Summary
International Symposium on Nonlinear Theory and its Applications
2010
Session Number:B2L-A
Session:
Number:B2L-A2
Realizing Ideal Chaotic Dynamics for Combinatorial Optimization using a Spatiotemporal Filter
Mikio Hasegawa,
pp.289-292
Publication Date:2010/9/5
Online ISSN:2188-5079
Summary:
This paper proposes an optimization algorithm, which utilizes the most stable spatiotemporal chaotic dynamics for solution search in a high dimensional space. Such chaotic dynamics is generated by a FIR filter, which has been applied to the chaotic CDMA in previous researches to minimize the cross-correlation among the sequences. In the proposed method, such filters are introduced at the output of decision functions of combinatorial optimization algorithms to realize an ideal chaotic search, which generates ideally complicated searching dynamics. In this paper, the proposed scheme is applied to two combinatorial optimization approaches, the Hopfield-Tank neural network with additive noise and a heuristic algorithm based on the neighboring solution search, which solve the Traveling Salesman Problems and the Quadratic Assignment Problems. Simulation results show that the proposed approach using the ideal chaotic dynamics simply improves the performance of the chaotic algorithms without searching appropriate parameter values even for large-scale problems.