摘要
分析了蚁群算法及其参数,找到了算法中蚂蚁个数与节点个数的关系,提出了两项参数改进方案——使用自适应调整q0参数和使用精英策略局部更新信息素,对蚁群算法进行优化。通过Matlab仿真试验分析,找出了参数的最佳取值范围,使得新的蚁群算法能以较快的速度找到较优的路径,提高了蚁群算法的效率。
The ant colony algorithm （ACA） and its parameters is analyzed, and find out the relationship between the ant number and the point number is determined in this paper. Then two new improvement strategies to optimize the ant colony algorithm are proposed：one is the real-time adjusting self-adapted parameter q0 according to iteration, another is updating the local information by an outstanding strategy. By using the simulation of Matlab, the best range of the parameter is found, which makes the new ant algorithm locate the optimal path with less computing time, and the algorithm＇s efficiency is improved significantly.
出处
《天津工程师范学院学报》
2009年第3期30-33,共4页
Journal of Tianji University of Technology and Education
关键词
蚁群算法
参数优化
仿真
ant colony algorithm
parameters optimization
simulation
