混合智能算法在多约束优化问题中的应用  

Application of mixed intelligence algorithm in multi-constrained optimization problem

作　　者：朱玉平[1] 叶大振[1] 王锁萍[1] 吴新余[1] 

机构地区：[1]南京邮电大学,南京210003

出　　处：《计算机应用研究》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)

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.

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 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]