Synaptic Strengths For Neural Simulation Of The Traveling Salesman Problem
W. I. Clement, Rafael M. Inigo, Eugene S. Mcvey · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1988
The use of neural-like networks to solve optimization problems such as the Traveling Salesman Problem has been proposed by Hopfield and Tank. The networks are based on a standard neuron which can be implemented by means of voltage amplifiers. The gain of network conductances and time constants as well as the value of constants in the problem's energy function have a decisive influence on the solution provided by the network, yet Hopfield and Tank do not make clear how to determine the value of these constants for a particular problem. In this paper a method for selection of constants is proposed which gives good results for the TSP. Instead of readjusting the gains and adding terms to the energy function until good results are obtained, the gains are chosen a priori and the energy function's original form is not altered. Simulation results are presented and discussed.