A Self-Organizing Neural Network for the Traveling Salesman Problem That Is Competitive with Simulated Annealing-Reference-Cited by-同舟云学术

A Self-Organizing Neural Network for the Traveling Salesman Problem That Is Competitive with Simulated Annealing

Published:1996-02-15 Issue:2 Volume:8 Page:416-424
ISSN:0899-7667
Container-title:Neural Computation
language:en
Short-container-title:Neural Computation

Author:

Budinich Marco¹

Affiliation:

1. Center for Neural Networks, Kings's College London, London, U.K.

Abstract

Unsupervised learning applied to an unstructured neural network can give approximate solutions to the traveling salesman problem. For 50 cities in the plane this algorithm performs like the elastic net of Durbin and Willshaw (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.

Publisher

MIT Press - Journals

Subject

Cognitive Neuroscience,Arts and Humanities (miscellaneous)

Link

https://www.mitpressjournals.org/doi/pdf/10.1162/neco.1996.8.2.416

Reference9 articles.

1. Self-organizing feature maps and the travelling salesman problem

2. On the Ordering Conditions for Self-Organizing Maps

3. An analogue approach to the travelling salesman problem using an elastic net method

4. Self-organizing maps: ordering, convergence properties and energy functions

5. A study of the application of Kohonen-type neural networks to the Travelling Salesman Problem

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