Genetic Algorithms for Agent-Based Infrastructure Interdependency Modeling and Analysis

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Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, electric power, telecommunication, and financial networks. This paper describes initial research combining agent-based infrastructure modeling software and genetic algorithms (GAs) to help optimize infrastructure protection and restoration decisions. This research proposes to apply GAs to the problem of infrastructure modeling and analysis in order to determine the optimum assets to restore or protect from attack or other disaster. This research is just commencing and therefore the focus of this paper is the integration of a GA optimization method with a simulation through the ... continued below

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Permann, May March 1, 2007.

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Description

Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, electric power, telecommunication, and financial networks. This paper describes initial research combining agent-based infrastructure modeling software and genetic algorithms (GAs) to help optimize infrastructure protection and restoration decisions. This research proposes to apply GAs to the problem of infrastructure modeling and analysis in order to determine the optimum assets to restore or protect from attack or other disaster. This research is just commencing and therefore the focus of this paper is the integration of a GA optimization method with a simulation through the simulation’s agents.

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  • SpringSim 2007,Norfolk, VA,03/25/2007,03/29/2007

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  • Report No.: INL/CON-07-12317
  • Grant Number: DE-AC07-99ID-13727
  • Office of Scientific & Technical Information Report Number: 915522
  • Archival Resource Key: ark:/67531/metadc878514

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  • March 1, 2007

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  • Sept. 22, 2016, 2:13 a.m.

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  • Dec. 5, 2016, 4:48 p.m.

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Permann, May. Genetic Algorithms for Agent-Based Infrastructure Interdependency Modeling and Analysis, article, March 1, 2007; [Idaho Falls, Idaho]. (digital.library.unt.edu/ark:/67531/metadc878514/: accessed September 23, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.