摘要
人工免疫算法具有快速随机的全局搜索能力,但系统中的反馈信息利用不足且有大量无为的冗余迭代。蚁群算法具有分布式并行全局搜索能力,但初期信息素匮乏。本文提出一种基于人工免疫-蚁群算法的混合算法,采用人工免疫算法生成信息素分布,利用蚁群算法求优化解。将该算法用于求解包含带宽、时延和最小代价约束条件在内的平面QoS路由模型问题,进行计算机仿真。结果表明,该算法是一种收敛速度和寻优能力都比较好的优化方法。
Artificial hnmune Algorithm has the ability of doing a global searching quickly and stochastically. But it can' t make use of enough system output information and has to do a large redundancy repeat searching for the optimal solution. Ant Colony Mgorithm converges on the optimal path through pheromone accumulation and renewal, it has the ability of parallel processing and global searching. But it is poor pheromone on the path early. A hybrid algorithm based on Artificial Immune-Ant Colony Algorithm was propose. It adopts Artificial Immune Algorithm to give pheromone to distribute and makes use of Ant Colony Mgorithm to give the optimal solution. The computer simulation results show that the proposed algorithm is better than the previous two algorithms on the convergence speed and ability of searching for approximate global optimal solution.
出处
《河北工程大学学报(自然科学版)》
CAS
2007年第3期76-79,共4页
Journal of Hebei University of Engineering:Natural Science Edition
关键词
人工免疫算法
蚁群算法
QOS
路由算法
Artificial Immune Algorithm(AIA)
Ant Colony Algorithm(ACA)
QoS
routing algorithm