摘要
分析了蚁群算法局部信息素更新系数与全局信息素更新系数对算法寻优能力与收敛速度的关系,定义平均路径相似度(ATS)来表征寻优过程的成熟程度,并据此自适应调整信息素更新系数,提高算法收敛速度并避免陷入局部最优。经过与典型蚁群算法在多个旅行商问题测试用例上进行比较,表明该算法效果更好。
The relation between updating parameters of local pheromones and global pheromones of ant colony optimisation with regard to search ability and convergence speed of the algorithm is analysed.Average path similarity is defined to represent the maturity degree in optimisation search process,and the updating parameters of pheromones are adaptively adjusted accordingly,the convergence speed is raised as to prevent falling into local optimal as well.The comparison between the algorithm in this paper and the typical ant colony algorithm on the test cases on TSP problem indicate that the former has better effect.
出处
《计算机应用与软件》
CSCD
2010年第11期239-241,249,共4页
Computer Applications and Software
基金
德州市项目基金(20090162-8)
关键词
蚁群优化
平均路径相似度
自适应参数控制
Ant colony optimisation
Average path similarity
Adaptive parameters control
