Migration effects on tree topology of parallel evolutionary computation
Migration effects on tree topology of parallel evolutionary computation
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DOI：
10.1109/tencon.2010.5686041
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发表时间：
2010-11
期刊：
影响因子：
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通讯作者：
Hayato Miyagi;Takeshi Tengan;Said Mohamed;Morikazu Nakamura
中科院分区：
文献类型：
--
作者：
Hayato Miyagi;Takeshi Tengan;Said Mohamed;Morikazu Nakamura
在进化计算的分布式并行处理中，个体在岛屿之间的迁移在许多情况下是有效的。然而，迁移的有效性取决于许多因素，如迁移频率，迁移拓扑结构，迁移规模，时间，等等。我们的研究的目的是调查这些因素设计高效的并行进化计算。本文分析了树基岛模型在并行遗传算法和并行PBIL（Population Based Incremental Learning）中的迁移效应。计算实验表明了并行进化计算的迁移效果以及迁移拓扑和频率的影响。
Migration of individuals among islands is effective in many cases in distributed parallel processing of the evolutionary computation. However, the effectiveness of migration depends on many factors such as migration frequency, migration topologies, migration scale, timing, and so on. The objective of our research is to investigate such factors for designing efficient parallel evolutionary computation. In this paper we analyzes the migration effects of the tree based island model in parallel genetic algorithms and parallel PBIL (Population Based Incremental Learning). Computational experiment shows us migration effects of the parallel evolutionary computation and influence of the migration topology and frequency.