Abstract
The Traveling Salesman Problem is one of the most intensively studied problems in computational mathematics. Due to the basic genetic algorithm convergence speed is slow, easy to stagnation. We present in this paper a new improved mutation strategy to solve this problem. Roulette wheel selection strategy is used to avoid running into trap of the part best value. And simulated niche method is introduced to accelerate the search process effetively. This algorithm has been checked on a set of 144 cities in China and it outperforms the results obtained with other TSP heuristic methods.
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