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- W2155226790 abstract "This paper shows how the extended compact genetic algorithm can be scaled using data-intensive computing techniques such as MapReduce. Two different frameworks (Hadoop and MongoDB) are used to deploy MapReduce implementations of the compact and extended compact genetic algorithms. Results show that both are good choices to deal with large-scale problems as they can scale with the number of commodity machines, as opposed to previous efforts with other techniques that either required specialized high-performance hardware or shared memory environments." @default.
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- W2155226790 date "2010-07-01" @default.
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- W2155226790 title "Scaling eCGA model building via data-intensive computing" @default.
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- W2155226790 doi "https://doi.org/10.1109/cec.2010.5586468" @default.
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