A "cellular neuronal" approach to optimization problems.
The Hopfield-Tank [J. J. Hopfield and D. W. Tank, Biol. Cybern. 52, 141 (1985)] recurrent neural network architecture for the traveling salesman problem is generalized to a fully interconnected "cellular" neural network of regular oscillators. Tours are defined by synchronization patterns, allowing the simultaneous representation of all cyclic permutations of a given tour. The network converges to local optima some of which correspond to shortest-distance tours, as can be shown analytically in a stationary phase approximation. Simulated annealing is required for global optimization, but the stochastic element might be replaced by chaotic intermittency in a further generalization of the architecture to a network of chaotic oscillators.
Duane
Gregory S
GS
National Center for Atmospheric Research, Boulder, Colorado 80307, USA. gregory.duane@colorado.edu
D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001683:Biological Clocks / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D009991:Oscillometry / Q000379:methods; D009435:Synaptic Transmission / Q000502:physiology*