A “cellular neuronal” approach to optimization problems
Gregory S. Duane · Chaos An Interdisciplinary Journal of Nonlinear Science · 2009
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.