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
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;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155168