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Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience

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  • Ghorbani-Renani, Nafiseh
  • González, Andrés D.
  • Barker, Kash
  • Morshedlou, Nazanin

Abstract

Resilience is often thought of as the ability to withstand a disruption and recover quickly from it. Thus, improving the resilience of an infrastructure system is often associated with reducing its vulnerability (related to the extent to which a network is disrupted), and increasing its recoverability (related to the speed of restoration). To address these concerns simultaneously, we propose a tri-level protection-interdiction-restoration problem for a system of interdependent networks, to optimally balance vulnerability and recoverability before and after a disruption. In particular, the proposed tri-level model represents decisions made (i) by a defender before a disruption to reduce network vulnerability, (ii) by an attacker to effectively disrupt the network, and (iii) by a defender after the disruption to enhance recoverability. To solve the proposed protection-interdiction-restoration model to optimality, we use a tailored extension of the covering decomposition algorithm. To illustrate the proposed tri-level model and the modified covering decomposition algorithm, we present a case-study of the system of interdependent water, gas, and power utilities in Shelby County, TN. The computational results show the value of simultaneous analysis of both pre-disruption investments (to reinforce critical network components) and post-disruption resource assignment and crew scheduling.

Suggested Citation

  • Ghorbani-Renani, Nafiseh & González, Andrés D. & Barker, Kash & Morshedlou, Nazanin, 2020. "Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    • Handle: RePEc:eee:reensy:v:199:y:2020:i:c:s0951832019308191
    DOI: 10.1016/j.ress.2020.106907
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    13. Bellè, Andrea & Abdin, Adam F. & Fang, Yi-Ping & Zeng, Zhiguo & Barros, Anne, 2023. "A data-driven distributionally robust approach for the optimal coupling of interdependent critical infrastructures under random failures," European Journal of Operational Research, Elsevier, vol. 309(2), pages 872-889.
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    19. Moglen, Rachel L. & Barth, Julius & Gupta, Shagun & Kawai, Eiji & Klise, Katherine & Leibowicz, Benjamin D., 2023. "A nexus approach to infrastructure resilience planning under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    20. Han, Lin & Zhao, Xudong & Chen, Zhilong & Gong, Huadong & Hou, Benwei, 2021. "Assessing resilience of urban lifeline networks to intentional attacks," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    21. Li, Qing & Li, Mingchu & Gong, Zhongqiang & Tian, Yuan & Zhang, Runfa, 2022. "Locating and protecting interdependent facilities to hedge against multiple non-cooperative limited choice attackers," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    22. Jiangbin Zhao & Zaoyan Zhang & Mengtao Liang & Xiangang Cao & Zhiqiang Cai, 2023. "Start-Up Strategy-Based Resilience Optimization of Onsite Monitoring Systems Containing Multifunctional Sensors," Mathematics, MDPI, vol. 11(19), pages 1-18, September.

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