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Computer Engineering ›› 2011, Vol. 37 ›› Issue (3): 155-157. doi: 10.3969/j.issn.1000-3428.2011.03.055

• Networks and Communications • Previous Articles     Next Articles

Research on Multicast Routing Optimization Based on Chaos Genetic Algorithm

ZOU En, LIU Ze-hua, FANG Shi-yong, XIN Jian-tao, LIN Jin-qian   

  1. (Key Laboratory of Key Technology on Agricultural Machine and Equipment of Ministry of Education, South China Agricultural University, Guangzhou 510642, China)
  • Online:2011-02-05 Published:2011-01-28

基于混沌遗传算法的组播路由优化研究?

邹 恩,刘泽华,方仕勇,辛建涛,林锦钱   

  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)
  • 作者简介:邹 恩(1956-),女,教授、博士,主研方向:神经网络,模糊控制,混沌优化;刘泽华、方仕勇、辛建涛、林锦钱,硕士研究生
  • 基金资助:
    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)

Abstract: The introduction of chaos Genetic 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.

Key words: Tent chaos map, Genetic Algorithm(GA), QoS multicast routing, optimization

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。

关键词: Tent混沌映射, 遗传算法, QoS组播路由, 优化

CLC Number: