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
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