Fast combinatorial optimization with parallel digital computers

Authors:
H. Kakeya;Y. Okabe
Affiliations:
Commun. Res. Lab., Minist. of Posts & Telecommun., Tokyo, Japan;-
Venue:
IEEE Transactions on Neural Networks
Year:
2000

Citing 0
Cited 1

The modified Hopfield architecture applied in dynamic programming problems and bipartite graph optimization

International Journal of Hybrid Intelligent Systems - VIII Brazilian Symposium On Neural Networks

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Abstract

This paper presents an algorithm which realizes fast search for the solutions of combinatorial optimization problems with parallel digital computers. With the standard weight matrices designed for combinatorial optimization, many iterations are required before convergence to a quasioptimal solution even when many digital processors can be used in parallel. By removing the components of the eigenvectors with eminent negative eigenvalues of the weight matrix, the proposed algorithm avoids oscillation and realizes energy reduction under synchronous discrete dynamics, which enables parallel digital computers to obtain quasi-optimal solutions with much less time than the conventional algorithm.