Using genetic algorithms in chem-bio defense applications

Sue Ellen Haupt; Randy L. Haupt; George S. Young

doi:10.1109/BLISS.2007.41

Using genetic algorithms in chem-bio defense applications

Sue Ellen Haupt, Randy L. Haupt, George S. Young

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

There are many problems in Security and Defense that require a robust optimization technique, including those that involve the release of a chemical or biological contaminant. This paper discusses using a genetic algorithm for addressing such problems. An example is given how a mixed integer genetic algorithm can be used in conjunction with field sensor data to invert for source information and all necessary meteorological data. A new mixed integer genetic algorithm is described that is a state-of-the-art tool capable of optimizing a wide range of objective functions. Such an algorithm is useful for optimizing atmospheric stability, wind speed, wind direction, and source location. We demonstrate that the algorithm is successful at reconstructing these source and meteorological parameters.

Original language	English (US)
Title of host publication	Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007
Pages	151-154
Number of pages	4
DOIs	https://doi.org/10.1109/BLISS.2007.41
State	Published - 2007
Event	2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007 - Edinburgh, United Kingdom Duration: Aug 9 2007 → Aug 10 2007

Publication series

Name	Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007

Other

Other	2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007
Country/Territory	United Kingdom
City	Edinburgh
Period	8/9/07 → 8/10/07

All Science Journal Classification (ASJC) codes

Information Systems
Information Systems and Management
Control and Systems Engineering

Access to Document

10.1109/BLISS.2007.41

Cite this

Haupt, S. E., Haupt, R. L., & Young, G. S. (2007). Using genetic algorithms in chem-bio defense applications. In Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007 (pp. 151-154). Article 4290958 (Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007). https://doi.org/10.1109/BLISS.2007.41

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title = "Using genetic algorithms in chem-bio defense applications",

abstract = "There are many problems in Security and Defense that require a robust optimization technique, including those that involve the release of a chemical or biological contaminant. This paper discusses using a genetic algorithm for addressing such problems. An example is given how a mixed integer genetic algorithm can be used in conjunction with field sensor data to invert for source information and all necessary meteorological data. A new mixed integer genetic algorithm is described that is a state-of-the-art tool capable of optimizing a wide range of objective functions. Such an algorithm is useful for optimizing atmospheric stability, wind speed, wind direction, and source location. We demonstrate that the algorithm is successful at reconstructing these source and meteorological parameters.",

author = "Haupt, {Sue Ellen} and Haupt, {Randy L.} and Young, {George S.}",

year = "2007",

doi = "10.1109/BLISS.2007.41",

language = "English (US)",

isbn = "0769529194",

series = "Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007",

pages = "151--154",

booktitle = "Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007",

note = "2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007 ; Conference date: 09-08-2007 Through 10-08-2007",

}

Haupt, SE, Haupt, RL & Young, GS 2007, Using genetic algorithms in chem-bio defense applications. in Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007., 4290958, Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007, pp. 151-154, 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007, Edinburgh, United Kingdom, 8/9/07. https://doi.org/10.1109/BLISS.2007.41

Using genetic algorithms in chem-bio defense applications. / Haupt, Sue Ellen; Haupt, Randy L.; Young, George S.
Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007. 2007. p. 151-154 4290958 (Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - There are many problems in Security and Defense that require a robust optimization technique, including those that involve the release of a chemical or biological contaminant. This paper discusses using a genetic algorithm for addressing such problems. An example is given how a mixed integer genetic algorithm can be used in conjunction with field sensor data to invert for source information and all necessary meteorological data. A new mixed integer genetic algorithm is described that is a state-of-the-art tool capable of optimizing a wide range of objective functions. Such an algorithm is useful for optimizing atmospheric stability, wind speed, wind direction, and source location. We demonstrate that the algorithm is successful at reconstructing these source and meteorological parameters.

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Haupt SE, Haupt RL, Young GS. Using genetic algorithms in chem-bio defense applications. In Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007. 2007. p. 151-154. 4290958. (Proceedings - 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007). doi: 10.1109/BLISS.2007.41

Using genetic algorithms in chem-bio defense applications

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