将局部优化算子引入遗传算法求解TSP问题，以求提高算法的性能。具体措施是在标准遗传算法的最后阶段增加步，即对每代的最优个体进行一定次数的局部搜索，以求改善该最优个体。首先提出将反序一杂交法引入局部优化过程中。

同几种‘常用的局部优化力一法相比，反序一杂交法的性能最为突出。实验结果表明，该优化力一法能有效求解300个城市以内的

TSP问题。

-Will introduce a local optimization operator TSP problem genetic algorithm, in order to increase the performance of algorithm. Specific measures in the standard genetic algorithm to increase the final phase of step-by-step, that is optimal for each individual to carry out on behalf of a certain number of local search, in order to improve the best individual. First put forward the anti-sequence hybridization to introduce a local optimization process. With several ' common edge of a local optimization method, the anti-sequence of a hybridization of the most outstanding performance. Experimental results show that the optimization method can effectively force a solution of 300 cities within the TSP problem.