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Quick convergence of genetic algorithm for QoS-driven web service selection

机译:QoS驱动的Web服务选择的遗传算法快速收敛

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摘要

A novel quickly convergent population diversity handling genetic algorithm (CoDiGA) is presented for web service selection with global Quality-of-Service (QoS) constraints. CoDiGA is characterized by good stability and quick convergence. In CoDiGA, an enhanced initial population policy and an evolution policy are proposed based on population diversity and a relation matrix coding scheme. The integration of the two policies overcomes shortcomings resulting from randomicity of genetic algorithm, such as slow convergence, great variance among the running results, soaring overhead along with increasing size of composition. The simulation results on web service selection with global QoS constraints have shown that prematurity was overcomed effectively, and convergence and stability of genetic algorithm were improved greatly.
机译:提出了一种新颖的快速收敛的人口多样性处理遗传算法(CoDiGA),用于具有全球服务质量(QoS)约束的网络服务选择。 CoDiGA具有良好的稳定性和快速收敛的特点。在CoDiGA中,基于人口多样性和关系矩阵编码方案,提出了增强的初始人口政策和进化政策。两种策略的集成克服了遗传算法的随机性所带来的缺点,例如收敛速度慢,运行结果之间存在较大差异,开销急剧增加以及组合的大小增加。针对具有全局QoS约束的Web服务选择的仿真结果表明,有效克服了早熟问题,大大提高了遗传算法的收敛性和稳定性。

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