| Combining Single（Mixed） Metric Approach and Genetic Algorithm for QoS Routing Problem |
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| 引用本文： | 胡世余,谢剑英.Combining Single（Mixed） Metric Approach and Genetic Algorithm for QoS Routing Problem[J].西南交通大学学报(英文版),2004,12(1):20-24. |
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| 作者姓名： | 胡世余 谢剑英 |
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| 作者单位： | Automation Research Institute，Automation Research Institute Shanghai Jiaotong University，Shanghai 200030，China，Shanghai Jiaotong University，Shanghai 200030，China |
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| 摘 要： | A hybrid algorithm for the delay constrained least cost path problem is proposed through combination of single(mixed)metric approach and genetic algorithm．Compared with the known genetic algorithm for the same problem，the new algorithm adopts integral coding scheme and new genetic operator，which reduces the search space and improves the efficiency of genetic operation．Meanwhile，the single(mixed)approach accelerates the convergence speed．Simulation results indicate that the proposed algorithm can find near-optimal even optimal solutions within moderate numbers of generations．
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| 关 键 词： | 服务品质 QoS路由选择 遗传算法 带宽 计算机网络技术 |
Combining Single (Mixed) Metric Approach and Genetic Algorithm for QoS Routing Problem |
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| Hu Shiyu Xie Jianying Automation Research Institute,Shanghai Jiaotong University,Shanghai ,China.Combining Single (Mixed) Metric Approach and Genetic Algorithm for QoS Routing Problem[J].Journal of Southwest Jiaotong University,2004,12(1):20-24. |
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| Authors: | Hu Shiyu Xie Jianying Automation Research Institute Shanghai Jiaotong University Shanghai China |
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| Institution: | Automation Research Institute, Shanghai Jiaotong University, Shanghai 200030, China |
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| Abstract: | A hybrid algorithm for the delay constrained least cost path problem is proposed through combination of single (mixed) metric approach and genetic algorithm. Compared with the known genetic algorithm for the same problem, the new algorithm adopts integral coding scheme and new genetic operator, which reduces the search space and improves the efficiency of genetic operation. Meanwhile, the single (mixed) approach accelerates the convergence speed. Simulation results indicate that the proposed algorithm can find near-optimal even optimal solutions within moderate numbers of generations. |
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| Keywords: | QoS QoS routing Genetic algorithm |
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