摘要
针对蚁群算法在最优路径的选取和收敛速度方面的缺陷,提出了通过初始信息素分布和挥发信息素改进蚁群算法的新方法.首先初始信息素并根据全局路径重新设定,使得算法前期不再盲目搜索路径,进而加快算法的收敛速度;然后对信息素进行二次挥发以提高算法精度及后期收敛能力.最后通过典型的TSP实例检验改进前后的蚁群算法.仿真结果表明,改进的蚁群算法能够加快算法的收敛速度,提高算法的精准度.
Aiming at the shortcomings of the basic ant colony algorithm in the optimal path selection and slow convergence speed,a new improved method is proposed for the initial pheromone distribution and pheromone volatility.Firstly,the initial pheromone was reset according to the global path so that the blind search path is no longer used in the early stage of the algorithm and the convergence speed is accelerated.Then the second volatilization of pheromone was carried out to improve the precision and convergence of the algorithm.Finally,the effectiveness of the improved algorithm was tested by classical Traveling Salesman Problems.The simulation results show that the improved ant colony algorithm can speed up the algorithm′s convergence rate and improve its accuracy.
作者
何亮亮
王晓东
HE Liangliang;WANG Xiaodong(School of Science, Xi′an Polytechnic University, Xi′an 710048, China)
出处
《西安工程大学学报》
CAS
2018年第6期739-744,共6页
Journal of Xi’an Polytechnic University
基金
陕西省自然科学基金(2016JM1031)
关键词
蚁群算法
初始信息素
挥发因子
二次挥发
旅行商问题
ant colony algorithm
initial pheromone
volatilization factor
secondary volatilization
traveling salesman problem
