Application of Neuro-Fuzzy system to solve Traveling Salesman Problem
This paper presents the application of adaptive neuro-fuzzy inference system (ANFIS) in solving the traveling salesman problem. Takagi-Sugeno-Kang neuro-fuzzy architecture model is used for this purpose. TSP, although, simple to describe & mathematically well characterized, is quite difficult to solve. TSP is called a NP-Hard problem, i.e. this problem is as hard as the hardest problem in NP-Complete space. Training of fuzzy system was performed by a hybrid Back-Propagation (BP) and Least-Mean-Square (LMS) algorithm and for optimizing the number of fuzzy rules, subtractive-clustering algorithm was utilized. Then the ANFIS was tested against a number of training data samples. More accurate and quick results were obtained by using ANFIS.