These service networks are commonly referred to as lifelines and considered vital such that their destruction would have a debilitating effect on economic productivity and daily living [1, 2]. Thus, after an extreme event disrupts them, it is important to restore the critical services provided by CIS as soon as possible, in order to minimize the negative impact to society. In this paper, we develop a generalizable measure and a framework to help stakeholders and managers of CIS to efficiently plan restoration operations so that the services provided within the system recover from unexpected major disruptions in a timely manner.
In this paper, we integrated ideas from the field of network science and operations research to establish effective recovery plans to improve the resilience of critical infrastructure systems. In addition, we provide insights on how the information on the impact of a disruption and the operational and topological attributes of service networks benefit the resilience analysis.