On the stability of the travelling salesman problem algorithm of Hopfield and Tank
Biological Cybernetics
Neural network methods in combinatorial optimization
Computers and Operations Research - Special issue on neural networks and operations research
Mapping combinatorial optimization problems onto neural networks
Information Sciences—Intelligent Systems: An International Journal
A New Technique for Optimization Problems in Graph Theory
IEEE Transactions on Computers
An Efficient Multivalued Hopfield Network for the Traveling Salesman Problem
Neural Processing Letters
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Neural techniques for combinatorial optimization with applications
IEEE Transactions on Neural Networks
“Optimal” Hopfield network for combinatorial optimization with linear cost function
IEEE Transactions on Neural Networks
A general methodology for designing globally convergent optimization neural networks
IEEE Transactions on Neural Networks
Design and analysis of maximum Hopfield networks
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
Some neural networks have been proposed as a model of computation for solving combinatorial optimization problems. The ability to solve interesting classic problems has motivated the use of neural networks as models for parallel computing. In this paper the degree of parallelism of a binary Hopfield network is studied using the chromatic number of the graph G associated to the network. We propose a rule to coloring the vertices of the neural network associated to the Traveling Salesman Problem such that the neurons with the same color can be simultaneously updated.