TY - JOUR
T1 - Multiobjective formulation for protection allocation in interdependent infrastructure networks using an attack-diffusion model
AU - Rocco, Claudio M.
AU - Barker, Kash
AU - Moronta, Jose
AU - Ramirez-Marquez, Jose E.
N1 - Publisher Copyright:
© 2018 American Society of Civil Engineers.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - Interdependent networks are a collection of individual networks that contain nodes that have interdependent relationships with nodes of other networks. Recognizing that many real-life networks are interdependent, approaches that were previously developed to study vulnerability in single networks are being extended to interdependent network applications (e.g., intentional attack of selected nodes). As such, this study proposes an approach for finding the best set of protection strategies for a given set of interdependent networks exposed to random or intentional attacks through the development of a multiobjective optimization formulation. A simple diffusion model [susceptible-infected-recovered (SIR)], based on cellular automata is used to describe the dynamics of the spread of the disruptive event through each individual network, and Monte Carlo simulation enables simulating the stochastic evolution of the disruption between the nodes of the interdependent networks. Several criteria considering the results of the propagation dynamics in each network or in the whole set of interdependent networks are proposed to assess the security characteristics of the network, and Pareto-optimal solutions are derived using the multiobjective evolutionary Nondominated Sorting Genetic Algorithm (NSGA-II). An example using the topology of an Italian electric power network and the set of communities previously defined illustrates the approach.
AB - Interdependent networks are a collection of individual networks that contain nodes that have interdependent relationships with nodes of other networks. Recognizing that many real-life networks are interdependent, approaches that were previously developed to study vulnerability in single networks are being extended to interdependent network applications (e.g., intentional attack of selected nodes). As such, this study proposes an approach for finding the best set of protection strategies for a given set of interdependent networks exposed to random or intentional attacks through the development of a multiobjective optimization formulation. A simple diffusion model [susceptible-infected-recovered (SIR)], based on cellular automata is used to describe the dynamics of the spread of the disruptive event through each individual network, and Monte Carlo simulation enables simulating the stochastic evolution of the disruption between the nodes of the interdependent networks. Several criteria considering the results of the propagation dynamics in each network or in the whole set of interdependent networks are proposed to assess the security characteristics of the network, and Pareto-optimal solutions are derived using the multiobjective evolutionary Nondominated Sorting Genetic Algorithm (NSGA-II). An example using the topology of an Italian electric power network and the set of communities previously defined illustrates the approach.
KW - Cellular automata
KW - Diffusion model
KW - Interdependent networks
KW - Monte Carlo simulation
KW - Multiobjective optimization
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U2 - 10.1061/(ASCE)IS.1943-555X.0000415
DO - 10.1061/(ASCE)IS.1943-555X.0000415
M3 - Article
AN - SCOPUS:85042125739
SN - 1076-0342
VL - 24
JO - Journal of Infrastructure Systems
JF - Journal of Infrastructure Systems
IS - 1
M1 - 04018002
ER -