Management of interdependent infrastructure networks under disaster-related uncertainties

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2020-8

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Canbilen, Tuğçe

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During a disaster, multiple infrastructures such as power, water, or telecommunications networks may face disruptions in their services. Services of these infrastructures are vital in the aftermath of a disaster to facilitate search-and-rescue activities, relief transportation, and restoration efforts. Furthermore, the operations of these infrastructures may depend on receiving services from others, resulting in an interdependent network structure. In the aftermath of a disaster, damages on the network segments are observed and repair activities are scheduled accordingly. Repair activities need to be planned efficiently and in limited amount of time, taking into account the interdependencies between these networks. Reinforcement of network components prior to a disaster helps mitigate the amount of damage on the infrastructures and may play an important role in reducing the need for repairs in the aftermath of the disaster. On the other hand, reinforcement activities are costly and need to take into account uncertainties related to the effects of a potential disaster on the network. To integrate the pre-disaster reinforcement and post-disaster repair activities, the Stochastic Interdependent Infrastructure Reinforcement and Repair (SIIRR) problem is defined in this study. A scenario-based two-stage stochastic program is proposed to model the SIIRR problem, and a heuristic making use of the genetic algorithm and partial optimization is devised. The heuristic is then tested on realistic instances to observe its performance and make managerial inferences.

Subject Keywords

Humanitarian logistics, Interdependent infrastructures, Disaster management, Stochastic programming, Genetic algorithm

URI

https://hdl.handle.net/11511/69058

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

T. Canbilen, “Management of interdependent infrastructure networks under disaster-related uncertainties,” M.S. - Master of Science, Middle East Technical University, 2020.