一种改进蚁群优化算法的仿真研究

针对蚁群优化算法存在容易陷入局部最优、收敛速度慢、参数设置复杂等缺点，提出了一种改进的蚁群优化算法，研究了伪随机比例转移规则中参数 的取值方法，并对信息素的取值方式和信息素的更新规则进行了改进。最后以中国31个城市的旅行商问题和路径规划问题为实例，分别运用改进前后的蚁群算法进行了仿真研究。仿真结果表明：改进之后的算法不仅能够得到更好的解，更能显著地提高算法的收敛速度。

Simulation Research with an Improved Ant Colony Algorithm

In order to solve some defects of the ant colony optimization such as easily to fall into local optimum, slowly to converge and difficultly to set parameters, this paper puts forward an improved ant colony algorithm. The method of valuing that is a parameter of the pseudo-random proportional transition rule is studied. The method of valuing pheromones and the update rule of the pheromones are improved in this paper. The simulation experiments with the improved ant colony optimization about traveling salesman problem （TSP） of CHN-31 and route planning problem are conducted. The simulation results show that the improved algorithm is not only able to get a better solution, but also can significantly improve the convergence speed.