Interdependent network restoration: On the value of information-sharing

Thomas C. Sharkey; Burak Cavdaroglu; Huy Nguyen; Jonathan Holman; John E. Mitchell; William A. Wallace

doi:10.1016/j.ejor.2014.12.051

Interdependent network restoration: On the value of information-sharing

Thomas C. Sharkey, Burak Cavdaroglu, Huy Nguyen, Jonathan Holman, John E. Mitchell, William A. Wallace

Research output: Contribution to journal › Article › peer-review

77 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	309-321
Number of pages	13
Journal	European Journal of Operational Research
Volume	244
Issue number	1
Early online date	6 Jan 2015
DOIs	https://doi.org/10.1016/j.ejor.2014.12.051
Publication status	Published - 1 Jul 2015
Externally published	Yes

Bibliographical note

Funding Information:
The work of Thomas Sharkey was supported in part by the U.S. National Science Foundation under grant number CMMI-1254258. The work of Thomas Sharkey, John Mitchell, and William Wallace was supported in part by the U.S. National Science Foundation under grant number CMMI-1314350. The work of Burak Cavdaroglu and William Wallace was supported by the U.S. Department of Homeland Security under award number 2008-ST-061-ND 0001 . The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Department of Homeland Security.

Publisher Copyright:
© 2015 Elsevier B.V. All rights reserved.

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title = "Interdependent network restoration: On the value of information-sharing",

abstract = "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.",

author = "Sharkey, {Thomas C.} and Burak Cavdaroglu and Huy Nguyen and Jonathan Holman and Mitchell, {John E.} and Wallace, {William A.}",

note = "Funding Information: The work of Thomas Sharkey was supported in part by the U.S. National Science Foundation under grant number CMMI-1254258. The work of Thomas Sharkey, John Mitchell, and William Wallace was supported in part by the U.S. National Science Foundation under grant number CMMI-1314350. The work of Burak Cavdaroglu and William Wallace was supported by the U.S. Department of Homeland Security under award number 2008-ST-061-ND 0001 . The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Department of Homeland Security. Publisher Copyright: {\textcopyright} 2015 Elsevier B.V. All rights reserved.",

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N2 - 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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Interdependent network restoration: On the value of information-sharing

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