A Study of the Traveling Salesman Problem Using Fuzzy Self Organizing Map

Kohonen self organizing map is an important artificial neural network technique that uses competitive, unsupervised learning to produce a low-dimensional discretized representation of the input space of the training samples which preserves the topological properties of the input space. The fuzzy set theory introduces the concept of membership function to the learning process of Self Organizing Map which helps to handle the inherent vagueness involved in most of the real life problems. In this paper, fuzzy self organizing map with one dimensional neighborhood is used to find an optimal solution for the symmetrical Traveling Salesperson Problem. The solution generated by the Fuzzy Self Organizing Map algorithm is improved by the 2opt algorithm. Finally, the Fuzzy Self Organizing Map algorithm is compared with Lin-Kerninghan Algorithm and Evolutionary Algorithm with Enhanced Edge Recombination operator and self-adapting mutation rate.

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