遗传算法是基于达尔文进化论的一种智能优化算法,一种可用于复杂系统优化的具有鲁棒性的搜索算法，适用于解决传统方法难以解决的复杂的、非线性问题，可广泛应用于组合优化、离散优化、工程优化等领域。旅行商问题是一种NP难的组合优化问题，具有重要的理论研究价值和实际应用背景。然而，传统遗传算法中存在有不足，需要提出新的改进的遗传算法，并应用于旅行商问题的求解。-Genetic algorithm is based on Darwin' s theory of evolution of an intelligent optimization algorithm, a complex system can be used to optimize the robustness of the search algorithm, the application of traditional methods to solve difficult and complex, nonlinear problems, can be widely used in combination optimization, discrete optimization, engineering, optimization and other fields. Traveling Salesman Problem is a NP hard combinatorial optimization problem, has important theoretical value and practical application of research background. However, the traditional genetic algorithm, there is less than the need to introduce new improved genetic algorithm, and applied for solving the traveling salesman problem.