Electronic neural network for solving "traveling salesman" and s

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395 24, G06F 1546, G06G 712

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052553493

ABSTRACT:
This invention is a novel high-speed neural network based processor for solving the "traveling salesman" and other global optimization problems. It comprises a novel hybrid architecture employing a binary synaptic array whose embodiment incorporates the fixed rules of the problem, such as the number of cities to be visited. The array is prompted by analog voltages representing variables such as distances. The processor incorporates two interconnected feedback networks, each of which solves part of the problem independently and simultaneously, yet which exchange information dynamically.

REFERENCES:
patent: 4660166 (1987-04-01), Hopfield
patent: 4807168 (1989-02-01), Moopenn et al.
patent: 4931763 (1990-06-01), Ramesham et al.
Goldstein, M., N. Toomarian, and J. Barhen, 1988. "A Comparison Study of Optimization Methods of the Bipartite Matching Problem (BMP)". IEEE conf. Neural Networks II-267, San Diego, Calif., Jul. 24-27, 1988.
Hopfield, J. and D. Tank, 1985. "Neural Computation of Decisions in Optimization Problems". Biol. Cybern. 52:147-152.
Moopenn A., A. Thakoor, and T. Duong, 1988. "A Neural Network for Euclidean Distance Minimization". Proc. IEEE conf. Neural Network II-349 San Diego, Calif., Jul. 24-27, 1988.

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