A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
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 specializeddoi:10.1109/cec.2010.5586468 dblp:conf/cec/VermaLVGC10 fatcat:mzgehg2ownbw7hfp5hyqmjen2y