Toward Developing Genetic Algorithms to Aid in Critical Infrastructure Modeling

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Today’s society relies upon an array of complex national and international infrastructure networks such as transportation, telecommunication, financial and energy. Understanding these interdependencies is necessary in order to protect our critical infrastructure. The Critical Infrastructure Modeling System, CIMS©, examines the interrelationships between infrastructure networks. CIMS© development is sponsored by the National Security Division at the Idaho National Laboratory (INL) in its ongoing mission for providing critical infrastructure protection and preparedness. A genetic algorithm (GA) is an optimization technique based on Darwin’s theory of evolution. A GA can be coupled with CIMS© to search for optimum ways to protect infrastructure assets. ... continued below

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Creator: Unknown. May 1, 2007.

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Description

Today’s society relies upon an array of complex national and international infrastructure networks such as transportation, telecommunication, financial and energy. Understanding these interdependencies is necessary in order to protect our critical infrastructure. The Critical Infrastructure Modeling System, CIMS©, examines the interrelationships between infrastructure networks. CIMS© development is sponsored by the National Security Division at the Idaho National Laboratory (INL) in its ongoing mission for providing critical infrastructure protection and preparedness. A genetic algorithm (GA) is an optimization technique based on Darwin’s theory of evolution. A GA can be coupled with CIMS© to search for optimum ways to protect infrastructure assets. This includes identifying optimum assets to enforce or protect, testing the addition of or change to infrastructure before implementation, or finding the optimum response to an emergency for response planning. This paper describes the addition of a GA to infrastructure modeling for infrastructure planning. It first introduces the CIMS© infrastructure modeling software used as the modeling engine to support the GA. Next, the GA techniques and parameters are defined. Then a test scenario illustrates the integration with CIMS© and the preliminary results.

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  • 2007 IEEE Conference on Technologies for Homeland Security,Boston,05/16/2007,05/17/2007

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  • Report No.: INL/CON-07-12404
  • Grant Number: DE-AC07-99ID-13727
  • Office of Scientific & Technical Information Report Number: 915524
  • Archival Resource Key: ark:/67531/metadc887402

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  • May 1, 2007

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  • Sept. 22, 2016, 2:13 a.m.

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  • Dec. 9, 2016, midnight

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Toward Developing Genetic Algorithms to Aid in Critical Infrastructure Modeling, article, May 1, 2007; [Idaho Falls, Idaho]. (digital.library.unt.edu/ark:/67531/metadc887402/: accessed November 18, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.