摘要
为了克服蚁群算法 (Ant Colony Optimization,ACO)收敛速度慢 ,易限于局部最小点等缺陷 ,对 ACO进行了改进 ,在每次循环结束时 ,保留最优解 ,自适应地改变挥发度系数 ,引入遗传算法的交叉算子 ,提出了一种基于 ACO的有时延约束的多播路由算法模型 .仿真结果表明 ,基于改进 ACO的多播路由算法模型可以稳定地获得优于现有启发式算法的解 ,是一种有效的多播路由算法 。
The performance of ant colony optimization (ACO) was improved. The best result is reserved every circulation and the volatility parameter is varied adaptively. The cross operation of genetic algorithm is introduced into the ACO. The simulation shows that the results of this algorithm for multicast routing are better than that of the heuristic algorithms. This algorithm is also well suited for parallel implementation and execution.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2002年第4期526-528,531,共4页
Journal of Shanghai Jiaotong University
关键词
蚁群算法
多媒体网络
多播路由算法
最小代价树
ant colony optimization(ACO)
multimedia network
multicast routing
minimum cost tree
