Critical infrastructure networks, including water, power, communication, and transportation, among others, are necessary to society’s functionality. In recent years, the threat of different types of disruptions to such infrastructure networks has become an increasingly important problem to address. Due to existing interdependencies, damage to a small area of one of the networks could have far-reaching effects on the ability to meet demand across the entire system. Common disruption scenarios include, among others, intentional malevolent attacks, natural disasters, and random failures. Similar works have focused on only one type of scenario, but combining a variety of disruptions may lead to more realistic results. Additionally, the concept of social vulnerability, which describes an area’s ability to prepare for and respond to a disruption, must be included. This should promote not only the protection of the most at-risk components but also ensure that socially vulnerable communities are given adequate resources. This work provides a decision making framework to determine the allocation of defensive resources that accounts for all these factors. Accordingly, we propose a multi-objective mathematical model with the objectives of: (i) minimizing the vulnerability of a system of interdependent infrastructure networks, and (ii) minimizing the total cost of the resource allocation strategy. Moreover, to account for uncertainty in the proposed model, this paper incorporates a means to address robustness in finding the most adaptable network protection plan to reduce the vulnerability of the system of interdependent networks to a variety of disruption scenarios. The proposed work is illustrated with an application to social vulnerability and interdependent power, gas, and water networks in Shelby County, Tennessee.
|Number of pages||16|
|Journal||Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability|
|State||Published - Oct 2021|
Bibliographical noteFunding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported in part by the National Science Foundation through awards 1541165 and 1635813. Further, the authors gratefully acknowledge the assistance of Ms. Deniz Berfin Karakoc.
© IMechE 2021.
- Interdependent networks
- multi-criteria decision analysis
- robust allocation
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality