基于混沌遗传算法的多目标QoS组播路由优化  

Optimization of Multi-Objective QoS Multicast Routing Based on Chaotic Genetic Algorithm

作　　者：邹恩[1] 蓝江林[1,2] 刘泽华[1] 方仕勇[1] 

机构地区：[1]华南农业大学工程学院,广东广州510642 [2]华南理工大学自动化科学与工程学院,广东广州510641

出　　处：《湖南工业大学学报》2012年第1期70-73,共4页Journal of Hunan University of Technology

基　　金：国家863计划基金资助项目(2006AA10Z262);广东省科技厅产学研结合基金资助项目(2010B090400451);华南农业大学校长基金资助项目(K071700;2008X004);广东省大学生创新基金资助项目(1056410009)

摘　　要：针对遗传算法易发生早熟收敛的缺点,提出了一种既满足时延、时延抖动及带宽等约束,又能使通信代价最小的混沌遗传算法。该算法利用混沌扰动算子对种群进行扰动操作,增加种群的多样性,抑制遗传早熟收敛的发生,提高收敛速度。仿真结果表明了该算法的有效性、快速收敛性及稳定性。To overcome the drawback that the premature convergence is liable to take place m geneuc algonmm, a lowest cost chaotic genetic algorithm with delay, delay jitter and bandwidth constraints is proposed. Introducing the chaotic perturbation to operate the population with a perturbation, the proposed algorithm is employed to maintain the diversity of the population in genetic algorithm, thus to overcome the premature and improve the convergence rate. The simulation results show that the proposed algorithm is effective, quick and stable.

关 键 词：混沌优化 遗传算法 QOS组播路由 

分 类 号：TP313.8[自动化与计算机技术—计算机软件与理论]