Analysis of Scalable Parallel Evolutionary Algorithms
Analysis of Scalable Parallel Evolutionary Algorithms
复制标题
可扩展并行进化算法分析
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
X. Yao
中科院分区：
文献类型：
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作者：
Jun He;X. Yao
进化算法的内在并行性被认为是进化算法最重要的优点之一。对可扩展并行进化算法的加速比进行了初步研究。首先描述了可扩展并行进化算法;然后基于首命中时间定义了此类可扩展算法的加速比;利用新定义分析了种群多样性与超线性加速比之间的关系;最后通过一个实例说明种群多样性在产生超线性加速比中的重要作用。
Inherent parallelism is regarded as one of the most important advantages of evolutionary algorithms. This paper aims at making an initial study on the speedup of scalable parallel evolutionary algorithms. First the scalable parallel evo lutionary algo rithms are described; then the speedup of such scalable algorithms is defined based on the first hitting time; Using the new definition, the relationship between population diversity and superlinear speedup is analyzed; finally a case study demonstra tes how population diversity plays a crucial role in generating the superlinear speedup.