Infrastructure System Restoration Planning using Evolutionary Algorithms
Abstract
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.
Recommended Citation
S. Corns et al., "Infrastructure System Restoration Planning using Evolutionary Algorithms," Proceedings of the 26th Annual International Symposium of the International Council on Systems Engineering (2016, Edinburgh, Scotland), vol. 26, no. 1, pp. 1947 - 1956, Wiley, Jul 2016.
The definitive version is available at https://doi.org/10.1002/j.2334-5837.2016.00272.x
Meeting Name
26th Annual International Symposium of the International Council on Systems Engineering, INCOSE2016 (2016: Jul. 18-21, Edinburgh, Scotland)
Department(s)
Engineering Management and Systems Engineering
Research Center/Lab(s)
Intelligent Systems Center
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2016 Laboratory for Freeform Fabrication and University of Texas at Austin, All rights reserved.
Publication Date
21 Jul 2016
