• DocumentCode
    326327
  • Title

    MAAP: the military aircraft allocation planner

  • Author

    Abrahams, P. ; Balart, R. ; Byrnes, J.S. ; Cochran, D. ; Larkin, M.J. ; Moran, W. ; Ostheimer, G. ; Pollington, A.

  • Author_Institution
    Prometheus Inc., Newport, RI, USA
  • fYear
    1998
  • fDate
    4-9 May 1998
  • Firstpage
    336
  • Lastpage
    341
  • Abstract
    The authors present an application of genetic algorithms to the field of large-scale allocation problems in which a collection of resources (assets) must be mapped in an optimal or near-optimal manner to a number of objectives (targets), as measured by an objective function. Such problems are complex due to their requirements for integer solutions, non-linear objective functions and linear asset constraints. Genetic algorithms have turned out to be a natural fit for this application. They summarize the scope of the MAAP tool prototype as delivered to the U.S. Air Force and indicate their plans for ongoing and future research
  • Keywords
    genetic algorithms; military aircraft; planning; resource allocation; MAAP; US Air Force; genetic algorithm; integer solutions; large-scale allocation problems; linear asset constraints; military aircraft allocation planner; nonlinear objective functions; objective function; resources; Air traffic control; Asset management; Costs; Genetic algorithms; Large-scale systems; Military aircraft; Prototypes; Resource management; Software tools; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    0-7803-4869-9
  • Type

    conf

  • DOI
    10.1109/ICEC.1998.699755
  • Filename
    699755