• DocumentCode
    2178591
  • Title

    A new algorithm for minimizing convex functions over convex sets

  • Author

    Vaidya, Pravin M.

  • Author_Institution
    AT&T Bell Labs., Murray Hill, NJ, USA
  • fYear
    1989
  • fDate
    30 Oct-1 Nov 1989
  • Firstpage
    338
  • Lastpage
    343
  • Abstract
    An algorithm for minimizing a convex function over a convex set is given. The notion of a volumetric center of a polytope and a related ellipsoid of maximum volume inscribable in the polytope is central to the algorithm. The algorithm has a much better rate of global convergence than the ellipsoid algorithm. A by-product of the algorithm is an algorithm for solving linear programming problems that performs a total of O(mn2L+M(n )nL) arithmetic operations in the worst case, where m is the number of constraints, n the number of variables, and L a certain parameter. This gives an improvement in the time complexity of linear programming for m>n2
  • Keywords
    computational complexity; linear programming; convex functions; global convergence; linear programming; polytope; related ellipsoid; time complexity; volumetric center; Computational efficiency; Convergence; Ellipsoids; Iterative algorithms; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Foundations of Computer Science, 1989., 30th Annual Symposium on
  • Conference_Location
    Research Triangle Park, NC
  • Print_ISBN
    0-8186-1982-1
  • Type

    conf

  • DOI
    10.1109/SFCS.1989.63500
  • Filename
    63500