29 March 1988 Synaptic Strengths For Neural Simulation Of The Traveling Salesman Problem
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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.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
W. I. Clement, R. M. Inigo, and E. S. McVey "Synaptic Strengths For Neural Simulation Of The Traveling Salesman Problem", Proc. SPIE 0937, Applications of Artificial Intelligence VI, (29 March 1988); doi: 10.1117/12.946996; https://doi.org/10.1117/12.946996


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