Competitive percolation strategies for network recovery
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by
Andrew M. Smith, Márton Pósfai, Martin Rohden, Andrés D.
Gonzáles, Leonardo Dueńas-Osorio, Raissa M. D'Souza
2019
Abstract
Restoring operation of critical infrastructure systems after catastrophic
events is an important issue, inspiring work in multiple fields, including
network science, civil engineering, and operations research. We consider the
problem of finding the optimal order of repairing elements in power grids and
similar infrastructure. Most existing methods either only consider system
network structure, potentially ignoring important features, or incorporate
component level details leading to complex optimization problems with limited
scalability. We aim to narrow the gap between the two approaches. Analyzing
realistic recovery strategies, we identify over- and undersupply penalties of
commodities as primary contributions to reconstruction cost, and we demonstrate
traditional network science methods, which maximize the largest connected
component, are cost inefficient. We propose a novel competitive percolation
recovery model accounting for node demand and supply, and network structure.
Our model well approximates realistic recovery strategies, suppressing growth
of the largest connected component through a process analogous to explosive
percolation. Using synthetic power grids, we investigate the effect of network
characteristics on recovery process efficiency. We learn that high structural
redundancy enables reduced total cost and faster recovery, however, requires
more information at each recovery step. We also confirm that decentralized
supply in networks generally benefits recovery efforts.
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