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Cooperative co-evolutionary approach to optimize recovery for improving resilience in multi-communities

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  • Valcamonico, Dario
  • Sansavini, Giovanni
  • Zio, Enrico

Abstract

Communities around the world are showing to be still highly vulnerable to natural and man-made hazards. The increasing complexity and interconnectivity of the systems which make the lifeline of communities, has led to a strong emphasis on communities’ resilience. Recovery after disruptions is a key step for building the resilience of communities. This process is influenced by the allocation of resources from different communities and the choice between investments on infrastructure recovery or local emergency solutions. Therefore, the overall community resilience emerges from the coordinated decision-making among the impacted communities and from the trade-off between global and local investments. This work proposes a methodology for resilient recovery of interdependent infrastructure systems driven by multi-community decision making, sustained by a cooperative co-evolution approach to optimization. The methodology is deployed in a simulation model that constitutes a practical tool for restoration management.

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  • Valcamonico, Dario & Sansavini, Giovanni & Zio, Enrico, 2020. "Cooperative co-evolutionary approach to optimize recovery for improving resilience in multi-communities," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    • Handle: RePEc:eee:reensy:v:197:y:2020:i:c:s0951832019300675
    DOI: 10.1016/j.ress.2020.106800
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    Cited by:

    1. 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).
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