TY - JOUR
T1 - Regional resilience analysis
T2 - A multiscale approach to optimize the resilience of interdependent infrastructure
AU - Sharma, Neetesh
AU - Tabandeh, Armin
AU - Gardoni, Paolo
N1 - Funding Information:
The research presented in this paper was supported in part by the Center for Risk‐Based Community Resilience Planning funded by the U.S. National Institute of Standards and Technology (NIST Financial Assistance Award Number: 70NANB15H044) and by the Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) Program of the National Science Foundation (Award Number: 1638346). The views expressed are those of the authors and may not represent the official position of the sponsors.
PY - 2020/12
Y1 - 2020/12
N2 - Reducing hazard-induced disruptions to infrastructure functionality is cardinal to regional resilience. Specifically, effective strategies to enhance regional resilience require: (a) developing mathematical models for infrastructure recovery; (b) quantifying resilience associated with the developed recovery process; and (c) developing a computationally manageable approach for resilience optimization. This paper proposes a rigorous mathematical formulation to model recovery, quantify resilience, and optimize the resilience of large-scale infrastructure. Specifically, a multiscale model of the recovery process is proposed that significantly reduces the computational cost, while favoring practical and easily manageable recovery schedules. To quantify regional resilience, resilience metrics are proposed that capture the temporal and spatial variations of the recovery process. The paper then formulates a multiobjective optimization problem that aims to improve regional resilience in terms of the proposed metrics, while minimizing the recovery cost. Finally, the paper illustrates the proposed formulation by considering interdependent infrastructure in Shelby County, Tennessee, United States.
AB - Reducing hazard-induced disruptions to infrastructure functionality is cardinal to regional resilience. Specifically, effective strategies to enhance regional resilience require: (a) developing mathematical models for infrastructure recovery; (b) quantifying resilience associated with the developed recovery process; and (c) developing a computationally manageable approach for resilience optimization. This paper proposes a rigorous mathematical formulation to model recovery, quantify resilience, and optimize the resilience of large-scale infrastructure. Specifically, a multiscale model of the recovery process is proposed that significantly reduces the computational cost, while favoring practical and easily manageable recovery schedules. To quantify regional resilience, resilience metrics are proposed that capture the temporal and spatial variations of the recovery process. The paper then formulates a multiobjective optimization problem that aims to improve regional resilience in terms of the proposed metrics, while minimizing the recovery cost. Finally, the paper illustrates the proposed formulation by considering interdependent infrastructure in Shelby County, Tennessee, United States.
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U2 - 10.1111/mice.12606
DO - 10.1111/mice.12606
M3 - Article
AN - SCOPUS:85089092761
VL - 35
SP - 1315
EP - 1330
JO - Computer-Aided Civil and Infrastructure Engineering
JF - Computer-Aided Civil and Infrastructure Engineering
SN - 1093-9687
IS - 12
ER -