Applying 3D printing and genetic algorithm-generated anticipatory system dynamics models to a homeland security challenge

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{North:2015:WSC,
  author =       "Michael J. North and Pam Sydelko and 
                 Ignacio Martinez-Moyano",
  booktitle =    "2015 Winter Simulation Conference (WSC)",
  title =        "Applying {3D} printing and genetic algorithm-generated
                 anticipatory system dynamics models to a homeland
                 security challenge",
  year =         "2015",
  pages =        "2511--2522",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7408361",
  DOI =          "doi:10.1109/WSC.2015.7408361",
  abstract =     "In this paper we apply 3D printing and genetic
                 algorithm-generated anticipatory system dynamics models
                 to a homeland security challenge, namely understanding
                 the interface between transnational organized criminal
                 networks and local gangs. We apply 3D printing to
                 visualize the complex criminal networks involved. This
                 allows better communication of the network structures
                 and clearer understanding of possible interventions. We
                 are applying genetic programming to automatically
                 generate anticipatory system dynamics models. This will
                 allow both the structure and the parameters of system
                 dynamics models to evolve. This paper reports the
                 status of work in progress. This paper builds on
                 previous work that introduced the use of genetic
                 programs to automatically generate system dynamics
                 models. This paper's contributions are that it
                 introduces the use of 3D printing techniques to
                 visualize complex networks and that it presents in more
                 detail our emerging approach to automatically
                 generating anticipatory system dynamics in weakly
                 constrained, data-sparse domains.",
  notes =        "Also known as \cite{7408361}",
}

Genetic Programming entries for Michael J North Pam Sydelko Ignacio Martinez-Moyano

Citations