On the stability of the travelling salesman problem algorithm of Hopfield and Tank
Biological Cybernetics
Initial placement of gate arrays using least-squares methods
DAC '84 Proceedings of the 21st Design Automation Conference
Evolutionary algorithms for the physical design of VLSI circuits
Advances in evolutionary computing
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Hopfield decision neural nets have been claimed to be good for solving a class of optimization problems such as the traveling salesman's problem. A study was undertaken to determine if these techniques were applicable to the many optimization problems that occur in VLSI circuit design and layout. Module placement was chosen as a representative problem. It was observed that the convergence process closely resembles that of greedy hill climbing algorithms. Apart from the known problems of long simulation times and hardware implementation complexity, it was noted that the quality of solution was mediocre, at best, and highly sensitive to network parameters. Various modifications were attempted, none of which significantly improved the result. It is concluded that Hopfield neural nets do not, in their present form, provide an interesting solution to this class of CAD problems.