对旅行商(TSP)问题设计了一个新的遗传算法.首先,对n个城市的旅行商问题设计了一个新的编码方法,并且对这种编码方法,给出了简便的解码方法.其次,针对编码的特点,设计了一种新的、有效的杂交算子和变异算子,这些算子均能直接产生可行的后代.为提高杂交算子的搜索能力,结合了一个局部搜索技术来改进杂交算子.在此基础上,提出了求解TSP的一个新的遗传算法,并证明了其全局收敛性.为了验证算法的有效性,对10个国际标准算例(城市规模从14到1000)进行了计算机仿真,结果表明算法是有效的. A new genetic algorithm is designed for the Traveling Salesman (TSP) problem.Firstly, a new encoding method is designed for the n-city traveling salesman problem, and a simple decoding method is given for this encoding method.Secondly, Aiming at the characteristics of coding, a new and effective crossover operator and mutation operator are designed, which can directly generate feasible descendants.In order to improve the searching ability of hybrid operators, a local search technique is used to improve Based on this, a new genetic algorithm for solving TSP is proposed and its global convergence is proved.In order to verify the validity of the algorithm, 10 international standard examples (urban scale from 14 to 1000) Computer simulation results show that the algorithm is effective.