CAJ | 학술논문

针对最短路径问题TSP（Traveling Salesman Problem）的求解时，传统算法收敛慢，且求得的路径并不是所有行程的最短路径。提出用智能演化算法来求解，并对算法的演化算子进行改进和对各参数进行优化设置。结合10个城市和30个城市的仿真实例，分别进行传统算法、演化算法以及改进的演化算法进行对比。计算机仿真结果表明：改进后的演化算法收敛速度快，收敛精度高，鲁棒性好，寻求的最短路径明显优于传统算法。
침대최단로경문제TSP（Traveling Salesman Problem）적구해시，전통산법수렴만，차구득적로경병불시소유행정적최단로경。제출용지능연화산법래구해，병대산법적연화산자진행개진화대각삼수진행우화설치。결합10개성시화30개성시적방진실례，분별진행전통산법、연화산법이급개진적연화산법진행대비。계산궤방진결과표명：개진후적연화산법수렴속도쾌，수렴정도고，로봉성호，심구적최단로경명현우우전통산법。
When solving the shortest path problem (traveling salesman problem,TSP),traditional algorithm converges slowly,and the path derived is not the shortest path in all trips.Aiming at this issue,we propose to solve it with the intelligent evolutionary algorithm,and improve the evolution operator of the algorithm and make the optimisation setting on the parameters as well.In combination with 1 0 cities and using the simulation examples of 30 cities,we applied and compared the traditional algorithm,the evolutionary algorithm and the improved evolutionary algorithm on them respectively.It is shown by the computer simulation results that the improved evolutionary algorithm has fast convergence speed, high convergence precision and good robustness, the shortest path it found was obviously better than the traditional algorithm.