An Improved genetic algorithm for solving TSP

Abstract An improved genetic algorithm is proposed to solve the traveling salesman problem. On basis of traditional algorithm, greedy introduced initialize population. The parameters are adjusted adaptively from two aspects evolution algebra and individual fitness function value, which can speed up optimization prevent falling into local optimum. In mutation operation, adaptive used select operator improve quality variation search effect algorithm; after evolution, one-way evolutionary reversal operation chance inheriting parent genes, ability for optimal solution.