• DocumentCode
    276567
  • Title

    Solving the assignment problem with statistical physics

  • Author

    Kosowsky, J.J. ; Yuille, A.L.

  • Author_Institution
    Div. of Appl. Sci., Harvard Univ., Cambridge, MA, USA
  • Volume
    i
  • fYear
    1991
  • fDate
    8-14 Jul 1991
  • Firstpage
    159
  • Abstract
    Proposes a novel method for solving the assignment problem using techniques adapted from statistical physics. The authors derive a convex effective energy function whose unique minimum corresponds to the optimal assignment. Steepest descent results in a continuous time dynamical system which is guaranteed to converge arbitrarily close to the optimal solution. This algorithm has an appealing economic interpretation and interesting connections to the discrete auction algorithm proposed by D.P. Bertsekas (1990)
  • Keywords
    convergence; minimisation; statistical mechanics; assignment problem; bipartite weighted matching problem; continuous time dynamical system; convergence; convex effective energy function; discrete auction algorithm; economic interpretation; minimum; statistical physics; steepest descent; Annealing; Biological neural networks; Ducts; Heuristic algorithms; Iterative algorithms; Iterative methods; Physics; Polynomials; Power generation economics; Tin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-0164-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.155168
  • Filename
    155168