Comparison of neural networks for solving the travelling salesman problem

The TSP deals with finding a shortest path through a number of cities. This seemingly simple problem is hard to solve because of the amount of possible solutions. Which is why methods that give a good suboptimal solution in a reasonable time are generally used. In this paper three methods were compa...

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Bibliographic Details
Published in:2012 11th Symposium on Neural Network Applications in Electrical Engineering pp. 21 - 24
Main Authors: La Maire, B. F. J., Mladenov, V. M.
Format: Conference Proceeding
Language:English
Published: IEEE 01.09.2012
Subjects:
Biological neural networks
Cities and towns
Hopfield Neural Network
Integer Programming
Kohonen Self Organizing Feature Map Neural Network
Linear programming
Neurons
Organizing
Traveling Salesman Problem
Traveling salesman problems
ISBN:9781467315692, 1467315699
Online Access:Get full text
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Summary:The TSP deals with finding a shortest path through a number of cities. This seemingly simple problem is hard to solve because of the amount of possible solutions. Which is why methods that give a good suboptimal solution in a reasonable time are generally used. In this paper three methods were compared with respect to quality of solution and ease of finding correct parameters: the Integer Linear Programming method, the Hopfield Neural Network, and the Kohonen Self Organizing Feature Map Neural Network.
ISBN:9781467315692
1467315699
DOI:10.1109/NEUREL.2012.6419953