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    Interdependent network restoration: On the value of information-sharing
    (Elsevier Science BV, 2015-07-01) Sharkey, Thomas C.; Çavdaroğlu, Burak; Nguyen, Huy; Holman, Jonathan; Mitchell, John E. M.; Wallace, William Al
    We consider restoring multiple interdependent infrastructure networks after a disaster damages components in them and disrupts the services provided by them. Our particular focus is on interdependent infrastructure restoration (IIR) where both the operations and the restoration of the infrastructures are linked across systems. We provide new mathematical formulations of restoration interdependencies in order to incorporate them into an interdependent integrated network design and scheduling (IINDS) problem. The IIR efforts resulting from solving this IINDS problem model a centralized decision-making environment where a single decision-maker controls the resources of all infrastructures. In reality, individual infrastructures often determine their restoration efforts in an independent, decentralized manner with little communication among them. We provide algorithms to model various levels of decentralization in IIR efforts. These algorithms are applied to realistic damage scenarios for interdependent infrastructure systems in order to determine the loss in restoration effectiveness resulting from decentralized decision-making. Our computational tests demonstrate that this loss can be greatly mitigated by having infrastructures share information about their planned restoration efforts.
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    MUNICIPAL: A decision technology for the restoration of critical infrastructures
    (Institute of Industrial Engineers, 2013) Loggins, Ryan A.; Wallace, William Al; Çavdaroğlu, Burak
    This paper describes the decision technology MUNICIPAL (Multi-Network Interdependent Critical Infrastructure Program for the Analysis of Lifelines). This technology supports decision makers in the restoration of critical infrastructure systems after an extreme event. MUNICIPAL consists of four components: a vulnerability simulator which predicts damage to infrastructure components given a specific disaster scenario, an optimization module which produces a restoration plan given a damage scenario, a GIS interface to visualize and manipulate the data, and a database structured to support the data needs and integration of the other three modules. A case study was developed with the emergency management department of New Hanover County, North Carolina, to assess the technology with respect to the impact of a hurricane.