Distributed Genetic Algorithm using Automatic Migration Control


The KIPS Transactions:PartB , Vol. 17, No. 2, pp. 157-162, Apr. 2010
10.3745/KIPSTB.2010.17.2.157,   PDF Download:

Abstract

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 algorithms 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 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.


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Cite this article
[IEEE Style]
H. J. Lee, Y. C. Na, J. H. Yang, "Distributed Genetic Algorithm using Automatic Migration Control," The KIPS Transactions:PartB , vol. 17, no. 2, pp. 157-162, 2010. DOI: 10.3745/KIPSTB.2010.17.2.157.

[ACM Style]
Hyun Jung Lee, Yong Chan Na, and Ji Hoon Yang. 2010. Distributed Genetic Algorithm using Automatic Migration Control. The KIPS Transactions:PartB , 17, 2, (2010), 157-162. DOI: 10.3745/KIPSTB.2010.17.2.157.