Unsupervised learning applied to an unstructured neural network can give approximate solutions to the travelling salesman problem. For 50 cities in the plane this algorithm performs like the elastic net of Durbin and Willshaw [Durbin 1987] and it improves when increasing the number of cities to get better than simulated annealing for problems with more than 500 cities. In all the tests this algorithm requires a fraction of the time taken by simulated annealing.

A Self-Organising Neural Network for the Travelling Salesman Problem that is Competitive with Simulated Annealing

BUDINICH, MARCO
1996

Abstract

Unsupervised learning applied to an unstructured neural network can give approximate solutions to the travelling salesman problem. For 50 cities in the plane this algorithm performs like the elastic net of Durbin and Willshaw [Durbin 1987] and it improves when increasing the number of cities to get better than simulated annealing for problems with more than 500 cities. In all the tests this algorithm requires a fraction of the time taken by simulated annealing.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2559057
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