Toward Decentralized Decision-Making for Interdependent Infrastructure Network Resilience

Cilali, Buket; Ghorbani-Renani, Nafiseh; Barker, Kash; González, Andrés D.

doi:10.1007/978-3-030-64973-9_4

Cited by 2 publications

(2 citation statements)

References 27 publications

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“…This approach brings more features with realistic characteristics to the analysis, although it adds to the complexity of the problem. Many researchers have also investigated this approach considering various definitions and solution methods, demonstrating the cooperative or noncooperative nature of decision‐makers in the system (Cil1ali et al., 2021; Ghorbani‐Renani et al., 2020; 2021; Guan & Zhuang, 2015; Lou et al., 2017; Smith et al., 2020; Talebiyan & Duenas‐Osorio, 2020).…”

Section: Introductionmentioning

confidence: 99%

Game‐theoretic algorithm for interdependent infrastructure network restoration in a decentralized environment

Rangrazjeddi,

González,

Barker

2024

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Having reliable interdependent infrastructure networks is vital for well‐being of a safe and productive society. Systems are vulnerable to failure or performance loss due to their interdependence among various networks, as each failure can propagate through the whole system. Although the conventional view has concentrated on optimizing the restoration of critical interdependent infrastructure networks using a centralized approach, having a lone actor as a decision‐maker in the system is substantially different from the actual restoration decision environment, wherein infrastructure utilities make their own decisions about how to restore their network service. In a decentralized environment, the definition of whole system optimality does not apply as each decision‐maker's interest may not converge with the others. Subsequently, this results in each decision‐maker developing its own reward functions. Therefore, in this study, we address the concern of having multiple decision‐makers with various payoff functions in interdependent networks by proposing a decentralized game theory algorithm for finding Nash equilibria solutions for network restoration in postdisaster situations.

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Section: Introductionmentioning

confidence: 99%

Game‐theoretic algorithm for interdependent infrastructure network restoration in a decentralized environment

Rangrazjeddi,

González,

Barker

2024

Risk Analysis

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“…As a result, many models and algorithms have been developed to determine restoration schedules for disrupted networks from a centralized perspective, where a complex system is controlled by an overarching decision-maker [ 13 – 20 ]. However, in many real cases, the restoration of infrastructure networks is scheduled in decentralized manner, as different networks are controlled by different entities (e.g., utility companies), potentially autonomous and potentially with conflicting interests [ 9 , 21 – 24 ]. As such, game theory can be effective in describing the effect of the selection of different strategies by one decision-maker on those of another.…”

Section: Introductionmentioning

confidence: 99%

Adaptive algorithm for dependent infrastructure network restoration in an imperfect information sharing environment

2022

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Critical infrastructure networks are vital for a functioning society and their failure can have widespread consequences. Decision-making for critical infrastructure resilience can suffer based on several characteristics exhibited by these networks, including (i) that there exist interdependencies with other networks, (ii) that several decision-makers represent potentially competing interests among the interdependent networks, and (iii) that information about other decision-makers’ actions are uncertain and potentially unknown. To address these concerns, we propose an adaptive algorithm using machine learning to integrate predictions about other decision-makers’ behavior into an interdependent network restoration planning problem considering an imperfect information sharing environment. We examined our algorithm against the optimal solution for various types, sizes, and dependencies of networks, resulting in insignificant differences. To assess the proposed algorithm’s efficiency, we compared its results with a proposed heuristic method that prioritizes, and schedules components restoration based on centrality-based importance measures. The proposed algorithm provides a solution sufficiently close to the optimal solution showing the algorithm performs well in situations where the information sharing environment is incomplete.

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Toward Decentralized Decision-Making for Interdependent Infrastructure Network Resilience

Cited by 2 publications

References 27 publications

Game‐theoretic algorithm for interdependent infrastructure network restoration in a decentralized environment

Game‐theoretic algorithm for interdependent infrastructure network restoration in a decentralized environment

Adaptive algorithm for dependent infrastructure network restoration in an imperfect information sharing environment

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