摘要
针对传统蚁群算法存在效率低、收敛速度慢、易陷入局部最优解等问题,笔者提出一种改进的蚁群算法。该算法在启发函数中引入距离启发因子,使蚂蚁在路径搜索过程中具有导向性,使算法不易陷入局部最优解。研究结果表明,所提出的改进蚁群算法能够有效、快速地找到最优路径,而且路径质量优于传统蚁群算法规划出的路径。
Aiming at the problems of traditional ant colony algorithm such as low efficiency,slow convergence speed,and easy to fall into local optimal solution,the author proposes an improved ant colony algorithm.The algorithm introduces a distance heuristic factor into the heuristic function,which makes the ants have the orientation in the path search process,and makes the algorithm not easy to fall into the local optimal solution.The research results show that the proposed improved ant colony algorithm can find the optimal path efficiently and quickly,and the quality of the path is better than the path planned by the traditional ant colony algorithm.
作者
张小龙
李燕
黄永良
卢峥松
ZHANG Xiaolong;LI Yan;HUANG Yongliang;LU Zhengsong(School of Automation,Nanjing University of Information Science and Technology,Nanjing Jiangsu 210044,China;College of Internet of Things Engineering,Binjiang College,Nanjing University of Information Science and Technology,Wuxi Jiangsu 214105,China)
出处
《信息与电脑》
2021年第8期63-66,共4页
Information & Computer
关键词
蚁群算法
启发函数
路径规划
栅格法
ant colony algorithm
heuristic function
path planning
grid method
