摘要
提出了一种将蚁群算法、遗传算法和粒子种群优化融合的混合智能算法来解决多约束最优路径和QoS路由问题。采用蚁群算法进行寻径生成初始群体,利用遗传算法对路径进行优化,利用PSO算法来优化蚁群算法中的信息素,优势互补。仿真结果表明该算法是可行、有效的。
This paper proposed a mixed intelligence algorithm to solve multi-constrained optimal path and QoS routing that was based on the combination of ant colony algorithm, genetic algorithm and particle swarm optimization. First, it adopted ant colony algorithm to get a new population by routing. Second, it made use of the genetic algorithm to optimize the path, the PSO algorithm to optimize the pheromone in ant colony algorithm. Finally, it developed enough advantage of the three algorithms. The simulation results show that the algorithm is feasible and effectiee.
出处
《计算机应用研究》
CSCD
北大核心
2008年第4期1039-1042,1045,共5页
Application Research of Computers
基金
江苏省教育厅基金资助项目(03KJD510159)
关键词
多约束最优路径
QOS路由
蚁群算法
遗传算法
粒子种群优化
multi-constrained optimal path
QoS routing
ant colony algorithm
genetic algorithm
particle swarm optimization