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CEC
2009
IEEE

Distributed genetic algorithm using automated adaptive migration

9 years 6 months ago
Distributed genetic algorithm using automated adaptive migration
—We present a new distributed genetic algorithm that can be used to extract useful information from distributed, large data over the network. The main idea of the proposed algorithm is to determine how many and which individuals move between subpopulations at each site adaptively. In addition, we present a method to help individuals from other subpopulations not be weeded out but adapt to the new subpopulation. We apply our distributed genetic algorithm to the feature subset selection task which has been one of the active research topics in machine learning. We used six data sets from UCI Machine Learning Repository to compare the performance of our approach with that of the single, centralized genetic algorithm. As a result, the proposed algorithm produced better performance than the single genetic algorithm in terms of the classification accuracy with the feature subsets.
Hyunjung Lee, Byonghwa Oh, Jihoon Yang, Seonho Kim
Added 21 Jul 2010
Updated 21 Jul 2010
Type Conference
Year 2009
Where CEC
Authors Hyunjung Lee, Byonghwa Oh, Jihoon Yang, Seonho Kim
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