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Interdependent Network Recovery Games

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  • Andrew M. Smith
  • Andrés D. González
  • Leonardo Dueñas‐Osorio
  • Raissa M. D'Souza

Abstract

Recovery of interdependent infrastructure networks in the presence of catastrophic failure is crucial to the economy and welfare of society. Recently, centralized methods have been developed to address optimal resource allocation in postdisaster recovery scenarios of interdependent infrastructure systems that minimize total cost. In real‐world systems, however, multiple independent, possibly noncooperative, utility network controllers are responsible for making recovery decisions, resulting in suboptimal decentralized processes. With the goal of minimizing recovery cost, a best‐case decentralized model allows controllers to develop a full recovery plan and negotiate until all parties are satisfied (an equilibrium is reached). Such a model is computationally intensive for planning and negotiating, and time is a crucial resource in postdisaster recovery scenarios. Furthermore, in this work, we prove this best‐case decentralized negotiation process could continue indefinitely under certain conditions. Accounting for network controllers' urgency in repairing their system, we propose an ad hoc sequential game‐theoretic model of interdependent infrastructure network recovery represented as a discrete time noncooperative game between network controllers that is guaranteed to converge to an equilibrium. We further reduce the computation time needed to find a solution by applying a best‐response heuristic and prove bounds on ε‐Nash equilibrium, where ε depends on problem inputs. We compare best‐case and ad hoc models on an empirical interdependent infrastructure network in the presence of simulated earthquakes to demonstrate the extent of the tradeoff between optimality and computational efficiency. Our method provides a foundation for modeling sociotechnical systems in a way that mirrors restoration processes in practice.

Suggested Citation

  • Andrew M. Smith & Andrés D. González & Leonardo Dueñas‐Osorio & Raissa M. D'Souza, 2020. "Interdependent Network Recovery Games," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 134-152, January.
  • Handle: RePEc:wly:riskan:v:40:y:2020:i:1:p:134-152
    DOI: 10.1111/risa.12923
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    References listed on IDEAS

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    2. Hao, Yucheng & Jia, Limin & Zio, Enrico & Wang, Yanhui & Small, Michael & Li, Man, 2023. "Improving resilience of high-speed train by optimizing repair strategies," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    3. Magoua, Joseph Jonathan & Li, Nan, 2023. "The human factor in the disaster resilience modeling of critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
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    5. Canbilen Sütiçen, Tuğçe & Batun, Sakine & Çelik, Melih, 2023. "Integrated reinforcement and repair of interdependent infrastructure networks under disaster-related uncertainties," European Journal of Operational Research, Elsevier, vol. 308(1), pages 369-384.
    6. Du, Ao & Wang, Xiaowei & Xie, Yazhou & Dong, You, 2023. "Regional seismic risk and resilience assessment: Methodological development, applicability, and future research needs – An earthquake engineering perspective," Reliability Engineering and System Safety, Elsevier, vol. 233(C).

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