• DocumentCode
    2026270
  • Title

    On stockpile planning using a multi-objective genetic algorithm

  • Author

    Pall, Raman ; Cheung, Edward

  • Author_Institution
    Dept. of Nat. Defence, Defence R&D Canada, Ottawa, ON, Canada
  • fYear
    2011
  • fDate
    19-21 Sept. 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The North Atlantic Treaty Organization (NATO) Stockpile Planning Committee (SPC) periodically determines if NATO member nations have the necessary munitions for a full range of mission types, accomplished through the use of a model that minimizes the cost of the required stockpile. We were tasked to examine how the methodology of this model could be modified to allow individual nations to better determine their requirements for Precision-Guided Munitions (PGMs). The approach we undertook involves augmenting the methodology of the model with a multi-objective optimization approach using a genetic algorithm, in which the solution is optimized along two competing objectives: total cost (which is minimized), and the usage of PGMs (which is maximized). We recommended that the SPC consider including this change in all future versions of ACROSS.
  • Keywords
    genetic algorithms; military computing; NATO Stockpile Planning Committee; North Atlantic Treaty Organization; multiobjective genetic algorithm; multiobjective optimization; precision-guided munitions; stockpile planning; Analytical models; Genetic algorithms; Optimization; Planning; Software systems; Sorting; Weapons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Measurement Systems and Applications (CIMSA), 2011 IEEE International Conference on
  • Conference_Location
    Ottawa, ON, Canada
  • ISSN
    2159-1547
  • Print_ISBN
    978-1-61284-924-9
  • Type

    conf

  • DOI
    10.1109/CIMSA.2011.6059911
  • Filename
    6059911