Optimization of Travelling Salesman Problem Using Genetic Algorithm and Fuzzy C-Means Clustering

Travelling Salesman Problem (TSP) is one of the most intensively studied optimization problems in computer science and some other areas. It is expected that the optimum tour is completed with the minimum cost by salesman. In this study, a hybrid system is developed composed of two methods Genetic Algorithms and Fuzzy C-Means Clustering for solving TSP. The aim in selecting TSP is that it can be applied in real world as well as adaptive applications. In our method, the cities according to their membership functions are divided into several clusters by the Fuzzy C-Means Clustering method. Therefore, an appropriate form of a populati on in the genetic algorithm is provided. The performances of both proposed method and classical genetic algorithm are obtained and compared. In the conclusion of the paper, some experimental results are provided to i l lustrate the effectiveness of the approach