摘要
为在加快算法收敛速度的同时又能避免停滞现象,提出一种基于混合行为的蚁群算法.首先就蚂蚁行为对算法性能的影响进行了分析,在此基础上提出了该算法的模型;然后定义了蚂蚁行为,并为该算法设计了4种具体的蚂蚁行为,根据模型实现了该算法.实验结果表明,该算法在性能上远优于蚂蚁系统.
In order to accelerate the convergence rate of the algorithm while avoiding the stagnation behavior, a hybrid behavior based ant colony algorithm (HBACA) is proposed. The influence of ant behavior on performance of algorithm is analyzed and a model of ant colony algorithm is proposed. The ants behavior and four kinds of concrete ants behaviors are defined for HBACA algorithm and the algorithm is implemented based on the model. The experimental results show that HBACA algorithm is better than ant systems.
出处
《控制与决策》
EI
CSCD
北大核心
2005年第1期69-72,共4页
Control and Decision
基金
重庆大学基础及应用基础研究项目(717411061).
关键词
蚁群算法
混合行为
旅行商问题
Convergence of numerical methods
Learning algorithms
Traveling salesman problem
