Year: 2009
Type: article
Abstract: 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.
DOI: 10.1063/1.3184829
Author: Gregory S. Duane
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W2088565648