Comparison of neural networks for solving the travelling salesman problem

Author

La Maire, B.F.J. ; Mladenov, Valeri M.

Author_Institution

Dept. of Chem. Eng. & Chem., Eindhoven Univ. of Technol., Eindhoven, Netherlands

fYear

2012

fDate

20-22 Sept. 2012

Firstpage

21

Lastpage

24

Abstract

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.

Keywords

Hopfield neural nets; integer programming; linear programming; self-organising feature maps; travelling salesman problems; Hopfield neural network; Kohonen self organizing feature map neural network; TSP; integer linear programming method; travelling salesman problem; Biological neural networks; Cities and towns; Linear programming; Neurons; Organizing; Traveling salesman problems; Hopfield Neural Network; Integer Programming; Kohonen Self Organizing Feature Map Neural Network; Traveling Salesman Problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Network Applications in Electrical Engineering (NEUREL), 2012 11th Symposium on

Conference_Location

Belgrade

Print_ISBN

978-1-4673-1569-2

Type

conf

DOI

10.1109/NEUREL.2012.6419953

Filename

6419953