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Optimizing large-scale problems by combining chaotic neural network and self-organizing feature map

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3 Author(s)
Xiu-Hong Wang ; Inst. of Syst. Eng., Tianjin Univ., China ; Qing-Li Qiao ; Zheng-Ou Wang

A novel approach using transient chaotic neural network (TCNN) and self-organizing feature map (SOFM) process to solve large-scale combinatorial optimization problems has been proposed. With the clustering function of self-organizing feature map, the computational cost of a large-scale combinatorial optimization problem solved by TCNN is reduced. Numerical simulation of TSP shows that the proposed method is effective to solve large-scale optimization problems.

Published in:

Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on  (Volume:6 )

Date of Conference:

26-29 Aug. 2004