• DocumentCode
    2995934
  • Title

    Multiple single objective Pareto sampling

  • Author

    Hughes, Evan J.

  • Author_Institution
    Dept. of Aerosp., Power & Sensors, Cranfield Univ., England, UK
  • Volume
    4
  • fYear
    2003
  • fDate
    8-12 Dec. 2003
  • Firstpage
    2678
  • Abstract
    We detail a new nonPareto evolutionary multiobjective algorithm, multiple single objective Pareto sampling (MSOPS), that performs a parallel search of multiple conventional target vector based optimisations, e.g. weighted min-max. The method can be used to generate the Pareto set and analyse problems with large numbers of objectives. The method allows bounds and discontinuities of the Pareto set to be identified and the shape of the surface to be analysed, despite not being able to visualise the surface easily. A new combination metric is also introduced that allows the shape of the objective surface that gives rise to discontinuities in the Pareto surface to be analysed easily.
  • Keywords
    Pareto optimisation; evolutionary computation; sampling methods; search problems; Pareto set; Pareto surface; combination metric; evolutionary multiobjective algorithm; multiple single objective Pareto sampling; parallel search; target vector based optimizations; Algorithm design and analysis; Educational institutions; Evolutionary computation; Pareto analysis; Pareto optimization; Sampling methods; Shape; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
  • Print_ISBN
    0-7803-7804-0
  • Type

    conf

  • DOI
    10.1109/CEC.2003.1299427
  • Filename
    1299427