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A Multi-granularity Evolution Based Quantum Genetic Algorithm For Qos Multicast Routing Problem In Wdm Networks

机译:WDM网络中一种基于多粒度进化的量子遗传算法求解Qos组播路由问题

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摘要

QoS multicast routing problem in WDM networks is investigated, and an improved algorithm Multi-granularity Evolution based Quantum Genetic Algorithm (MEQGA) is proposed to address it. Based on Quantum Genetic Algorithm (QGA) with quantum rotation gate strategy, MEQGA introduces multi-granularity evolution mechanism, which allows different chromosomes of one generation to have different rotation angle step values to update. In term of this mechanism, MEQGA can significantly improve its capability of exploration and exploitation, since its optimization performance does not over-depend on the single rotation angle step scheme shared by all chromosomes any longer. MEQGA also presents an adaptive quantum mutation operation which is able to avoid local search efficiently. A repair method is applied to eliminate illegal graphs as many as possible hence more excellent solutions will appear in each evolutionary generation. Simulation results show that, for the QoS multicast routing problem, MEQGA outperforms other heuristic algorithms and is characterized by robustness, high success ratio, fast convergence and excellent capability on global searching.
机译:研究了WDM网络中的QoS组播路由问题,提出了一种改进的基于多粒度进化的量子遗传算法(MEQGA)。 MEQGA基于具有量子旋转门策略的量子遗传算法(QGA),引入了多粒度进化机制,该机制允许一代中不同的染色体具有不同的旋转角度步长值进行更新。按照这种机制,MEQGA的优化性能不再过度依赖于所有染色体共享的单个旋转角步进方案,因此可以显着提高其勘探和开发能力。 MEQGA还提出了一种自适应量子突变操作,该操作能够有效避免局部搜索。应用了一种修复方法来消除尽可能多的非法图,因此在每个进化代中都会出现更出色的解​​决方案。仿真结果表明,对于QoS组播路由问题,MEQGA优于其他启发式算法,具有健壮性,高成功率,快速收敛性和出色的全局搜索能力。

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