一种解决网络编码资源优化问题的自适应量子衍生进化算法  

Adaptive quantum-inspired evolutionary algorithm for network coding resources optimization

作　　者：付佳[1] 纪越峰[1] 

机构地区：[1]北京邮电大学信息光子学与光通信教育部重点实验室,北京100876

出　　处：《中国科技论文在线》2011年第1期20-24,共5页

基　　金：高等学校博士学科点专项科研基金资助项目(200800130001)

摘　　要：在构建一棵满足可达组播速率的组播树过程中,尽可能地减少网络编码操作次数能降低网络的整体代价。针对网络编码组播中的编码资源优化问题提出一种基于汉明距离的自适应量子衍生进化算法。该算法充分考虑到种群个体间的差异性,为每个个体自适应地分配一个适合于自身进化的角步长,通过这种动态的角步长旋转机制进行种群的更新。将所提算法与基本量子衍生进化算法和基于适应度的自适应量子衍生进化算法进行比较分析,通过对不同的拓扑仿真进行性能评估。结果表明,基于汉明距离的自适应量子衍生进化算法在收敛速度、全局优化效果等方面均明显优于其他算法。A reduction of network coding operation leads to a lower network cost while constructing a multicast tree which meets the given multicast rate.An adaptive quantum-inspired evolutionary algorithm based on hamming distance was proposed to optimize the network coding resources.This adaptive algorithm takes the difference among the individuals into consideration,and then distributes a suitable rotation angle step for each individual.A performance comparison over three different scenarios has been conducted among our proposed algorithm,basic quantum-inspired evolutionary algorithm and an adaptive quantum-inspired evolutionary algorithm based on the individual＇s fitness.The results provide a solid demonstration that the proposed algorithm is far superior over the other algorithms in terms of the convergence speed and the global optimization ability.

关 键 词：网络编码 量子衍生进化算法 资源优化 汉明距离 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]