A library to run evolutionary algorithms in the cloud using mapreduce

Authors:
Pedro Fazenda;James McDermott;Una-May O'Reilly
Affiliations:
Institute for Systems and Robotics, IST, Lisbon, Portugal and Evolutionary Design and Optimization Group, CSAIL, MIT;Evolutionary Design and Optimization Group, CSAIL, MIT;Evolutionary Design and Optimization Group, CSAIL, MIT
Venue:
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Year:
2012

Citing 7
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Abstract

We discuss ongoing development of an evolutionary algorithm library to run on the cloud. We relate how we have used the Hadoop open-source MapReduce distributed data processing framework to implement a single "island" with a potentially very large population. The design generalizes beyond the current, one-off kind of MapReduce implementations. It is in preparation for the library becoming a modeling or optimization service in a service oriented architecture or a development tool for designing new evolutionary algorithms.