• DocumentCode
    173164
  • Title

    A comparative study between using A*-search, Latin Hypercube and genetic algorithms in design of experiment for simulation of military operational plans

  • Author

    Schubert, Jeffrey ; Horling, Pontus

  • Author_Institution
    Dept. of Decision Support Syst., Swedish Defence Res. Agency, Stockholm, Sweden
  • fYear
    2014
  • fDate
    5-8 Oct. 2014
  • Firstpage
    365
  • Lastpage
    372
  • Abstract
    In this paper we compare three alternative ways of designing a data farming experiment for a military operational planning problem. In this multi-objective optimization problem the goal is to minimize two different measures of effectiveness. Military plans under consideration are evaluated by an event based simulation system. We compare three different approaches for selecting which plans should be simulated; A*-search, genetic algorithms and Latin Hypercube. The more robust Latin Hypercube approach is found to be the better approach for this application compared to the other two more focused approaches.
  • Keywords
    design of experiments; genetic algorithms; search problems; A*-search algorithm; Latin hypercube algorithm; data farming experiment design; design-of-experiment; effectiveness measure minimization; event-based simulation system; genetic algorithm; military operational plan simulation; military operational planning problem; multiobjective optimization problem; Analytical models; Computational modeling; Data models; Genetic algorithms; Hypercubes; Optimization; Planning; A*; Data farming; computer simulation; data analysis; decision support systems; design of experiment; effects-based approach to operations; genetic algorithms; nearly orthogonal nearly balanced hypercube; operational planning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • Type

    conf

  • DOI
    10.1109/SMC.2014.6973935
  • Filename
    6973935