• DocumentCode
    2007431
  • Title

    Improved WTA problem solving method using a parallel genetic algorithm which applied the RMI initialization method

  • Author

    Sung-Sam Hong ; Jongmin Yun ; Bomin Choi ; Jonghwan Kong ; Myung-Mook Han

  • Author_Institution
    Dept. of Comput. Sci., Gachon Univ., Seongnam, South Korea
  • fYear
    2012
  • fDate
    20-24 Nov. 2012
  • Firstpage
    2189
  • Lastpage
    2193
  • Abstract
    The problem of Weapon Target Allocation (WTA) is to find an optimum solution, the type of vector that our weapons assign to targets, to minimize the damage of our assets from the target of an enemy offending us. we proposed the novel parallel genetic algorithm for solved to the WTA problem. The proposed. As the first step, our proposed algorithm is to expand the problem search space through the Random Mutation Inherit (RMI) population initialization method thereby improving convergence performance. We proposed an algorithm which obtains the WTA solution quickly and solves the WTA problem efficiently.
  • Keywords
    genetic algorithms; military computing; parallel algorithms; target tracking; weapons; RMI initialization method; WTA problem solving method; parallel genetic algorithm; random mutation inherit; weapon target allocation; Genetic Algorithm; Optimization; Parallel Process; Population Intialization; Weapon Assignment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
  • Conference_Location
    Kobe
  • Print_ISBN
    978-1-4673-2742-8
  • Type

    conf

  • DOI
    10.1109/SCIS-ISIS.2012.6505315
  • Filename
    6505315