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Infrastructure System Restoration Planning Using Evolutionary Algorithms
Author(s) -
Corns Steven,
Long Suzanna,
Shoberg Tom
Publication year - 2016
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2016.00272.x
Subject(s) - evolutionary algorithm , interdependence , computer science , greedy algorithm , scale (ratio) , operations research , algorithm , engineering , geography , artificial intelligence , cartography , political science , law
This paper presents an evolutionary algorithm to address restoration issues for supply chain interdependent critical infrastructure. Rapid restoration of infrastructure after a large‐scale disaster is necessary to sustaining a nation's economy and security, but such long‐term restoration has not been investigated as thoroughly as initial rescue and recovery efforts. A model of the Greater Saint Louis Missouri area was created and a disaster scenario simulated. An evolutionary algorithm is used to determine the order in which the bridges should be repaired based on indirect costs. Solutions were evaluated based on the reduction of indirect costs and the restoration of transportation capacity. When compared to a greedy algorithm, the evolutionary algorithm solution reduced indirect costs by approximately 12.4% by restoring automotive travel routes for workers and re‐establishing the flow of commodities across the three rivers in the Saint Louis area.