基于混沌遗传算法的组播路由优化研究  

Research on Multicast Routing Optimization Based on Chaos Genetic Algorithm

作　　者：邹恩[1] 刘泽华[1] 方仕勇[1] 辛建涛[1] 林锦钱[1] 

机构地区：[1]华南农业大学南方农业机械与装备关键技术省部共建教育部重点实验室,广州510642

出　　处：《计算机工程》2011年第3期155-157,共3页Computer Engineering

基　　金：国家"863"计划基金资助项目(2006AA10Z262);华南农业大学校长基金资助项目(K07170;2008X004)

摘　　要：在采用混沌遗传算法优化多目标QoS组播路由时,为克服Logistic映射收敛速度不快,而使传统混沌遗传算法优化效果不好的缺陷,将Tent混沌遗传算法引入QoS组播路由问题的求解中。该算法利用Tent混沌映射优越的区间均匀搜索能力,对通过遗传优选出的个体再次进行混沌优化,优化出适应度最高的个体进行交叉变异,从而保证足够多的下一代,以致算法不会陷入早熟。仿真结果表明,该算法优于Logistic混沌遗传算法,有效地改进了搜索效率,且收敛速度更快、更稳定。The introduction of chaos Ganetic Algorithm（GA） to optimize multi-objective QoS multicast routing, is to overcome the convergence of logistic map isn＇t fast enough, will affect the efficiency of the tradition chaos genetic algorithm. A new kind of chaos GA based on Tent map chaos GA is introduced to the solving of QoS multicast routing in this paper. The excellent interval uniform search capability of tent map is used, chaos optimization again to individuals which are selected out of the genetic optimization, optimizing the highest fitness individuals to crossover and mutation, to ensure a sufficient number of the next generation, and algorithm will not fall into premature. Simulation results show the algorithm is better than Logistic chaos GA, which is effective to improve the search efficiency, speed up the convergence and make it more stable.

关 键 词：Tent混沌映射 遗传算法 QOS组播路由 优化 

分 类 号：N945[自然科学总论—系统科学]