• DocumentCode
    3374302
  • Title

    Optimal computing budget allocation for small computing budgets

  • Author

    LaPorte, G.J. ; Branke, Jurgen ; Chun-Hung Chen

  • Author_Institution
    George Mason Univ., Fairfax, VA, USA
  • fYear
    2012
  • fDate
    9-12 Dec. 2012
  • Firstpage
    1
  • Lastpage
    13
  • Abstract
    In this paper, we develop an optimal computing budget allocation (OCBA) algorithm for selecting a subset of designs under the restriction of an extremely small computing budget. Such an algorithm is useful in population based Evolutionary Algorithms (EA) and other applications that seek an elite subset of designs.
  • Keywords
    budgeting; evolutionary computation; OCBA algorithm; design subset; evolutionary algorithms-based population; extremely small computing budget; optimal computing budget allocation; Algorithm design and analysis; Computational modeling; Current measurement; Educational institutions; Resource management; Sociology; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference (WSC), Proceedings of the 2012 Winter
  • Conference_Location
    Berlin
  • ISSN
    0891-7736
  • Print_ISBN
    978-1-4673-4779-2
  • Electronic_ISBN
    0891-7736
  • Type

    conf

  • DOI
    10.1109/WSC.2012.6465085
  • Filename
    6465085
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3374302