• DocumentCode
    3062669
  • Title

    The Regularized Newton Method for Multiobjective Optimization

  • Author

    Wang, Zhijie ; Liu, Sanming

  • Author_Institution
    Sch. of Electr. Eng., Shanghai Dianji Univ., Shanghai, China
  • fYear
    2012
  • fDate
    23-26 June 2012
  • Firstpage
    394
  • Lastpage
    398
  • Abstract
    In this paper, we introduce the regularized Newton method for multiobjective optimization. The method does not scalarize the original multiobjective optimization problem. For any vector convex function, with a compact level set, the regularized Newton method generates a sequence that converges to the optimal points from any starting point. Moreover the regularized Newton method does not require strong convexity property in the entire space.
  • Keywords
    Newton method; convex programming; vectors; multiobjective optimization; regularized Newton method; vector convex function; Convergence; Convex functions; Educational institutions; Level set; Newton method; Optimization; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization (CSO), 2012 Fifth International Joint Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4673-1365-0
  • Type

    conf

  • DOI
    10.1109/CSO.2012.94
  • Filename
    6274753