IEEJ Transactions on Electronics, Information and Systems
Online ISSN : 1348-8155
Print ISSN : 0385-4221
ISSN-L : 0385-4221
An Improvement of Algorithm using Kohonen's Self-Organizing Feature Map for the Traveling Salesman Problem
Kikuo FUJIMURAHeizo TOKUTAKAYasuhiro OHSHIMAShin-ichi TANAKASatoru KISHIDA
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1996 Volume 116 Issue 3 Pages 350-358

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Abstract
The Traveling Salesman Problem (TSP) is well known as one of the combinatorial optimization problem. In 1988, Angeniol et al. first applied Kohonen's Self Organizing feature Map (SOM) to the TSP. They demonstrated that the practical solutions (sub-optimal tour) were obtained by their proposed method in sufficiently short time compared with conventional methods;e.g. Hopfield Network, Simulated Annealing, Genetic Algorithm (GA) and Chaos Neural Network. In this paper, we have improved Angeniol's method to reduce the calculating time by the following modifications of (1) optimization of node creation timing and (2) adding a momentum effect for the update factor. Using the best combination of the several parameters in the modified method, we confirm that the modified method can be take just one fourth time compared with original method to solve the squarely located 36 cities TSP. Finally, we illustrate that the 200 cities TSP can be solved about one minute using our method on the personal computer.
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© The Institute of Electrical Engineers of Japan
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