Abstract
The neural network method of Hopfield and Tank claims to be able to find nearly-optimum solutions for discrete optimization problems, e.g. the travelling salesman problem. In the present paper, an example is given which shows that the Hopfield-Tank algorithm systematically prefers certain solutions even if the energy values of these solutions are clearly higher than the energy of the global minimum.
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Kunz, D. Suboptimum solutions obtained by the Hopfield-Tank neural network algorithm. Biol. Cybern. 65, 129–133 (1991). https://doi.org/10.1007/BF00202388
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DOI: https://doi.org/10.1007/BF00202388