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Infrastructure Resilience Conference 2018

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Resource Location for Interdependent Infrastructure Network Recovery: Optimization and Human-Based Computation Approaches

Critical infrastructure networks, such as electric power and water distribution, are not isolated from each other, but instead most of them rely on one another to be functional. In this work, we study the recovery problem of interdependent infrastructure networks following a disruption event, primarily determining the best location of recovery resources (e.g., equipment, daily starting positions for work crews) to expedite recovery. That is, this work addresses a variation of the facility location problem for interdependent infrastructure network recovery. We address the problem with two approaches and draw comparison between them: (i) through a traditional optimization problem, and (ii) through a human-based computing framework enabled with serious gaming. The proposed optimization model is a multi-objective mixed-integer programming model that seeks to minimize the total cost of recovery while maximizing the combined resilience of interdependent infrastructure networks. The human-based computing framework is a serious video game that enables players to evaluate instances of the problem and interactively propose solutions, and by aggregating the computation performed by players during the course of the game, an approximation of the solution is obtained. Results of these two approaches are provided, and a comparison between them is drawn for interdependent infrastructure networks of different sizes and topologies.

Yasser Almoghathawi
University of Oklahoma
United States

Luis Perez Estrada
Stevens Institute of Technology
United States

Kash Barker
University of Oklahoma
United States

Jose Ramirez-Marquez
Stevens Institute of Technology
United States

 

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